Methods and compounds for promoting survival of photoreceptors

Abstract

The disclosure relates to methods of treating photoreceptor disease and / or inhibiting degeneration or death of photoreceptors. The methods comprise administering to a subject in need thereof a therapeutically effective amount of an inhibitor of mitogen-activated protein kinase 11 (MAPK11), an inhibitor of casein kinase 1 (CK1), or combinations thereof. This disclosure also relates to certain inhibitors of MAPK11 or CK1 and to pharmaceutical compositions that contain such inhibitors.

Description

[0001] Atorney Docket No. : 761131.152320

[0002] METHODS AND COMPOUNDS FOR PROMOTING SURVIVAL OF PHOTORECEPTORS

[0003]

[0001] The present application claims the benefit of U.S. Provisional Application No. 63 / 696,182, filed on September 18, 2024, the entire contents of which are incorporated herein by reference.

[0004] BACKGROUND

[0005] [1] Blindness is the complete or nearly complete loss of vision and in most forms is incurable. It is estimated that 43 million people were blind in 2020 (GBD 2019 Blindness and Vision Impairment Collaborators, Lancet Glob Health, (2021), 9(2):el30-el43). One of the most common causes of blindness is retinal disease, such as degeneration or dysfunction of retinal photoreceptors cells and the consequent loss of light sensitivity. In a certain subset of blind patients, studies have shown that cone photoreceptors remain alive in a dormant stage (Cideciyan and Jacobson, Invest Ophthalmol. Vis. Sci. (2019), 60(5): 1680-1695).

[0006] [2] Human organoids are three-dimensional (3D) cellular assemblies grown from stem cells. They mimic the cellular architecture, cell-type diversity, and in some cases, the functionality of their corresponding organs (Lancaster and Knoblich, Science. (2014), 345; Clevers et al., Cell, (2016) 165: 1586-1597). A wide range of organoids have been generated that model organs such as the brain, retina, thyroid, heart, vasculature, lung, liver, gastrointestinal tract, pancreas, kidney, female reproductive tract, placenta, prostate, and testis (Rossi et al., Nat. Rev. Genet. (2018) 19: 671-687; Tang et al., Signal Transduc. Target. Ther. (2022) 7: 168; Chumduri et al, J. Mol. Med. Berl. Ger. (2021) 99:531-553; Patricio et al., WIREs Meeh. Dis. (2023), 15:el590). These organoids, derived from both healthy and disease-affected individuals, serve multiple purposes such as unraveling the fundamental biology of organ development and deciphering the mechanisms of genetic diseases (Clevers et al., Cell, (2016) 165: 1586-1597).

[0007] [3] Two other potential uses of human organoids are to screen for compounds that can improve or reverse a disease phenotype (Broutier et al., Nat. Med. (2017) 23: 1424-1435; Toshimitsu et al., Nat. Chem. (2022) 18:605-614; Dorgau et al., Stem Cells Transl. Med. (2022) 11: 159-177) and, in toxicology, to screen for compounds with potential side effects on specific organs . These two objectives rely on efficient and large-scale production of human organoids, as well as the comprehensive recording and analysis of phenotypic changes within 3D tissues. Atorney Docket No. : 761131.152320

[0008] Noteworthy progress has been made in screening for compounds using mouse intestinal organoids (Lukonin et al., Nature. (2020) 586:275-280) and dissociated cells from mouse retinal organoids (Chen et al., eLife. (2023) 12:e83205), contributing to our understanding of organ biology and allowing for potential therapy development. However, therapies developed in mice do not always translate to humans due to variation in cell types and molecular pathways between the two species (Srivastava, P.K., Nat. Immunol. (2000) 1:363-366; Ruvera et al., Immunity. (2008) 28:1-4; Jtittner et al. Nat. Neurosci. (2019) 22: 1345-1356). Screening of compounds in human organoids has only been done on a small scale, using fewer than sixty compounds and has been limited to cancer organoids (Broutier et al., Nat. Med. (2017) 23: 1424-1435; Toshimitsu et al., Nat. Chem. (2022) 18:605-614). Large-scale screening in human organoids for compounds that can alleviate disease phenotypes or cause harmful side effects, has not been described.

[0009] [4] The brain, including the retina, is composed of numerous cell types (Macosko et al., Cell. (2015) 161: 1202-1214; Zeng et al., Nat. Rev. Neurosci. (2017) 18:530-546) and a fundamental characteristic of brain diseases is ‘selective vulnerability’, where the pathology predominantly affects specific cell types (Fu et al., Nat. Neurosci. (2018) 21:1350-1358). For instance, in Parkinson's disease, the motor symptoms are primarily caused by targeted loss of dopaminergic neurons in the ventral substantia nigra pars compacta (Raza et al., Life Sci. (2019) 226:77-90). Similarly, in Huntington's disease, medium spiny GABAergic neurons in the striatum are particularly affected (McColgan et al., Eur. J. Neurol. (2018) 25:24-34). Given the selective vulnerability of specific cell types in various brain diseases, compound screening to find drugs that mitigate disease phenotypes in brain or retinal organoids will be most effective when they focus specifically on the cell types affected by the disease.

[0010] [5] The human retina is part of the brain (Dowling et al., Belknap Press: An Imprint of Harvard University Press. (2012), Edition 2) and contains diverse cell types arranged in five layers (Cowan et al., Cell. (2020) 182:1623-1640; Yan et al., Sci. Rep. (2020) 10:9802; Grunert et al., Prog. Retin. Eye Res. (2020) 100844). Photoreceptors sense light and transmit information to about ten different types of bipolar cells. In turn, the bipolar cells further transmit visual information to an even greater variety of ganglion cells. Ganglion cells are the output neurons of the retina, with their axons forming the optic nerve through which information is broadcast to the rest of the brain. The transmission of information from photoreceptors to bipolar cells is influenced by horizontal cells, while transmission from bipolar cells to ganglion cells is Atorney Docket No. : 761131.152320 modulated by a multitude of amacrine cell types (Dowling et al., Belknap Press: An Imprint of Harvard University Press. (2012), Edition 2).

[0011] [6] Photoreceptors in the retina are of two types: rods and cones. Rods are utilized in low- light conditions, such as at dusk, and lack of rod function results only in mild or no vision impairment (Zeitz et al., Prog. Retin. Eye Res. (2015) 45:58-110). Cones are primarily responsible for image formation in daylight and enable the high-resolution vision that allows reading and face recognition. The loss of cones or their functionality, mainly due to age-related macular degeneration or end-stage retinitis pigmentosa, results in blindness and affects over 200 million individuals worldwide (Parmeggiani et al., Curr. Genomics. (2011) 12:236-237; Vyawahare et al., Cureus. (2022) 14:e29583). In age-related macular degeneration, the dysfunction or death of cones is either a direct consequence of the disease or secondary to the dysfunction of the retinal pigment epithelium (Fleckenstein et al., Nat. Rev. Dis. Primer. (2021) 7). Retinitis pigmentosa, a group of monogenic retinal diseases, primarily affects rods (Humphries et al., Science. (1992) 256:804-808; Ferrari et al., Curr. Genomics. (2011) 12:238- 249) and cones degenerate as a secondary consequence of rod death (Narayan et al., Acta Ophthalmol. (2016) 94:748-754). The reasons behind cone degeneration in age-related macular degeneration and retinitis pigmentosa are extensively studied but are not fully understood, and several approaches are being developed to halt the degeneration process (Ait-Ali et al., Cell. (2015) 161:817-832; Amamoto et al., eLife. (2022) l l:e76389; Byrne et al., J. Clin. Invest. (2015) 125: 105-116; Leveillard et al., Nat. Genet. (2004) 36:755-759; Mohand-Said et al., Proc. Natl. Acad. Sci. (1998) 95:8357-8362; Pardue et al., Prog. Retin. Eye. Res (2018) 65:50-76; Punzo et al., Nat. Neurosci. (2009) 12:44-52; Sahel et al., Adv. Exp. Med. Biol. (2018) 1074: 499-509; Wang et al., J. Clinic. Invest (2020) 130:4360-4369; Wang et al., JCI Insight (2021) 6:el50796); Wang et al., Proc. Natl. Acad. Sci. (2019) 116: 10140-10149); Xue et al., Perspect. Med. (2023) 116:10140-10149; Xue et al., Proc. Natl. Acad. Sci. (2023) 120; Xue et al., eLife. (2021) 10; Yang et al., Mol. Ther. J. Am. Soc. Gene Ther. (2009) 17:787-795; Samardzija et al., Cell Death Differ. (2021) 28: 1317-1332; Tnfunovic et al., Hum. Mol. Genet. (2016) 25:4462- 4472; Sundaramurthi et al., Front. Cell Dev. Biol. (2020) 8:689). For retinitis pigmentosa one common theme has emerged: that cones are likely starving from the lack of glucose (Ait-Ali et al., Cell. (2015) 161:817-832; Punzo et al., Nat. Neurosci. (2009) 12:44-52; Whalley et al., Nat. Rev. Neurosci. (2009) 10:84-85; Bovolenta et al., Nat. Neurosci. (2009) 12:5-6; Krol et al., Cell. Atorney Docket No. : 761131.152320

[0012] (2015) 161:706-708). Slowing down cone degeneration in patients has so far not been achieved. Given the critical importance of cones for human vision, preserving their viability remains a significant objective in medicine.

[0013] [7] Retinal organoids were among the earliest organoids to be established (Eiraku et al., Nature. (2011) 472:51-56; Nakano et al., Cell Stem Cell. (2012) 10:771-785). Since then, the technology for developing human retinal organoids has advanced rapidly and allows for the generation of complex, five-layered organoids that are light sensitive and consist of multiple cell types resembling those found in the adult human retina (Cowan et al., Cell. (2020) 182: 1623- 1640; Zhong et al., Nat. Commun. (2014) 5:4047; Saha et al., Cell Stem Cell. (2022) 29:487- 489). Cones in human retinal organoids exhibit a close similarity to their counterparts in the adult human retina in terms of gene expression, morphology, and function (Cowan et al., Cell. (2020) 182:1623-1640; Saha et al., Cell Stem Cell. (2022) 29:487-489) and, thus, present a unique opportunity to study cone degeneration.

[0014] [8] There is a need for identifying compounds that either slow down or induce the death of cones.

[0015] [9] There is a need for assessing the safety of new compounds planned for clinical trials by identifying compounds that induce cone death and their targets.

[0016]

[0010] There is a need for therapeutic compounds that can preserve cones, paving the way for therapies that mitigate cone loss in conditions such as macular degeneration and retinitis pigmentosa.

[0017] SUMMARY

[0018]

[0011] The disclosure relates to methods of treating photoreceptor disease and / or inhibiting degeneration or death of photoreceptors. As described further herein, the methods comprise administering to a subject in need thereof a therapeutically effective amount of an inhibitor of mitogen-activated protein kinase 11 (MAPK11), an inhibitor of casein kinase 1 (CK1), or combinations thereof. This disclosure also relates to certain inhibitors of MAPK11 or CK1 and to pharmaceutical compositions that contain such inhibitors.

[0019]

[0012] In aspects this disclosure relates to methods of treating a photoreceptor disease, comprising administering to a subject in need thereof a therapeutically effective amount of an Atorney Docket No. : 761131.152320 inhibitor of mitogen-activated protein kinase 11 (MAPK11), an inhibitor of casein kinase 1 (CK1), or combinations thereof. The disclosure further relates to a method of inhibiting degeneration or death of photoreceptor cells, comprising administering to a subject in need thereof a therapeutically effective amount of an inhibitor of mitogen-activated protein kinase 11 (MAPK11), an inhibitor of casein kinase 1 (CK1), or combinations thereof. The photoreceptor can be a cone photoreceptor, a rod photoreceptor, or a combination thereof.

[0020]

[0013] The inhibitor of MAPK11 can inhibit the activity, expression, or activity and expression of MAPK11. The inhibitor of MAPK11 can directly inhibit kinase activity of MAPK11. The inhibitor of MAPK11 can be a small molecule or a protein binder that directly inhibits the kinase activity of MAPK11. The protein binder can be an antibody or antigen-binding fragment of an antibody that binds MAPK11 or a non-immunoglobulin scaffold that binds MAPK11.

[0021]

[0014] The inhibitor of MAPK11 can be a compound that targets MAPK11 for degradation. The compound can alter, silence, attenuate, or knockout expression of MAPK11.

[0022]

[0015] The inhibitor of MAPK11 can be a nucleic acid editor that alters the MAPK11 gene to reduce or prevent its expression. The nucleic acid editor can comprise a guide RNA (gRNA) selected from those disclosed in Table 3A.

[0023]

[0016] The inhibitor of MAPK11 can comprise an siRNA or shRNA that comprises a sequence complementary to (e.g., targets) a sequence in mRNA encoding MAPK11. The siRNA can comprise nucleotide sequences selected from those disclosed in Table 4A.

[0024]

[0017] The inhibitor of MAPK11 can comprise an shRNA. The shRNA can comprise nucleotide sequences selected from those disclosed in Table 5A.

[0025]

[0018] The inhibitor or MAPK11 can comprise an antisense oligonucleotide (ASO) that comprises a sequence complementary to (e.g., targets) a sequence in an RNA molecule that codes for MAPK11, such as an mRNA or pre-mRNA. The ASO can comprise nucleotide sequences selected from the group disclosed in Table 6A.

[0026]

[0019] The inhibitor of CK1 can inhibit the activity, expression, or activity and expression of CK1. The inhibitor of CK1 can directly inhibit kinase activity of CK1. The inhibitor of CK1 can be a small molecule or a protein binder that directly inhibits the kinase activity of CK1. The protein binder can be an antibody or antigen-binding fragment of an antibody that binds CK1 or a non-immunoglobulin scaffold that binds CK1. Atorney Docket No. : 761131.152320

[0027]

[0020] The inhibitor of CK1 can be a compound that targets CK1 for degradation. The compound can alter, silence, attenuate, or knockout expression of CK1.

[0028]

[0021] The inhibitor of CK1 can be a nucleic acid editor that alters the CK1 gene to reduce or prevent its expression. The nucleic acid editor can comprise a guide RNA (gRNA) selected from those disclosed in Table 3B-3G.

[0029]

[0022] The inhibitor of CK1 can comprise an siRNA or shRNA that comprises a sequence complementary to (e.g., targets) a sequence in mRNA encoding CK1. The siRNA can comprise nucleotide sequences selected from those disclosed in Table 4B-4G.

[0030]

[0023] The inhibitor of CK1 can comprise an shRNA. The shRNA can comprise nucleotide sequences selected from those disclosed in Table 5B-5G.

[0031]

[0024] The inhibitor or CK1 can comprise an antisense oligonucleotide (ASO) that comprises a sequence complementary to (e.g., targets) a sequence in an RNA molecule that codes for CK1, such as an mRNA or pre-mRNA. The ASO can comprise nucleotide sequences selected from the group disclosed in Table 6B-6G.

[0032]

[0025] The inhibitor of CK1 can be an inhibitor of CK1 alpha, CK1 delta, CK1 epsilon, CKlgammal, CKlgamma2, CKlgamma3 or any combination of the foregoing.

[0033]

[0026] In further aspects, the photoreceptor disease is cone-rod dystrophy, rod-cone dystrophy, macular degeneration, geographic atrophy, age-related macular degeneration (AMD), wet- AMD, retinitis pigmentosa, macular dystrophy, Stargardt disease, juvenile macular degeneration, achromatopsia, diabetic retinopathy, Usher syndrome, Leber congenital amaurosis (LCA), X- linked juvenile retinoschisis, or central areolar choroidal dystrophy.

[0034]

[0027] In further aspects, the subject in need thereof has cone-rod dystrophy, rod-cone dystrophy, macular degeneration, geographic atrophy, age-related macular degeneration (AMD), wet- AMD, retinitis pigmentosa, macular dystrophy, Stargardt disease, juvenile macular degeneration, achromatopsia, diabetic retinopathy, Usher syndrome, Leber congenital amaurosis (LCA), X-linked juvenile retinoschisis, or central areolar choroidal dystrophy.

[0035] BRIEF DESCRIPTION OF THE DRAWINGS

[0036]

[0028] FIGs. 1A-1C show glucose starvation induces rapid death of cones in human retinal organoids. FIG. 1A is a schematic illustrating the transduction strategy for organoids. FIG. IB is a graph quantifying the specificity and efficacy of cone labeling by ProA7-GFP AAV. Results Atorney Docket No. : 761131.152320 are shown as mean ± sd. FIG. 1C is a graph quantifying cone survival in human retinal organoid in both normal and low glucose conditions over seven days. The results are shown as mean ± se.

[0037]

[0029] FIGs. 2A-2F show cone glucose starvation data. FIG. 2A is a graph showing the results of a glucose consumption assay of human retinal organoids. Mean ± se from 10 human retinal organoids. FIGs. 2B and 2C are graphs showing quantification of cone survival in human retinal organoids in normal and low glucose over seven days. Quantification with either 3D-count (FIG. 2B) or MIP-count (FIG. 2C). Mean ± se. Low glucose, n=26; normal glucose, n=6. FIG. 2D-2F are graphs showing quantification of cone survival in human retinal organoids in normal and low glucose over fourteen days using all three quantification algorithms (3D-additive (FIG. 2D); 3-D count (FIG. 2E); and MIP-count (FIG. 2F)).

[0038]

[0030] FIGs. 3A-3J show the primary screen of compounds that damage or save cones. FIG. 3A is a schematic illustration of the primary screen in which (1) human retinal organoids were transferred from cell culture flasks to 96- well plates; (2) compounds were distributed from 384- to 96-well plates with five replicates of each compound and low glucose and normal glucose controls are included; (3) compounds were added to human retinal organoids; (4) human retinal organoids were imaged; and (5) cones from the same human retinal organoid were quantified at day 0 (DO) and day 7 (D7). FIG. 3B is a bar chart showing the number of compounds with a given number of targets. FIG. 3C is a bar chart showing the number of targets with a given number of compounds per target. FIG. 3D is a categorization of targets and compounds of the compound library. FIGs. 3E and 3F are graphs showing dependence of cone survival on the DO cone count. FIG 3E shows cone survival as a function of the logarithm of the cone count at DO, with a fitted linear model; the regression line is shown. The distribution of DO counts is shown above. FIG. 3F shows adjusted cone survival as a function of the logarithm of the cone count at DO with the transformed regression line. The distribution of DO counts is shown above. FIG. 3G is a graph showing adjusted cone survival of normal and low glucose controls for individual well plates and organoid batches using the 3D-additive-count algorithm, mean ± se. FIGs. 3H and 31 are graph showing adjusted cone survival of all normal and low glucose control human retinal organoids. FIG. 3J is a graph showing the effect of compounds on cone survival in the primary screen. Each dot corresponds to the effect of one compound, with the median of the adjusted cone survival of five human retinal organoids on the x-axis and the p-value comparing the cone survival between the compound and the low glucose controls on the y-axis. The medians (lines) Atorney Docket No. : 761131.152320 and the interquartile ranges (shaded areas) of normal glucose (right side) and low glucose (left side) controls are indicated. The distribution of median adjusted cone survival for compounds is shown at top. Results were obtained using the 3D-additive-count algorithm.

[0039]

[0031] FIGs. 4A-4O show data and analysis from the primary screen. FIGs. 4A-4C are graphs showing data thresholding based on counts at DO for all quantification algorithms. The dotted lines indicate the threshold beyond which wells are included in the analysis. FIGs. 4D-4G are graphs showing adjustment of cone survival values based on the DO count. (FIGs. 4D and 4E, 3D-count and FIGs. 4F and 4G, MIP-count) FIGs. 4D and 4F are graphs showing cone survival and the logarithm of the cone count at DO, fitted with a linear model. Regression line; summary statistics, top right corner of each panel. FIGs. 4E and 4G are graphs showing adjusted cone survival and the logarithm of the cone count at DO with the transformed regression line. FIG. 4H shows well position bias analysis. The means of adjusted cone survival for all wells of the primary screen data are depicted. FIGs. 4I-4L are graphs showing adjusted cone survival of normal and low glucose controls for individual well plates (FIGs. 41 and 4 J) and organoid batches (FIGs. 4K and 4L), mean ± se. (FIGs. 41 and 4K, 3D-count and FIGs. 4J and 4L, MIP- count.) FIGs. 4M and 4N are graphs showing adjusted cone survival of all normal and low glucose controls. (FIG. 4M, 3D-count and FIG. 4N, MIP-count.) FIG. 40 is a graph showing adjusted cone survival of normal and low glucose controls for individual experiments (groups of 5 well plates containing all replicates for compounds) using the 3D-additive-count algorithm, mean ± se.

[0040]

[0032] FIGs. 5A-5H show data from the primary screen and comparison of different quantifications. FIGs. 5A-5F are graphs illustrating results of different quantification methods comparing adjusted cone survival values of individual organoids (FIG. 5A-5C) or the median of adjusted cone survival values for individual compounds (FIGs. 5D-5F). The dotted line represents the unity line and ‘R’ denotes the Pearson’s correlation coefficient. FIGs. 5G and 5H are graphs showing the effect of compounds on cone survival in the primary screen. (FIG. 5G: 3D-count, and FIG. 5H: MIP-count.) Each dot corresponds to the effect of one compound, with the median of the adjusted cone survival of five human retinal organoids on the x-axis and the p- value comparing the cone survival in the compound and in low glucose on the y-axis. The medians (lines) and the interquartile ranges (shaded areas) of normal glucose (right side) and low Atorney Docket No. : 761131.152320 glucose (left side) controls are indicated. The distribution of median adjusted cone survival for compounds is shown at top.

[0041]

[0033] FIGs. 6A-6R show data from the secondary screen of cone-damaging compounds. FIG. 6A is a schematic illustration of the plate layout in the secondary screen for cone-damaging compounds. Different shades represent distinct compounds. No compound control, far right top. FIG. 6B is a heat map summary of compound effects for significant cone-damaging compounds (p<0.05 for at least one concentration after Benjamini Hochberg correction for multiple testing). The positive control was Staurosporine. Compounds are ordered by minimum p-value per concentration, with the smallest p-value at the top. FIGs. 6C-6F are graphs showing doseresponses for significant compounds within the same cluster. Dots represent the median of cone survival at the indicated concentrations. The median (lines) and the interquartile range of normal glucose controls are indicated. FIGs. 6G-6O are graphs showing dose-response curves of eight compounds with the lowest p-values (at any concentration) and Staurosporine. ITK and beta- catenin inhibitors are in cluster 1, BCL2L1, AP-1 immunoprotease and AAA ATPase p97 inhibitors are in cluster 2, sodium ionophor is in cluster 3, and HD AC inhibitor 3 and staurosponine are in cluster 4. The median and the interquartile range are labeled as in FIGs. 6C-6F. Significant compounds and concentrations are marked with *, denoting a p-value<0.05 (after Benjamini Hochberg correction for multiple testing). FIG. 6P is a graph showing adjusted cone survival and p-values in the primary screen for HD AC I / II, HD AC III, and tubulin. The medians (lines) and the interquartile ranges (shaded areas) of normal (right side) and low (left side) glucose controls are indicated. FIG. 6Q is a graph showing target analysis of primary screen. The means of the median adjusted cone survival for each target are shown, along with their p-values. Compound targets are HD AC I / II, HD AC III, andtubulin. The median (line) and the interquartile range of low glucose controls are indicated. FIG. 6R are graphs showing different HD AC I / II inhibitors (numbered from 1 to 45) (top) with their targets (black shaded areas). Compounds are sorted from left to right based on median adjusted cone survival. Middle: Adjusted cone survival for each of the 45 compounds. Bottom: Number of HD AC I / II targets of the 45 compounds.

[0042]

[0034] FIGs. 7A-7M show data and analysis from the secondary screen for cone-damaging compounds. FIGs. 7A-7C are graphs showing thresholding of data for the secondary screen of cone-damaging compounds based on counts at DO for all quantification methods. The dotted line Atorney Docket No. : 761131.152320 indicates the threshold beyond which wells are included in the analysis. FIGs. 7D-7F are graphs showing the effect of DO count on cone survival and the logarithm of the cone count at DO, fitted with a linear model. The regression line is shown and the summary statistics are displayed at top right. FIGs. 7G-7I are graphs showing cone survival for normal glucose controls with indicated means for all three quantification methods. FIGs. 7J-7L are heat map summaries of the effects of all cone-damaging compounds tested in the secondary screen. The positive control is Staurosporine. Compounds are sorted by the minimum p-value across all concentrations, with the smallest p-value at the top. Significant compounds (at any concentration) are marked with *, denoting a p-value<0.05 (after Benjamini Hochberg correction for multiple testing). FIG. 7M is a graph depicting target analysis showing the number of compounds against the fraction of compounds having a significant cone-damaging effect (p-values<0.05, after Benjamini Hochberg correction for multiple testing) for all targets with more than two compounds.

[0043]

[0035] FIGs. 8A-8Y show data and dose-response curves from the secondary screen for conedamaging compounds Dose-response curves of all secondary screen cone-damaging compounds are shown, excluding those depicted in FIGs. 6G-6O. The compounds analyzed in FIGS 8A-8P are from cluster 1, FIG 8Q is from cluster 2, FIGs. 8R and 8S are from cluster 3 and FIGs. ST- SY are from cluster 4. Black dots denote median cone survival, gray dots represent individual values. The line and shaded area indicate median and interquartile range of the normal glucose controls, respectively. The structure of each compound is illustrated within the plot. Significant compounds and concentrations are marked with * denoting a p-value<0.05 (after Benjamini Hochberg correction for multiple testing).

[0044]

[0036] FIGs. 9A-9N show the secondary screen of cone-saving compounds. FIG. 9A is a schematic illustration of plate layout in the secondary screen for cone-saving compounds. Different shades indicate distinct compounds and low glucose controls and normal glucose controls are included. FIGs. 9B-9E are graphs showing dose-response curves of the four significant compounds. Black dots, median adjusted cone survival; gray dots, individual adjusted cone survival values. The medians (lines) and the interquartile ranges (shaded areas) of normal (upper) and low glucose (lower) controls are indicated. The structure of each compound is shown in the plot and the annotated target is indicated on top. FIGs. 9F-9G are graphs showing (left) adjusted cone survival and p-values of the four significant compounds identified in the secondary screen ( HSP90AA1, MTOR, PDGFRA, and TP53). The median and the interquartile range are Atorney Docket No. : 761131.152320 labeled as in FIGs. 9B-9E. FIG. 9G is an exploded view of the boxed region in FIG. 9F. FIG. 9H is a graph showing target analysis of the secondary screen. The means of the median adjusted cone survivals for each target are shown, along with their p-values (HSP90AA1, MT0R, PDGFRA, and TP53). The median and the interquartile range are labeled as in FIGs. 9B-9E. FIGs. 9I-K show the structures of compounds and names assigned to the compounds. FIGs. 9L- 9N are graphs showing time course of cone survival in glucose-starved human retinal organoids with the indicated compounds for 14 days. Results are shown as mean ± se.

[0045]

[0037] FIGs. 10A-100 show data and analysis from the secondary screen for cone-saving compounds. FIGs. 10A-10C are graphs showing thresholding of data for the secondary screen of cone-saving compounds based on counts at DO for all quantification methods. The dotted line indicates the threshold beyond which wells are included in the analysis. FIGs. 10D-10I are graphs showing adjustment of cone survival values based on DO counts for all quantification methods. FIGs. 10D, 10E, 10F are graphs showing cone survival and the logarithm of the cone counts at DO, fitted with a linear model. Regression line; summary statistics, top right corner of each panel. FIGs. 10G, 10H, and 101 are graphs showing adjusted cone survival and the logarithm of the cone counts at DO with the transformed regression line. FIGs. 10J-10L are graphs showing adjusted cone survival of all normal and low glucose controls for all quantification methods. FIGs. 10M-100 heat map summaries of the effects of cone-saving compounds. Compounds are sorted by the maximum median adjusted cone survival. Results are shown for all three quantification methods. Significant compounds are marked with *, denoting a p-value<0.05 (after Benjamini Hochberg correction for multiple testing).

[0046]

[0038] FIGs. 11A-Z and 11AA show data and dose-response curves from the secondary screens for cone-saving compounds. FIGs. 11A-A and 11AA are graphs showing dose-response curves of all secondary screen cone-saving compounds, excluding those depicted in FIG. 9B-E. Compounds are ordered by their maximum adjusted cone survival (most effective concentration). Black dots denote median cone survival, gray dots represent individual values. The medians (lines) and the interquartile ranges (shaded areas) of normal (upper) and low glucose (lower) controls are indicated. The structure of each compound is illustrated within the plot.

[0047]

[0039] FIGs. 12A-12M are graphs showing target analysis and IC50 data. Compound targets are indicated in the figures. FIGs. 12A-12B are graphs showing the number of compounds and fractions of compounds having a median adjusted cone survival >80% for all targets (with more Atorney Docket No. : 761131.152320 than two compounds). FIGs. 12C is a graph showing adjusted cone survival and p-values in the primary screen of normal (right line and shaded area) and low glucose controls (left line and shaded area) are indicated. FIG. 12D is an exploded vies of the boxed area in FIG. 12C. FIG. 12E is a graph showing target analysis of primary screen. The means of the median adjusted cone survival for each target are shown, along with their p-values. The median and the interquartile range are labeled as in FIGs. 12C and 12D. FIGs. 12F-12M are graphs showing median IC50 values for compounds that bind the indicated targets (labeled on top) and their median adjusted cone survival. The medians and the interquartile ranges are labeled as in FIGs. 12C and 12D.

[0048]

[0040] FIG. 13 is a bar graph showing that the compounds that target HSP90AA1I-1, CS-KI-1 or CS-KI2 had no significant effects on cone survival in organoids under normal glucose conditions after seven days. HSP90AA1I-1 was used at 1 pM, while CS-KI-1 and CS-KI2 were used at 10 pM. Results are shown as mean ± se. Black dots indicate individual organoid cone survival.

[0049]

[0041] FIGs. 14A-14D show the effect of cone-saving compounds on rods. FIG. 14A is a graph quantifying the specificity and efficacy of rod labeling by ProA330-GFP AAV. Results are shown as mean ± sd. FIGs. 14B-14D are graphs showing time courses of rod survival in glucose-starved human retinal organoids treated with the indicated compounds for 14 days. (Normal glucose control is top line, compound treated is middle line, low glucose control is bottom line.) Results are shown as mean ± se. Structures of the compounds are shown.

[0050]

[0042] FIGs. 15A-15B show specificity of the rod promoter. FIG. 15A is a graph quantifying the specificity and efficacy of rod labeling in mice by ProA330-CatCh-GFP AAV. Rods were identified as being present in the photoreceptor layer but negative for the cone-marker mCAR. Results are shown as mean ± sd. FIG. 15B is a graph showing data thresholding based on rod counts at DO. The dotted line indicates the threshold beyond which wells are included in the analysis.

[0051]

[0043] FIGs. 16A-16D show chemical structures of CS-KI-1 (FIG. 16A), CS-KI-2 (FIG. 16B) and their corresponding analogues CS-KI-1A (FIG. 16C), CS-KI-2A (FIG. 16D).

[0052]

[0044] FIGs. 16E-16F are graphs showing time courses of cone survival in glucose-starved human retinal organoids with the indicated compounds for 14 days. Results are shown as mean ± Atorney Docket No. : 761131.152320 se. Same data as in FIGs. 9M and 9N, but including the nonfunctional analogue compounds CS- KI-1A and CS-KI-2A.

[0053]

[0045] FIG. 16G shows principal component analysis of transcriptomes under the indicated conditions.

[0054]

[0046] FIGs. 16H-16J show differential gene expression comparing human retinal organoid cone and rod transcriptomes treated with the indicated conditions.

[0055]

[0047] FIGs. 17A-17E show fluorescence activated cell sorting (FACS) of photoreceptors. Representative FACS density plots from a human retinal organoid co-transduced with ProA7- GFP (which labels cones) and ProA330-tdTomato (which labels rods). All numbers are percentages of gated cells. FIG. 17A is a histogram showing forward scatter area (FSC-A) and side scatter area (SCS-A) to filter cells from debris. FIG. 17B is a histogram showing FSC-A and forward scatter height (FSC-H) to filter single cells form aggregates. FIG. 17C is a histogram showing FSC-A and Hoechst channel (DAPI-A) to sort out living cells. FIGs. 17D- 17E are histograms showing GFP (cone) and tdTomato (rod) positive cells from either nontransduced (FIG. 17D) or co-transduced (FIG. 17E) human retinal organoids.

[0056]

[0048] FIGs. 18A-18C show compound target and marker gene expression. FIG. 18A shows expression of cone (top) and rod (bottom) marker genes. Heatmap colors correspond to gene expression normalized to the row-wise maximum. Normal and low glucose conditions are indicated at the top. FIGs. 18B and 18C show expression of genes encoding annotated compound targets. TPlOk, transcript counts per 10,000.

[0057]

[0049] FIGs. 19A-19K show differential gene expression analysis of controls and HSP90AA1I- 1 treated organoids. FIGs. 19A-19F are graphs showing differential gene expression comparing human retinal organoid cone (FIGs. 19A, 19B, and 19C) and rod (FIGs. 19D, 19E, and 19F) transcriptomes in normal glucose with untreated controls (left), normal glucose to low glucose (middle), and HSP90AA1I-1 treatment in low glucose (right). Vertical dotted lines indicate foldchange threshold beyond which genes were included in analysis. Horizontal dotted line indicates the p- value beyond which genes passed the significant threshold of p<0.05 after Benjamini-Hochberg correction for multiple testing. Average gene expression in low glucose cones (FIGs. 19A, 19B, and 19C) or rods (FIGs. 19D, 19E, and 19F) are indicated. The 10 most significantly up- or downregulated genes are labeled. TPlOk, transcript counts per 10,000. FIGs. 19G-19K are heatmaps displaying gene expression levels of differentially expressed genes Atorney Docket No. : 761131.152320 across samples under specified conditions. Up to 20 up- and downregulated genes are included and ordered by p-values with the most significant p-value at the top. Heatmap shades correspond to gene expression normalized to the row-wise maximum.

[0058]

[0050] FIGs. 20A-20D show geneset enrichment analysis for HSP90AA1I-1 treated organoids. Gene Ontology terms (GO, left) and Molecular Signatures Database Terms (MSigDB, right) enrichment analysis of HSP90AA1I-1 -treated samples compared to low glucose in both cones (FIGs. 20A and 20C) and rods (FIGs. 20B and 20D). Dots represent normalized enrichment scores (NES) with their size indicating the percentage of differentially expressed genes within each gene set, and the color reflecting the adjusted p-value corrected for multiple testing (padj). All or the top 15 GO-terms are shown ordered by p-values, whereas all enriched MSigDB-terms are shown. BP: biological process, CC: cellular component.

[0059]

[0051] FIGs. 21A-21D are plots showing differential gene expression analysis for cone-saving compounds. Differential gene expression comparing human retinal organoid cones (FIGs. 21A 21B) and rods (FIGs. 21C, 21D) transcriptomes treated with CS-KI-1 compared to CS-KI-1A treatment and low glucose controls (FIGS. 21 A and 21 C), or CS-KI-2 treatment compared to CS- KI-2A treatment and low glucose controls (FIGS. 21B and 21D). Vertical dotted lines indicate the threshold beyond which genes were included in analysis. Horizontal dotted line indicates the p-value beyond which genes passed the significant threshold of p<0.05 after Benjamini- Hochberg correction for multiple testing. Shades indicate average gene expression in low glucose cones or rods. Up to 10 most significantly up- or downregulated genes are labeled. TPlOk, transcript counts per 10,000.

[0060]

[0052] FIGs. 22A-22H show Geneset enrichment analysis for cone-saving compounds. FIGs. 22A-22H show Gene Ontology (GO) terms enrichment analysis (FIGs. 22A-22D) and Molecular Signatures Database (MSigDB) terms enrichment analysis (FIGs. 22E-22H) for specified comparisons in both cones and rods. Dots represent normalized enrichment scores (NES) with their size indicating the percentage of differentially expressed genes within each gene set, and the shading reflecting the adjusted p-value corrected for multiple testing (padj). All or the top 15 GO terms (FIGs 22A-22D) or MSigDB terms (FIGs. 22E-22H) with the most significant p- values are displayed ordered by p-values.

[0061]

[0053] FIGs. 23A-23F show kinase profiling and CK-1 and MAPK11 inhibition. FIG. 23A and 23 B are plots showing kinase profiling of 350 human kinases treated with CS-KI-1 and CS-KI- Atorney Docket No. : 761131.152320

[0062] 1A or CS-KI-2 and CS-KI-2A. Percentage value of kinase activity compared to a control reaction without inhibitors. Average expression level of the kinase gene in low glucose organoid cones is indicated. Dotted vertical and horzontal lines, 100% kinase activity. Dotted diagonal lines, unity line. TPlOk, transcript counts per 10,000. FIGs, 23C and 23D are plots showing differential kinase activity comparing active compounds and their analogues and average expression levels in organoid cones. FC, foldchange. TPlOk, transcript counts per 10,000. FIGs. 23E-23F show the effects of CK-1 and MAPK11 inhibitors on cone (FIG. 23E) and rod (FIG. 23F) survival under low glucose conditions. Results are shown as mean ± se with * denoting an adjusted p-value<0.05. Black dots indicate individual organoid cone (FIG. 23E) or rod (FIG. 23F) survival.

[0063]

[0054] FIGs. 24A-24C show expression of casein kinase 1 genes and MAPK11 in human retina and organoids. CK-1 and MAPK11 gene expression in human retina fovea and periphery and human retinal organoids at week 30 (W30) from published single cell atlases. Shading indicates mean expression across all cones or rods in UMI (unique molecular identifier) counts per 10000. Dot size indicates the fraction of cones or rods expressing the indicated gene.

[0064]

[0055] FIG. 25A illustrates the structure of an exemplary inhibitor based on the miR-155 backbone. The molecule contains three siRNAs (circled) against the same target (the siRNAs can be the same or preferably different) and is processed by endogenous enzymes to obtain the siRNAs.

[0065]

[0056] FIG. 25B illustrates the structure of an exemplary AAV vector that encodes an miR-155 based shRNA.

[0066] DETAILED DESCRIPTION

[0067]

[0057] The disclosure relates to methods of treating photoreceptor disease and / or inhibiting degeneration or death of photoreceptors. As described further herein, the methods comprise administering to a subject in need thereof a therapeutically effective amount of an inhibitor of mitogen-activated protein kinase 11 (MAPK11), an inhibitor of casein kinase 1 (CK1), or combinations thereof. This disclosure also relates to certain inhibitors of MAPK11 or CK1 and to pharmaceutical compositions that contain such inhibitors.

[0068]

[0058] As described further and exemplified herein, the inventors conducted a study to identify biological targets that are involved in photoreceptor survival and compounds that can modulate Atorney Docket No. : 761131.152320 those targets and promote survival of photoreceptors. The study involved the production and use of -20,000 human retinal organoids each 30 weeks old, which is a time when organoid cone transcriptomes are similar to those of adult human retina (Cowan, C. S. etal. Cell Types of the Human Retina and Its Organoids at Single-Cell Resolution. Cell 182, 1623-1640. e34, 2020). The photoreceptors of the human retinal organoids were specifically fluorescently labeled by expression of adeno associated viral vectors (AAVs) encoding fluorescent proteins under the control of cone-specific or rod-specific promoters. Death of cone photoreceptors was induced by glucose starvation. 3D imaging of the organoids was conducted before and after the starvation process, at a time when approximately 40% of cones were lost. A library of 2,707 compounds with known targets was then evaluated for modulating cone cell death. (Canham, Systematic Chemogenetic Library Assembly. Cell Chem. Biol. 27, 1124-1129. 10.1016 / j.chembiol, 2020).

[0069]

[0059] The study identified two kinase inhibitors that consistently preserved cones over a prolonged period. Both of these inhibitors also preserved rods. Through kinase profiling of both compounds and their inactive chemical analogues, mitogen-activated protein kinase (MAPK11) and casein kinase 1 (CK1) were identified as the biological targets of the inhibitors that promoted survival of cones and rods. Inhibitors of CK1 or MAPK11 increased survival of both cones and rods. Accordingly, this disclosure relates to methods for promoting the survival of photoreceptor cells and treating photoreceptor diseases using inhibitors of MAPK11 and / or CK1, and to certain inhibitors of MAPK11 or CK1.

[0070] Mitogen-activated protein kinase 11 (MAPK11)

[0071]

[0060] Mitogen-activated protein kinase 11 (MAPK11, also known as p380) is a serine / threonine kinase which acts as an essential component of the MAP kinase signal transduction pathway. It is one of four isoforms of the p38MAPK family (MAPK11 (p380), MAPK12 (p38y), MAPK13 (p388), and MAPK14 (p38a)), which phosphorylate a broad range of proteins. MAPK11 and MAPK14 (p38a) are reported as having similar functions. MAPK1 lis activated through its phosphorylation by MAP kinase kinases (MKKs), such as MKK6. Transcription factor ATF2 / CREB2 has been shown to be a substrate of MAPK11.

[0072] Casein kinase 1 (CK1) Atorney Docket No. : 761131.152320

[0073]

[0061] Casein kinase 1 (CK1) is a family of monomeric serine- threonine protein kinases found in eukaryotic organisms. In vertebrates, there are several CK1 isoforms (including a, 0, yl, y2, y3, 8 and e isoforms) and several splice variants for CKla, 8, e and y3 have been identified. There is a high degree of homology in isoforms, e.g., CK18 and CKlc are 98% identical in their kinase domain and 53% identical in their C-terminal regulatory domain. There is some redundancy with respect to substrate phosphorylation and there are also examples of distinct biological roles for the different CK1 isoforms. Casein kinase 1 epsilon has been suggested to play a role in phosphorylation of Dishevelled in the Wnt signaling pathway. Casein kinase 1 alpha (CKla) binds to and phosphorylates 0-catenin.

[0074] MAPK11 and CK1 Inhibitors

[0075]

[0062] The inhibitors according to this disclosure can inhibit the activity, expression (e.g, transcription, translation, protein level) or activity and expression of MAPK11 or CK1 (e.g., CKla, CKlyl, CKly2, CKly3, CK18 and CKle). The inhibitors can inhibit MAPK11 of CK1 directly or indirectly. For example, the inhibitor can directly inhibit MAPK11 or CK1 by binding to the kinase and inhibiting kinase activity or causing degradation of the kinase. Such inhibitors can bind to the target kinase noncovalently or through one or more covalent bonds. In examples, the inhibitor can indirectly inhibit MAPK11 or CK1 by, for example, altering the gene encoding MAPK11 or CK1 thereby decreasing expression (e.g., transcription and / or translation) and reducing the level of MAPK11 or CK1 kinase. Many suitable MAPK11 inhibitors and CK1 inhibitors are well-known in the art and other are disclosed herein. For example, in some embodiments the inhibitor that directly inhibits MAPK11 kinase activity or CK1 kinase activity, such as a small molecule or protein binder that binds to MAPK11 or CK1, inhibits kinase activity. Such inhibitors can function through any mechanism, for example they can be competitive inhibitors, non-competitive inhibitors or allosteric inhibitors. In some aspects, the inhibitor can bind to MAPK11 or CK1 and target the kinase for degradation. The inhibitor can directly or indirectly reduce or prevent expression of MAPK11 or CK1. For example, the inhibitor can reduce or prevent transcription or translation of mRNA encoding MAPK11 or CK1, through a variety of mechanism such as gene or RNA editing, RNA degradation, inhibiting binding of ribosome to mRNA, altering RNA splicing, and the like. In other examples, the Atorney Docket No. : 761131.152320 inhibitor can reduce the level of MAPK11 of CK1 in cells, e.g., by targeting MAPK11 of CK1 for degradation.

[0076] Small Molecule Inhibitors

[0077]

[0063] Kinases can phosphorylate certain amino acids in their protein substrates using ATP as the source of phosphate. Kinase activity requires a conformational change between the inactive conformation and the active (catalytically competent) conformation. All kinases include a so- called kinase domain that comprises the ATP binding site and the amino acid residues that mediate catalytic phosphotransferase activity.

[0078]

[0064] Kinase inhibitors can be categorized into two classes according to whether they compete with ATP for binding to the kinase (Duong-Ly et al., Curr. Protoc. Pharmacol. Chapter 2, Unit 2.9, 2013 and Knight et al., Chem. Biol. 12, 621-637, 2005). Competitive inhibitors can be classified as type I and type II inhibitors (Duong-Ly et al., Curr. Protoc. Pharmacol. Chapter 2, Unit 2.9, 2013 and Liu et al., Nat. Chem. Biol. 2, 358-364, 2006). Type I inhibitors bind to the active conformation, whereas type II inhibitors bind to the inactive conformation. Type I inhibitors bind to the ATP-binding pocket through the formation of hydrogen bonds to the kinase “hinge” residues, which are just like the interaction of adenine with the kinase. In addition, hydrophobic interactions in and around the region occupied by the adenine ring of ATP are also important. However, type II inhibitors not only occupy the ATP-binding pocket but also exploit unique hydrogen bonds with the residues of a-helix and DFG motif. Kinase inhibitors that are non-ATP competing can be allosteric inhibitors that bind to allosteric pockets, e.g., that are adjacent to but do not overlap with the ATP pocket (Type III inhibitors), or that are distant from the ATP-binding pocket (Type IV inhibitors), thereby inhibiting activity of MAPK11 or CK1 (Wang et al., 2021, Signal Transduction and Targeted Therapy, 6:423).

[0079]

[0065] Preferred small molecule inhibitors of MAPK11 or CK1 bind to MAPK11 or CK1 and thus directly inhibit the kinase activity of MAPK11 or CK1. Examples include small molecules that are Type I inhibitors, Type 2 inhibitors, Type 3 inhibitors or Type 4 inhibitors. The inhibitors can bind to MAPK11 or CK1 through non-covalent and / or covalent bonds. The binding of the inhibitors to MAPK11 or CK1 can be reversible or irreversible. Atorney Docket No. : 761131.152320

[0080]

[0066] Small molecules that bind to and inhibit the kinase activity of MAPK11 are well-known in art and include, for example, losmapimod (GW856553), ralimetinib (LY2228820), doramapimod (BIRB-796), neflamapimod (VX-745), pamapimod, talmapimod (SCIO-469), AMG-548, AZD-6703, SB-239063, AZD-7624, PF-03715455, acumapimod, VX702, TAK715, BMS-582949, ARRY-797, PH-797804, FX-005, GSK-610677, LY-3007113, PF-03715455, TA- 5493. See, e.g., WO 2020 / 128528. Further exemplary MAPK11 inhibitors include SB-202190, CDD-111 (SD-0006), SB-203580, SB-242235, SC409, L-skepinone and analogs, NJK14047, and PH-797804. See also Table 1. Attorney Docket No.: 761131.152320 Atorney Docket No.: 761131.152320 Atorney Docket No. : 761131.152320

[0081]

[0067] Small molecules that bind to and inhibit the kinase activity of CK1 (e.g., CKla, CKlyl, CKly2, CKly3, CK18 and / or CK1 e) are well-known in art and include, for example, the compounds disclosed in WO 2015 / 119579, WO 2011 / 103289, WO 2012 / 080727, WO 2016 / 180981, WO 2014 / 023271 and W02005061498. Further exemplary small molecules that bind to and inhibit the kinase activity of CK1 include Hua-lh , Huang- 1, Huang 2-9, Huang 10- 15, CKI-7, IC261, Bis-indole indirubine, lH-pyrrolo[3,2B, 3,2-C, and 3,2-C]pyridine-2- carboxamides, D4476, SB-202190, Peifer-17, SR- 1272 - SRI 279, SR-2797, SR-2805, Sehciclib (roscovitine), CYC202, SR-2890, (R)-DRF053, Bischof-5, Bischof-6, Yang-2, PF670462, PF670, PF4800567, PF480, BTX-A51, pyrido[3,4-g]quinazoline and halogenated (instead of sulfur) analogs, 1 ,4-Diaminoanthra-quinone, (-)-matairenisol, Lamellarin 3, MRT00033659, TG0003, Salado-34, Umbralisib, and TGR-1202. See also Table 2. Atorney Docket No.: 761131.152320 Atorney Docket No.: 761131.152320 Atorney Docket No.: 761131.152320 Atorney Docket No.: 761131.152320 Atorney Docket No.: 761131.152320 Atorney Docket No. : 761131.152320

[0082]

[0068] Small molecule inhibitors that bind to MAPK11 or CK1 can also induce protein degradation in addition to inhibiting kinase activity. This is particularly the case for inhibitors that bind covalently to MAPK11 or CK1. (See, e.g., Wang et al., Signal Transduction and Targeted Therapy, 6:423, 2021.)

[0083] Protein Binder Inhibitors

[0084]

[0069] The inhibitor of MAPK11 or CK1 can be a protein binder that binds to MAPK11 or CK1. A protein binder is a molecule, typically including one or more polypeptides, that contains a binding moiety (e.g. binding domain) that has binding affinity and preferably specificity for MAPK1 1 or CK1. Suitable binding moieties are well-known to persons of ordinary skill in the art and include, for example, antibodies and antigen-binding fragments of antibodies, the antigen and epitope of a preselected antibody or antigen-binding fragment thereof, receptors and ligandbinding fragments of receptors and their cognate ligands, non-immunoglobulin scaffolds, and the like. When a protein binder contains two or more polypeptides, each polypeptide can be covalently or non-covalently bonded to another polypeptide in the binder.

[0085]

[0070] Protein binders can include an antibody or antigen-binding fragment of an antibody, such as, a Fab, a F(ab’)2, a Fab’, an Fd, an Fv, a single chain Fv (scFv), or a single variable domain (e.g., dAb, a nanobody, a VHH, and a VNAR). The antibody can be any antibody that has the desired binding affinity and specificity, such as an IgG (e.g., human, humanized, mouse, primate) or a heavy chain antibody including a camelid HCab or an IgNAR. In some embodiments, the preferred binding moiety is an scFV or a single domain antibody (e.g., dAb, a nanobody, a VHH, and a VNAR).

[0086]

[0071] Protein binders can be a non-immunoglobulin scaffold; many suitable non- immunoglobulin scaffolds are well-known to a person of ordinary skill in the art. See, e.g., Vazques-Lombardi et al. Drug Discovery Today 20(10): 1271 (2015) and Luo et al. RSC Chem. Biol. 2022, 3, 830. For example, the binding moiety can be an affibody, an adnectin, (monobody), an anticalin, a DARPin, a knottin, a kunitz, a affimer, a nanofitin, a avimer, a centryin, a affilin, or an adapt. Atorney Docket No. : 761131.152320

[0087]

[0072] Protein binders can bind to MAPK11 or CK1 and inhibit MAPK11 or CK1 activity, for example, by blocking that catalytic site (e.g., and inhibiting ATP or substrate binding) or through other mechanism such as allosteric inhibition.

[0088] MAPK1 1 or CK1 degraders

[0089]

[0073] The inhibitor can target MAPK11 or CK1 for degradation thereby reducing kinase activity. Inhibitors that bind to and promote degradation of MAPK11 or CK1 can reduce the levels of these proteins in cells and thus inhibit or eliminate MAPK11 or CK1 activity. Typically, such inhibitors target MAPK11 of CK1 for degradation through the ubiquitin- proteosome system of the endosome-lysosome and autophagy-lysosome systems. Such inhibitors can be small molecules, peptidic or proteinaceous compounds or can include a peptidic or proteinaceous moiety and a small molecule moiety. For example, in an embodiment the small molecule degrader of CK1 is lenalidomide, which induces degradation of CKla through the ubiquitin proteosome system. (Petzold et al. Nature 532,127-130 (2016).

[0090]

[0074] Proteolysis targeting chimeras (PROTACs) are well-known to a person of ordinary skill in the art and can target MAPK11 or CK1 for ubiquitin-dependent degradation, (e.g. Wang et al., Signal Transduction and Targeted Therapy, 6:423, 2021 and Zhao et al., Signal Transduction and Targeted Therapy, 7: 113, 2022). PROTACs comprise an E3-recruiting ligand (e.g., IkBa phosphopeptide, MDM2 ligands such as nutlin, and the like), a MAPK11 or CK1 targeting molecule (e.g., such as a small molecule inhibitor that binds MAPK11 or CK1) and a linker connecting the two. Id., see also Smith et al. Bioorg Med Chem Lett 2008 18(22): 5904-5908. In addition to PROTAC, molecular glues, Lysosome-Targeting Chimaera (LYTAC), and Antibodybased PROTAC (AbTAC) are well-known in the art and can be used to degrade MAPK11 or CK1, thereby inhibiting kinase activity.

[0091]

[0075] Targeted protein degradation technologies for use in inhibiting kinase activity of MAPK1 1 or CK1 can include ubiquitin-proteasome systems (UPS) such as PROTAC, molecular glue, double-mechanism degrader, and PROTAC-based technologies (e.g. SARD, HyT, TF- PROTAC, dual-PROTAC, SERD (Zhao et al., Signal Transduction and Targeted Therapy, 7:113, 2022).

[0092]

[0076] Targeted protein degradation technologies for use in inhibiting kinase activity of MAPK1 1 or CK1 can also include endosome-lysosome systems and autophagy-lysosome Atorney Docket No. : 761131.152320 systems (Zhao et al., Signal Transduction and Targeted Therapy, 7:113, 2022). Examples of endosome-lysosome systems include LYTAC, bispecific aptamer chimera, AbTAC, and GlueTac. Examples of autophagy-lysosome systems include AUTAC, ATTEC, AUTOTAC, and CMA-based degrader. Both systems are well-known to a person of ordinary skill in the art (e.g. Wang et al., Signal Transduction and Targeted Therapy, 6:423, 2021 and Zhao et al., Signal Transduction and Targeted Therapy, 7: 113, 2022).

[0093] Inhibitors that reduce or prevent expression MAPK11 or CK1

[0094]

[0077] The methods of this disclosure comprise a compound that reduces or prevents expression of MAPK11 or CK1. Methods well-known to persons of ordinary skill in the art comprise altering, silencing, attenuating, or knocking out the MAPK11 or CK1 gene and can be used to modulate the expression profile of MAPK11 or CK1. As used herein, the term “knock-out” generally refers to a gene whose level of expression or activity has been reduced to zero. In some instances, a gene can be knocked-out via deletion of some or all of its coding sequence. In other instances, a gene can be knocked-out via introduction of one or more nucleotides into its open reading frame, which results in translation of a non-sense or otherwise non-functional protein product. For example, the MAPK11 or CK1 gene can be readily altered, silenced, attenuated, or knocked-out using known methods and reagents, including those described herein.

[0095]

[0078] A nucleic acid editor (e.g. gene editor, RNA editor) can alter the MAPK11 or CK1 gene or mRNA to reduce or prevent its expression. Suitable nucleic acid editors are well-known in the field and include, for example, DNA editing use transcription activator-like effector nucleases (TALENs), zinc-finger nucleases (ZFNs) and retrotransponson based DNA and RNA gene writers (e.g., W02020 / 047124). Certain preferred editors include DNA editors such as CRISPER-CAS9 (e.g. Ran et al. Nature Protocols 8, 2281-2308 (2013)), prime editing (e.g., Anzalone et al., Nature, 576, 149-157 (2019)), FiCAT editors (e.g., Pallares-Masmitja et al. Nature Communications 12(7071 (2021)), and RNA editors such as ADARs (e.g., Both et al. Mol Ther.31(6): 1533 (2023)). These preferred editors rely on guide RNA (gRNA) to target the editor. Exemplary guide RNAs for MAPK11 or CKla (CSNK1 Al), CK18 (CSNK1D), CK I e (CSNK1E1), CKlyl(CSNKlGl), CKly2 (CSNK1G2), CKly3 (CSNK1G3), comprise the sequences presented in Tables 3A - 3G. Atorney Docket No. : 761131.152320

[0096]

[0079] In embodiments, the nucleic acid editor is a DNA editor (e.g., CRISPER-CAS9, prime editor, FiCat editor) and comprises a MAPK11 gRNA that comprise a sequence selected from those in Table 3A.

[0097]

[0080] In embodiments, the nucleic acid editor is a DNA editor (e.g., CRISPER-CAS9, prime editor, FiCat editor) and comprises a CKla (CSNK1A1) gRNA that comprise a sequence selected from those in Table 3B.

[0098]

[0081] In embodiments, the nucleic acid editor is a DNA editor (e.g., CRISPER-CAS9, prime editor, FiCat editor) and comprises a CK18 (CSNK1D) gRNA that comprise a sequence selected from those in Table 3C.

[0099]

[0082] In embodiments, the nucleic acid editor is a DNA editor (e.g., CRISPER-CAS9, prime editor, FiCat editor) and comprises a CK I e (CSNK1E1) gRNA that comprise a sequence selected from those in Table 3D.

[0100]

[0083] In embodiments, the nucleic acid editor is a DNA editor (e.g., CRISPER-CAS9, prime editor, FiCat editor) and comprises a CKlyl(CSNKlGl) gRNA that comprise a sequence selected from those in Table 3E.

[0101]

[0084] In embodiments, the nucleic acid editor is a DNA editor (e.g., CRISPER-CAS9, prime editor, FiCat editor) and comprises a CKly2 (CSNK1G2) gRNA that comprise a sequence selected from those in Table 3F.

[0102]

[0085] In embodiments, the nucleic acid editor is a DNA editor (e.g., CRISPER-CAS9, prime editor, FiCat editor) and comprises a CKly3 (CSNK1G3) gRNA that comprise a sequence selected from those in Table 3G.

[0103]

[0086] Other inhibitors that reduce or prevent transcription and / or translation of MAPK11 or CKI can be used, such as silencing RNA (siRNA), short hairpin RNA (shRNA), antisense oligonucleotide (ASO), micro RNA (miRNA) and the like, all of which are all well known in the art.

[0104]

[0087] Exemplary siRNAs for MAPK11 or CKla (CSNK1 Al), CK18 (CSNK1D), CKlc (CSNK1E1), CKlyl(CSNKlGl), CKly2 (CSNK1G2), CKly3 (CSNK1G3), comprise an RNA strand with a sequence presented in Tables 4A - 4G. The siRNA preferable also contains a complementary RNA strand, with our without terminal overhangs. Atorney Docket No. : 761131.152320

[0105]

[0088] In embodiments, the siRNA targets MAPK11 and comprise an RNA strand with sequence selected from those in Table 4A. Preferable the siRNA also contains a complementary RNA strand, with or without terminal overhangs.

[0106]

[0089] In embodiments, the siRNA targets CKla (CSNK1A1) and comprise an RNA strand with sequence selected from those in Table 4B. Preferable the siRNA also contains a complementary RNA strand, with or without terminal overhangs.

[0107]

[0090] In embodiments, the siRNA targets CK18 (CSNK1D) and comprise an RNA strand with sequence selected from those in Table 4C. Preferable the siRNA also contains a complementary RNA strand, with or without terminal overhangs.

[0108]

[0091] In embodiments, the siRNA targets a CK1 e (CSNK1E1) and comprise an RNA strand with sequence selected from those in Table 4D. Preferable the siRNA also contains a complementary RNA strand, with or without terminal overhangs.

[0109]

[0092] In embodiments, the siRNA targets a CKlyl (CSNK1G1) and comprise an RNA strand with sequence selected from those in Table 4E. Preferable the siRNA also contains a complementary RNA strand, with or without terminal overhangs.

[0110]

[0093] In embodiments, the siRNA targets a CKly2 (CSNK1G2) and comprise an RNA strand with sequence selected from those in Table 4F. Preferable the siRNA also contains a complementary RNA strand, with or without terminal overhangs.

[0111]

[0094] In embodiments, the siRNA targets a CKly3 (CSNK1G3) and comprise an RNA strand with sequence selected from those in Table 4G. Preferable the siRNA also contains a complementary RNA strand, with or without terminal overhangs.

[0112]

[0095] Exemplary shRNAs for MAPK11 or CKla (CSNK1A1), CK18 (CSNK1D), CKlc (CSNK1E1), CKlyl(CSNKlGl), CKly2 (CSNK1G2), CKly3 (CSNK1G3), are presented in Tables 5A - 5G. The exemplary shRNAs include RNAi sequences in Tables 3A-3G (designated as “sense” in Tables 5A-5G) that are paired in a short hairpin with antisense sequences (designed “antisense”) in Tables 5A-5G). The exemplary shRNAs disclosed herein are based on the miR- 155 backbone, which allows for the expression of the shRNAs via a polymerase II system, enabling the use of cell-type-specific promoters for cell-type-specific shRNA expression (e.g., specific expression in cone and / or rod photoreceptors) and gene knockdown. As is understood by persons of skill in the art the shRNA is typically expressed from a suitable DNA that is transfected or transduced into a target cell. Atorney Docket No. : 761131.152320

[0113]

[0096] In embodiments, the shRNA targets MAPK11 and comprise a sequence and antisense sequence pair selected from those in Table 5A.

[0114]

[0097] In embodiments, the shRNA targets CKla (CSNK1A1) and comprise a sequence and antisense sequence pair selected from those in Table 5B.

[0115]

[0098] In embodiments, the shRNA targets CK18 (CSNK1D) and comprise a sequence and antisense sequence pair selected from those in Table 5C.

[0116]

[0099] In embodiments, the shRNA targets a CK1 e (CSNK1E1) and comprise a sequence and antisense sequence pair selected from those in Table 5D.

[0117]

[0100] In embodiments, the shRNA targets a CKlyl(CSNKlGl) and comprise a sequence and antisense sequence pair selected from those in Table 5E.

[0118]

[0101] In embodiments, the shRNA targets a CKly2 (CSNK1G2) and comprise a sequence and antisense sequence pair selected from those in Table 5F.

[0119]

[0102] In embodiments, the shRNA targets a CKly3 (CSNK1G3) and comprise a sequence and antisense sequence pair selected from those in Table 5G.

[0120]

[0103] Exemplary ASOs for MAPK11 or CKla (CSNK1A1), CK18 (CSNK1D), CKlc (CSNK1E1), CKlyl(CSNKlGl), CKly2 (CSNK1G2), CKly3 (CSNK1G3), comprise a sequence presented in Tables 6A - 6G.

[0121]

[0104] In embodiments, the ASO targets MAPK11 and comprise a sequence selected from those in Table 6A.

[0122]

[0105] In embodiments, the ASO targets CKla (CSNK1A1) and comprise a sequence selected from those in Table 6B.

[0123]

[0106] In embodiments, the ASO targets CK18 (CSNK1D) and comprise a sequence selected from those in Table 6C.

[0124]

[0107] In embodiments, the ASO targets a CKlc (CSNK1E1) and comprise a sequence selected from those in Table 6D.

[0125]

[0108] In embodiments, the ASO targets a CKlyl(CSNKlGl) and comprise a sequence selected from those in Table 6E.

[0126]

[0109] In embodiments, the ASO targets a CKly2 (CSNK1G2) and comprise a sequence selected from those in Table 6F.

[0127] [HO] In embodiments, the ASO targets a CKly3 (CSNK1G3) and comprise a sequence selected from those in Table 6G. Atorney Docket No. : 761131.152320

[0128] [Ill] Any of the sequences disclosed in Tables 3A-3G, 4A-4G, 5A-5G or 6A-6G can, if desired, include one or more modifications. For example, one or more nucleotides can differ from the sequences presented in Tables 3A-3G, 4A-4G, 5A-5G or 6A-6G, but preferably the sequence will be at least about 80%, 85%, 90% or 95% identical to a sequence in Tables 3A-3G, 4A-4G, 5A-5G or 6A-6G. The modification can be replacement of a nucleotide with a modified nucleotide that contains a modified nucleobase (e.g., mlA, mlG, m2G, M7G, m5C, m5U, s4U, pseudouracil, and the like) modified sugar (e.g., 4’ -thionucleotides, 4’ selenonucleotides, 2’deoxy-4’thionucleotides, and the like), modified phosphate linkages (e.g., phosphorothioate, thiophosphate, amide, and the like) or any combination thereof. Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320

[0129] 31 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320

[0130] 13 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Atorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320

[0131] Ill Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Atorney Docket No. : 761131.152320

[0132] Nucleic Acids And Vectors

[0133]

[0112] The disclosure additionally relates to nucleic acids and vectors that comprise a nucleic acid that encodes an inhibitor of MAPK11 or CK1 or a portion thereof, such as nucleic acid editor or portion thereof, gRNA, miRNA, shRNA, siRNA, ASO, peptidic or proteinaceous inhibitor (e.g., nanobody)). The nucleic acid can be DNA, RNA (e.g, mRNA) and can include one or more modified nucleotides if desired, such as nucleotides with modified nucleobases. The nucleic acid can be included in a vector. When the vector is for expression of the nucleic acid encoding an MAPK11 or CK1 inhibitor (e.g., nucleic acid editor, siRNA, shRNA, ASO) the nucleic acid encoding the inhibitor is operably linked to one or more regulatory or expression control elements. Such elements are well-known in the art and include, for example, promoters, enhancers, sequences encoding signal peptides, polyA sequences, and the like.

[0134]

[0113] The vector can be viral or non- viral, and many such vectors are well-known in the field. Viral and non-viral vectors and methods of their delivery are known to those of skill in the art, such as adenovirus vectors, AAV vectors, retrovirus vectors, lentiviral vectors, herpes virus vectors, and the like. For example the viral vector can be derived from Moloney murine leukemia virus vectors (MoMLV), MSCV, SFFV, MPSV or SNV, lentiviral vectors (e.g. derived Atorney Docket No. : 761131.152320 from human immunodeficiency virus (HIV), simian immunodeficiency virus (SIV), feline immunodeficiency virus (FIV), bovine immunodeficiency virus (BIV) or equine infectious anemia virus (EIAV)), adenoviral (Ad) vectors, AAV vectors, simian virus 40 (SV-40) vectors, bovine papilloma virus vectors, Epstein-Barr virus, herpes virus vectors, vaccinia virus vectors, Harvey murine sarcoma virus vectors, murine mammary tumor virus vectors, and Rous sarcoma virus vectors. Numerous suitable vectors are commercially available. Such vectors typically include polyadenylation signals, etc. in conjunction with multiple cloning sites, as well as additional elements such as origins of replication, selectable marker genes (e. g., LEU2, URA3, TRP 1, HIS3, GFP), centromeric sequences, etc.

[0135]

[0114] The vector may be in any form, including, but not limited to, plasmids and viral particles, such as rAAV particles that include a nucleic acid encoding an inhibitor of MAPK11 or CK1 or portion thereof (e.g., a nucleic acid editor, gRNA, miRNA, siRNA, shRNA, ASO) as described herein. If desired, the nucleic acids encoding an inhibitor of MAPK11 or CK1 as described herein can be combined with other suitable nucleic acid delivery agents, for example, complexed with lipids, encapsulated within liposomes, for delivery.

[0136]

[0115] The nucleic acid encoding an inhibitor of MAPK11 or CK1 disclosed herein may be packaged into a virus capsid to generate a viral particle, such as an AAV particle. The virus capsid may be any functional AAV capsid. In one embodiment, the capsid is provided by a single AAV source. Alternatively, the AAV capsid may be derived from more than one source. Any serotype of AAV known in the art, e.g, serotypes AAV1, AAV2, AAV3A, AAV3B, AAV4, AAV5, AAV6, AAV7, AAV8, AAV9, AAV10, AAV11, AAV12, rhlO, modified AAV, AAVPhP.B, or yet to be discovered, or a recombinant AAV based thereon, may be used as a source for the AAV capsid.

[0137]

[0116] When the vector is an AAV vector, for example, the vector can be based on an AAV viral genome with the capsid and other structural proteins removed. The vector provided herein can be suitable for gene therapy and comprise regulatory elements suitable for expression in desired cells (e.g, cone and / or rod photoreceptors) at desired levels, such as a suitable promoter, signal peptide and polyA signal. Each of the nucleotide sequences are operable linked. In addition, the vector may comprise additional elements for the expression of the nucleic acid. For instance, the vector may comprise one or more ITRs, a ribosome binding element, a terminator, an enhancer, a selection marker, an intron, a polyA signal, and / or an origin of replication. Atorney Docket No. : 761131.152320

[0138]

[0117] The nucleic acids (including vectors) described herein, or any component thereof, can be optimized (e.g., codon optimized) by sequence variation using well-known methods, for example, to achieve desired levels of expression, to reduce immunogenicity, or for other purposes. Suitable methods for optimizing nucleic acid construct by sequence alternation, including to increase expression, packaging and / or to decrease immunogenicity, for example, are well-known in the art and such modifications of the nucleic acids disclosed herein are considered to be variants of the particular nucleic acids. For example, the nucleic acids described herein, or any component thereof, can be codon optimized, CpG- depleted (See, e.g., U.S. Patent 11,015,210; Y. A. Medvedeva, et al, Bioinformatics-Trends and Methodologies, 449-472

[0139] (2011))40, modified to remove repeat and hairpin sequences, modified to eliminate alternative reading frames, modified to remove unwanted splice donor and acceptor sites, modified to add stuffer sequence, modified to include a miRNA, siRNA, shRNA, dsRNA, or gRNA sequence (See, e.g., Domenger and Grimm, Human Molecular Genetics, 2019, 28:R1-R12), modified to include an inducible control system (e.g. Tet on / off system) (See, e.g., Gossen et al, Science, 268: 1766-1769 (1995); Harvey et al, Curr. Opin. Chem. BioL, 2:512-518 (1998)) or modified to include an ITR deleted of the terminal resolution site (trs) sequence to generate a scAAV (See, e.g., McCarty et al., Gene Therapy, 2001, 16: 1248-54). Methods for optimizing the nucleic acids disclosed herein are conventional and well-known to those of ordinary skill in the art.

[0140]

[0118] Many different vectors are known in the art. The vector components generally include one or more of the following: a signal sequence, an origin of replication, one or more marker genes, an enhancer element, a promoter, and a transcription termination sequence, for example as described in U.S. Pat. No. 5,534,615.

[0141]

[0119] Typically, the regulatory elements, e.g, promoter, signal peptide, enhance, polyA and the link, are selected to be functional in desired host cells. Illustrative examples of suitable host cells are provided below. These host cells are not meant to be limiting, and any suitable host cell may be used to replicate or propagate nucleic acids and vectors or produce peptidic or proteinaceous inhibitors provided herein. Suitable host cells include any prokaryotic (e.g, bacterial), lower eukaryotic (e.g, yeast), or higher eukaryotic (e.g., mammalian) cells. Suitable prokaryotes include eubacteria, such as Gram-negative or Gram-positive organisms, for example, Enterobacteriaceae such as Escherichia (E. coli), Enterobacter, Erwinia, Klebsiella, Proteus, Salmonella (5. typhimurium), Serratia (5. marcescans), Shigella, Bacilli (B. subtilis and B. Atorney Docket No. : 761131.152320 licheniformis), Pseudomonas ( . aeruginosa), and Streptomyces. One useful E. coli cloning host is E. coli 294, although other strains such as E. coli B, E. coli XI 776, and E. coli W3110 are also suitable.

[0142]

[0120] In addition to prokaryotes, eukaryotic microbes such as filamentous fungi or yeast are also suitable cloning or expression hosts for binder-encoding vectors. Saccharomyces cerevisiae, or common baker's yeast, is a commonly used lower eukaryotic host microorganism. However, a number of other genera, species, and strains are available and useful, such as Schizosaccharomyces pombe, Kluyveromyces (K lactis, K. fragilis, K. bulgaricus, K. wickeramii, K. waltii, K. drosophilarum, K. thermotolerans, and K. marxianus), Yarrowia, Pichia pastoris, Candida (C. albicans), Trichoderma reesia, Neurospora crassa, Schwanniomyces (5. occidentalis), and filamentous fungi such as, for example Penicillium, Tolypocladium, and Aspergillus (A. nidulans and A. niger).

[0143]

[0121] Useful mammalian host cells include COS-7 cells, HEK293 cells; baby hamster kidney (BHK) cells; Chinese hamster ovary (CHO); mouse sertoli cells; African green monkey kidney cells (VERO-76), and the like. The host cells may be cultured in a variety of media.

[0144] Commercially available media such as, for example, Ham's F10, Minimal Essential Medium (MEM), RPMI-1640, and Dulbecco's Modified Eagle's Medium (DMEM) are suitable for culturing the host cells. In addition, any of the media described in Ham et al., Meth. Enz., 1979, 58:44; Barnes et al., Anal. Biochem., 1980, 102:255; and U.S. Pat. Nos. 4,767,704, 4,657,866, 4,927,762, 4,560,655, and 5,122,469; or WO 90 / 03430 and WO 87 / 00195 may be used45 46Each of the foregoing references is incorporated by reference in its entirety.

[0145]

[0122] Any of these media may be supplemented as necessary with hormones and / or other growth factors (such as insulin, transferrin, or epidermal growth factor), salts (such as sodium chloride, calcium, magnesium, and phosphate), buffers (such as HEPES), nucleotides (such as adenosine and thymidine), antibiotics, trace elements (defined as inorganic compounds usually present at final concentrations in the micromolar range), and glucose or an equivalent energy source. Any other necessary supplements may also be included at appropriate concentrations that would be known to those skilled in the art.

[0146]

[0123] The culture conditions, such as temperature, pH, and the like, suitable for use with the host cell selected for expression and / or replication and will be apparent to the ordinarily skilled artisan. When using recombinant techniques, the peptidic or proteinaceous inhibitor can be Atorney Docket No. : 761131.152320 produced intracellularly, in the periplasmic space, or directly secreted into the medium. If the inhibitors are produced intracellularly, as a first step, the particulate debris, either host cells or lysed fragments, is removed, for example, by centrifugation or ultrafiltration. For example, Carter et al Bio / Technology, 1992, 10: 163-167, incorporated by reference in its entirety describes a procedure for isolating modified ABs which are secreted to the periplasmic space of E. coli^ . Briefly, cell paste is thawed in the presence of sodium acetate (pH 3.5), EDTA, and phenylmethylsulfonylfluoride (PMSF) over about 30 min. Cell debris can be removed by centrifugation.

[0147]

[0124] In some embodiments, the inhibitor can be produced in a cell-free system. The cell-free system can be, for example, solid phase nucleic acid synthesis, solution phase nucleic acid synthesis, in vitro transcription and translation system as described in Yin et al., (2012), mAbs, 4:217-225. In some embodiments, the cell-free system utilizes a cell-free extract from a eukaryotic cell or from a prokaryotic cell (such as, E. coH).

[0148]

[0125] Where the inhibitor of MAPK11 or CK1 is secreted into the medium, supernatants from such expression systems are generally first concentrated using a commercially available protein concentration filter, for example, an Amico® or Millipore® Pellcon® ultrafiltration unit. A protease inhibitor such as PMSF may be included in any of the foregoing steps to inhibit proteolysis and antibiotics may be included to prevent the growth of adventitious contaminants.

[0149]

[0126] The inhibitor of MAPK11 or CK1 prepared from the cells can be purified using, for example, hydroxylapatite chromatography, gel electrophoresis, dialysis, and affinity chromatography, with affinity chromatography being a particularly useful purification technique. The suitability of protein A as an affinity ligand depends on the species and isotype of any immunoglobulin Fc domain that is present in the binder. Protein A can be used to purify modified ABs that comprise human yl, y2, or y4 heavy chains (Lindmark et al., J. Immunol.

[0150] Meth., 1983, 62:1-13). Protein G is useful for all mouse isotypes and for human y3 (Guss et al., (1986), EMBO J., 5:1567-1575).

[0151]

[0127] The matrix to which the affinity ligand is attached is most often agarose, but other matrices are available. Mechanically stable matrices such as controlled pore glass or poly(styrenedivinyl)benzene allow for faster flow rates and shorter processing times than can be achieved with agarose. Where the bispecific binder comprises a CH3 domain, the BakerBond ABX® resin is useful for purification. Atorney Docket No. : 761131.152320

[0152]

[0128] Other techniques for protein purification, such as fractionation on an ion-exchange column, ethanol precipitation, Reverse Phase HPLC, chromatography on silica, chromatography on heparin Sepharose®, chromatofocusing, SDS-PAGE, and ammonium sulfate precipitation are also available, and can be applied by one of skill in the art.

[0153]

[0129] Following any preliminary purification step(s), the mixture comprising the binder and contaminants may be subjected to low pH hydrophobic interaction chromatography using an elution buffer at a pH between about 2.5 to about 4.5, generally performed at low salt concentrations (e.g., from about 0 to about 0.25 M salt).

[0154]

[0130] The present disclosure also relates to a viral particle comprising a nucleic acid as described herein.

[0155]

[0131] The viral particle can be an AAV particle, lentiviral particle or other viral particles. The viral particle can be capable of transducing at least about 10% of human photoreceptor (e.g., cone cells, rod cells) cells. For instance, the viral particle can be capable of transducing at least about 10%, at least about 15%, at least about 20%, at least about 25%, at least about 30%, at least about 35%, at least about 40%, at least about 45%, at least about 50%, at least about 55% at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 94%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, at least about 99%, at least about 100% of the primary human cone cells.

[0156]

[0132] The present disclosure further relates to a host cell comprising a nucleic acid or a viral particle as described herein. Also provided herein are production methods and cultures for the production of virus particles. The culture can comprise suitable host cells, including, for example, human-derived cell lines such as HeLa, A549, or HEK293 cells, suitable helper virus function, provided by wild-type or mutant adenovirus, e.g. temperature sensitive adenovirus, Herpes virus, or a plasmid construct providing helper functions; AAV rep and cap genes and gene products, the nucleic acid disclosed herein or a vector comprising the nucleic acid, and suitable media and media components to support viral particle production that are well-known in the art.

[0157]

[0133] The disclosure additionally relates to an AAV vector, comprising a nucleic acid as described herein and an AAV capsid. In the AAV vector, the AAV capsid can be an AAV5 capsid, a PHP.eB capsid, an NHP26 capsid, an AAV8 capsid, an AAV8-BP2 capsid, an AAV9 Atorney Docket No. : 761131.152320 capsid, or a PHP.B capsid; preferably an AAV5 capsid, a PHP.eB capsid, or an NHP26 capsid; more preferably an AAV5 capsid. The promoter of the AAV vector can be a cone specific promoter (e.g., PR0A7), a rod specific promoter (e.g., PROA330) or a promoter active in both cones and rods.

[0158]

[0134] Many suitable AAV capsids and viral backbones are well-known in the art and multiple AAV capsid serotypes are known and may be suitable for a MAPK11 or CKlinihbitor construct. At least sixteen serotypes of AAV have been described in literature, and are referred to as AAV1, AAV2, AAV3, AAV4, AAV5, AAV6, AAV7, AAV8, AAV9, AAV10, AAV11, AAV 12, AAV13, AAV 14, AAV15, and AAV16. Many engineered and variant capsids are also well- known in the art.

[0159]

[0135] Exemplary AAV capsids suitable for the constructs disclosed herein include, but are not limited to, AAV8-BP2, AAV-PHP.B, AAV-PHP.eB, AAV5, or AAV-NHP26. Preferred AAV capsid proteins are AAV-PHP.eB, AAV8-BP2, or AAV5.

[0160]

[0136] Alternatively to using AAV natural serotypes, artificial AAV serotypes may be used, such as, AAV with a non-naturally occurring capsids. Such an artificial capsid may be generated by any suitable technique, using a selected AAV sequence (e.g., a fragment of a VP1 capsid protein) in combination with heterologous sequences which may be obtained from a different selected AAV serotype, non-contiguous portions of the same AAV serotype, from a non- AAV viral source, or from a non-viral source. An artificial AAV serotype may be, without limitation, a chimeric AAV capsid or a mutated AAV capsid. A chimeric capsid comprises VP capsid proteins derived from at least two different AAV serotypes or comprises at least one chimeric VP protein combining VP protein regions or domains derived from at least two AAV serotypes.

[0161]

[0137] AAV capsid proteins may also be mutated, in particular to enhance transduction efficiency. Mutated AAV capsids may be obtained from capsid modifications inserted by error prone PCR and / or peptide insertion or by including one or several amino acids substitutions. In particular, mutations may be made in any one or more of tyrosine residues of natural or nonnatural capsid proteins (e.g. VP1, VP2, or VP3). Mutated residues may be surface exposed tyrosine residues. Exemplary mutations include, but are not limited to tyrosine-to-phenylalanine substitutions such as Y252F, Y272F, Y444F, Y500F, Y700F, Y704F, Y730F, Y275F, Y281F, Y508F, Y576F, Y612G, Y673F and Y720F. Atorney Docket No. : 761131.152320

[0162] Therapeutic Uses And Applications

[0163]

[0138] This disclosure also relates to methods for inhibiting death or degeneration of photoreceptor cells (e.g., cone photoreceptors and / or rod photoreceptors) and treating a photoreceptor disease. The methods comprise administering to a subject in need thereof a therapeutically effective amount of an inhibitor of MAPK11, an inhibitor of CK1 or a combination thereof. The methods can help preserve photoreceptor viability in subjects, for example who have experiences ocular trauma, ocular ischemia (e.g., ocular ischemic syndrome), or drug-induced or light-induced photoreceptor death or degeneration. The methods can also be used to treat photoreceptor diseases such as cone-rod dystrophy, rod-cone dystrophy, macular degeneration, geographic atrophy, age-related macular degeneration (AMD), wet- AMD, retinitis pigmentosa, macular dystrophy, Stargardt disease, juvenile macular degeneration, achromatopsia, diabetic retinopathy, Usher syndrome, Leber congenital amaurosis (LCA), X- linked juvenile retinoschisis, and central areolar choroidal dystrophy.

[0164]

[0139] The subject to be treated can be a human, or other mammal (e.g., dog, cat, horse, and the like) or any other animal.

[0165]

[0140] The inhibitor of MAPK11 or CK1 can be administered to the subject by any suitable route, including but not limited to, intraocular (e.g., subretinal injection, intravitreal injection, suprachoroideal injection), oral, intradermal, intrathecal, intratumoral, intramuscular, intraperitoneal, intravenous, topical, subcutaneous, percutaneous, intranasal and inhalation routes, and via scarification (scratching through the top layers of skin, e.g., using a bifurcated needle). The preferred administration route is by ocular administration, such as intraocular administration, topical ocular application.

[0166]

[0141] The methods disclosed herein can further comprise administering at least one additional therapeutic agent to the subject. In particular, said therapeutic agent may be a corticosteroid, an antibiotic, an analgesic, an immunosuppressant, a trophic factor, or any combinations thereof.

[0167] Pharmaceutical Compositions

[0168]

[0142] The disclosure also relates to pharmaceutical compositions that comprise an inhibitor of MAPK1 1 or CK1 as disclosed herein, including nucleic acids, vectors and viral particles that encode such inhibitors. The pharmaceutical composition may comprise a pharmaceutically acceptable excipient. The term "pharmaceutically acceptable carrier" includes, but is not limited Atorney Docket No. : 761131.152320 to, any carrier that does not interfere with the effectiveness of the biological activity of the ingredients and that is not toxic to the subject to whom it is administered. Examples of suitable pharmaceutical carriers are well known in the art and include phosphate buffered saline solutions, water, emulsions, such as oil / water emulsions, various types of wetting agents, sterile solutions etc. Such carriers can be formulated by conventional methods and can be administered to the subject at a suitable dose. Preferably, the compositions are sterile. These compositions may also contain adjuvants such as preservative, emulsifying agents and dispersing agents. Prevention of the action of microorganisms may be ensured by the inclusion of various antibacterial and antifungal agents. Suitable carriers and their formulations are described in Remington: The Science and Practice of Pharmacy, 21st Edition, David B. Troy, ed., Lippincott Williams & Wilkins (2005).

[0169]

[0143] Typically, an appropriate amount of a pharmaceutically-acceptable salt is used in the formulation to render the formulation isotonic, although the formulate can be hypertonic or hypotonic if desired. Examples of the pharmaceutically-acceptable carriers include, but are not limited to, sterile water, saline, buffered solutions like Ringer's solution, and dextrose solution. The pH of the solution is generally about 5 to about 8 or from about 7 to 7.5. Other carriers include sustained release preparations such as semipermeable matrices of solid hydrophobic polymers containing the immunogenic polypeptides. Matrices are in the form of shaped articles, e.g., films, liposomes, or microparticles. Certain carriers may be more preferable depending upon, for instance, the route of administration and concentration of composition being administered. Carriers are those suitable for direct delivery to the eye which may be administered without undue toxicity. Pharmaceutically acceptable excipients include, but are not limited to, sorbitol, any of the various tween compounds, and liquids such as water, saline, glycerol and ethanol. Pharmaceutically acceptable salts can be included therein, for example, mineral acid salts such as hydrochlorides, hydrobromides, phosphates, sulfates, and the like; and the salts of organic acids such as acetates, propionates, malonates, benzoates, and the like. Most preferably, the composition is combined with saline, Ringer's balanced salt solution (pH 7.4), and the like.

[0170]

[0144] The pharmaceutical composition may optionally comprise one or more agents that facilitate delivery of the inhibitor of MAPK11 or CK1 including nucleic acids and vectors disclosed herein to a target cell (e.g., cone photoreceptors, rod photoreceptors), including but not limited to, transfection reagents or components thereof, such as lipids or polymers. Atorney Docket No. : 761131.152320

[0171]

[0145] The pharmaceutical composition disclosed herein can be formulated for administration to the eye, for example by intraocular injection (e.g., by subretinal, intravitreal, intracameral, juxtascleral, subconjunctival, retrobulbular and / or suprachoroideal), or by topical application. For intravitreal delivery, the pharmaceutical composition disclosed herein can be injected directly into the vitreous. For subretinal delivery, the pharmaceutical composition disclosed herein can be delivered in a localized subretinal bleb between the retinal pigment epithelium (RPE) and the photoreceptor layer in a surgical procedure. This can be accomplished during pars plana vitrectomy (ppV). Subretinal administration can provide the direct access to photoreceptors and the RPE. Suprachoroideal injection can provide access to the photoreceptors from the choroideal layer. Alternatively, the pharmaceutical composition can be delivered into the anterior section of the eye, in particular into the anterior chamber. Subretinal injection is the preferred administration mode. The pharmaceutical composition can also be formulated for systemic administration (e.g., oral, parenteral and the like).

[0172]

[0146] The amount of pharmaceutical composition to be administered may be determined by a clinician of ordinary skill based on the patient’s age, size, and weight, and type and severity of the disease being treated, the overall health of the patient and sensitivity to drugs, and other factors.

[0173]

[0147] The pharmaceutical composition may be formulated for administration by injection, e. g., by subretinal or intravitreal injection or suprachoroideal injection. Formulations for injection may be presented in unit dosage form, e. g., in ampoules or in multi-dose containers. The compositions may take such forms as suspensions, solutions or emulsions in oily or aqueous vehicles, and may contain formulatory agents such as suspending, stabilizing and / or dispersing agents. Alternatively, the active ingredient may be in powder form for constitution with a suitable vehicle, e. g., sterile pyrogen- free water, before use. The dosage form for administration to the eye can be liquid (e.g., solution, suspension or emulsion), semisolid (e.g., ointment, gel), solid (e.g., powder, insert) or mixed (e.g., an in situ gel). Liquid and semisolid dosage forms are generally preferred for topical applications (e.g., those that include carriers such as containing liposomes, nicosomes, nanomicelles, or nanoparticles). Such dosage forms are also suitable for injection (e.g., intravitreal injection). Solid dosage forms are also suitable for injection (e.g., intravitreal injection) such as powders, ocular inserts (e.g., a solid dosage form of bioerodable materials). Atorney Docket No. : 761131.152320

[0174]

[0148] The pharmaceutical composition disclosed herein may also be formulated as a depot preparation or for use in an implanted delivery system. Such long-acting formulations may be administered by implantation, for example, intraocular, or by intraocular injection. The pharmaceutical composition may also be formulated as a depot preparation for use in an implanted drug delivery system or device, particularly for repeated refill of a reservoir in the implanted drug delivery system or device. Thus, the pharmaceutical composition may be formulated with suitable polymeric or hydrophobic materials (for example, as an emulsion in an acceptable oil) or ion exchange resins, or as sparingly soluble derivatives, for example, as a sparingly soluble salt.

[0175]

[0149] In an embodiment, the pharmaceutical composition disclosed herein can comprise a vector or viral particle comprising the nucleic acid disclosed herein. Preferably, the vector or viral particle is an AAV vector or particle. The pharmaceutical composition may comprise host cells comprising the nucleic acid disclosed herein or the viral particle comprising the nucleic acid.

[0176]

[0150] The pharmaceutical composition may further comprise one or several additional active compounds such as corticosteroids, antibiotics, analgesics, immunosuppressants, trophic factors, or any combinations thereof.

[0177] Kits

[0178]

[0151] Also disclosed herein are kits comprising the MAPK11 and / or CK1 inhibitors (e.g., small molecule inhibitors, nucleic acids disclosed herein, viral particles comprising the nucleic acid, host cells, or a pharmaceutical composition thereof).

[0179]

[0152] The kit may comprise a MAPK11 and or CK1 inhibitor in the form of a prepared pharmaceutical formulation (e.g., pharmaceutically acceptable solution) or components that are used to prepare such a formulation prior to administration, e. g., an inhibitor of MAPK11 and / or CK1 together with in sterile saline, dextrose solution, or buffered solution, or other pharmaceutically acceptable sterile fluid. The inhibitor of MAPK11 and / or CK1 can, if desired, be lyophilized or desiccated; in this instance, the kit typically further comprises in a container a pharmaceutically acceptable solution (e. g., saline, dextrose solution, etc.), to reconstitute the complex to form a solution for injection purposes. Atorney Docket No. : 761131.152320

[0180]

[0153] A kit can further comprise a needle or syringe, preferably packaged in sterile form, for injecting the complex, and / or a packaged alcohol pad. Instructions are optionally included for administration of compositions by a clinician or by the patient.

[0181] Definitions

[0182]

[0154] All publications and patents cited in this disclosure are incorporated herein by reference in their entirety. To the extent, the material incorporated by reference contradicts or is inconsistent with this specification, the specification will supersede any such material. The citation of any references herein is not an admission that such references are prior art to the present disclosure. When a range of values is expressed, it includes embodiments using any particular value within the range. Further, reference to values stated in ranges includes each and every value within that range. All ranges are inclusive of their endpoints and combinable. When values are expressed as approximations, by use of the antecedent “about,” it will be understood that the particular value forms another embodiment. Reference to a particular numerical value includes at least that particular value, unless the context clearly dictates otherwise. The use of “or” will mean “and / or” unless the specific context of its use dictates otherwise.

[0183]

[0155] Various terms relating to aspects of the description are used throughout the specification and claims. Such terms are to be given their ordinary meaning in the art unless otherwise indicated. Other specifically defined terms are to be construed in a manner consistent with the definitions provided herein. The techniques and procedures described or referenced herein are generally well understood and commonly employed using conventional methodologies by those skilled in the art, such as, for example, the widely utilized molecular cloning methodologies described in Sambrook et al., Molecular Cloning: A Laboratory Manual 4th ed. (2012) Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY. As appropriate, procedures involving the use of commercially available kits and reagents are generally carried out in accordance with manufacturer-defined protocols and conditions unless otherwise noted.

[0184]

[0156] As used herein, the singular forms “a,” “an,” and “the” include plural forms unless the context clearly indicates otherwise. The terms “include,” “such as,” and the like are intended to convey inclusion without limitation, unless otherwise specifically indicated.

[0185]

[0157] Unless otherwise indicated, the terms “at least,” “less than,” and “about,” or similar terms preceding a series of elements or a range are to be understood to refer to every element in the Atorney Docket No. : 761131.152320 series or range. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific embodiments of the invention described herein. Such equivalents are intended to be encompassed by the following claims.

[0186]

[0158] As used herein, the term “promoter” refers to any cis-regulatory elements that are generally located upstream (towards the 5' region) that directs the transcription of a nucleic acid to which it is operable linked.

[0187]

[0159] As used herein, the term "operably linked" in the context of a nucleic acid sequence, refers to the orientation of nucleotide sequences on a single nucleic acid molecule that permits the components (i.e., the nucleic acid sequences) to function in their intended manner. For example, a promoter is operably linked with a nucleic acid sequence encoding a MAPK11 or CK1 inhibitor.

[0188]

[0160] As used herein, the term "nucleic acid" or "polynucleotide" refers to a polymeric form of nucleotides of any length, either ribonucleotides or deoxyribonucleotides. Thus, this term includes, but is not limited to, single-, double- or multi- stranded DNA or RNA, genomic DNA, cDNA, DNA-RNA hybrids, or a polymer comprising purine and pyrimidine bases, or other natural, chemically or biochemically modified, non-natural, or derivatized nucleotide bases. “Polynucleotides” can be composed of single-and double-stranded DNA, DNA that is a mixture of single-and double-stranded regions, single-and double-stranded RNA, and RNA that is mixture of single-and double-stranded regions, hybrid molecules comprising DNA and RNA that may be single-stranded or, more typically, double-stranded or a mixture of single-and doublestranded regions. In addition, polynucleotides can be composed of triple-stranded regions comprising RNA or DNA or both RNA and DNA. The backbone of the polynucleotide can comprise sugars and phosphate groups (as may typically be found in RNA or DNA), or modified or substituted sugar or phosphate groups. Alternatively, the backbone of the polynucleotide can comprise a polymer of synthetic subunits such as phosphoramidates and thus can be an oligodeoxynucleoside phosphoramidate (P-NH2) or a mixed phosphoramidate-phosphodiester oligomer.

[0189]

[0161] As used herein, the term "host cell" refers to a microorganism, a prokaryotic cell, a eukaryotic cell or cell line cultured as a unicellular entity that may be, or has been, used as a recipient for a recombinant vector or other transfer of polynucleotides, and includes the progeny of the original cell that has been transfected. The progeny of a single cell may not necessarily be Atorney Docket No. : 761131.152320 completely identical in morphology or in genomic or total DNA complement as the original parent due to natural, accidental, or deliberate mutation.

[0190]

[0162] As used herein, the term “therapeutically effective amount” refers to an amount of a compound described herein (i.e., a nucleic acid) that is sufficient to achieve a desired pharmacological or physiological effect under the conditions of administration. For example, a “therapeutically effective amount” can be an amount that is sufficient to reduce the signs or symptoms of a disease or condition (e.g., visual impairment or blindness). Those skilled in the art will appreciate that the therapeutic effects need not be complete or curative, as long as some benefit is provided to the subject. A therapeutically effective amount of a pharmaceutical composition can vary according to factors such as the disease state, age, sex, and weight of the individual, and the ability of the pharmaceutical composition to elicit a desired response in the individual. An ordinarily skilled clinician can determine appropriate amounts to administer to achieve the desired therapeutic benefit based on these and other considerations.

[0191]

[0163] As used herein, the terms “treat,” “treatment,” or “treating” and grammatically related terms, refer to an improvement of any sign, symptoms, or consequence of the disease, such as prolonged survival, less morbidity, and / or a lessening of side effects. As is readily appreciated in the art, full eradication of disease is preferred but not a requirement for treatment.

[0192]

[0164] The term “subject” as used herein refers to any animal, such as any mammal, including but not limited to, humans, non-human primates, rodents, and the like. In some embodiments, the mammal is a human.

[0193]

[0165] Additional description of the methods and guidance for the practice of the methods are provided herein.

[0194] EQUIVALENTS

[0195]

[0166] It will be readily apparent to those skilled in the art that other suitable modifications and adaptions of the methods of the invention described herein are obvious and may be made using suitable equivalents without departing from the scope of the disclosure or the embodiments. Having now described certain compositions and methods in detail, the same will be more clearly understood by reference to the following examples, which are introduced for illustration only and not intended to be limiting. Atorney Docket No. : 761131.152320

[0196] EXAMPLES

[0197] Example 1. Cell type-focused compound screen in human organoids reveals CK1 and MAPK11 inhibition to protect cone photoreceptors from death

[0198] Specific and rapid live-labeling of cones in human retinal organoids

[0199]

[0167] The

[0200]

[0168] Agarose Multiwell Array Seeding and Scraping (AMASS) method was modified to generate -20,000 five-layered human retinal organoids that were grown for 30 weeks. These organoids contain the major cell classes and various cell types found in the human retina. They also exhibit functional cone photoreceptors with light-sensitive outer segments, inner segments, cell bodies, and axons. Moreover, the transcriptomic profile of the cones in the organoids resembles that of adult human cones.

[0201]

[0169] To visualize living cones, organoids were transduced with AAVs expressing GFP under control of the cone-specific promoter ProA7 (FIG. 1 A). Five different capsid variants were tested and the inventors and found that AAVs with the AAV9-PHP.eB capsid provided the highest number of labeled cones within four weeks. The cone labeling specificity in organoids was 97±1% (n=5), while the efficacy was 64±8% (n=5). The inventors performed AAV transduction in cell culture flasks that allowed simultaneous labelling of -130 organoids, which were subsequently positioned into 96-well plates for 3D imaging. As a result, the inventors achieved GFP labeling of cones in a large number of organoids with high specificity, efficacy and uniformity.

[0202] Glucose starvation induces cone death

[0203]

[0170] To induce cone death, organoids were cultured individually in 96-well plates using low glucose medium. Cell death was recorded by monitoring the disappearance of cytosolic GFP as a reliable and rapid indicator of cell death. This was realized by 3D confocal imaging of GFP in each well of the 96-well plate. The organoids were imaged for two weeks without a change of the medium to avoid any displacement of the organoids. Additionally, we included organoids in normal glucose medium in the same 96-well plate as controls.

[0204]

[0171] Three different cell-counting algorithms were developed to determine the number of cones in each organoid. The first (referred to as '3D-additive-count' ) quantifies cones image-by- Atorney Docket No. : 761131.152320 image from a 3D confocal image stack. The second ('3D-count' ) counts cones from the entire 3D stack. The third ('MlP-count') counts cones from the maximum intensity projection of the 3D stack. While the primary measure of cone numbers was based on the 3D-additive-count, we also verified the results using the 3D-count and MIP-count methods.

[0205]

[0172] The inventors measured glucose concentration in the low and normal glucose media during organoid imaging without exchanging the media. Initially, glucose levels in the low glucose medium were 9% of those in the normal glucose medium. With time, glucose levels decreased in both the low and the normal glucose media, becoming undetectable after two days in the low glucose medium and seven days in the normal glucose medium.

[0206]

[0173] Next, cones were examined over the two-week period in both types of media. In the low glucose medium, the organoids began losing cones after two days of starvation, and this cone loss continued over the two weeks. Conversely, cone numbers in the control organoids in normal glucose medium remained constant until day seven, after which they declined (FIG. 1C). Therefore, the inventors conducted further experiments for a duration of seven days. Within this time frame, the glucose-deprived organoids lost -40% of their cones, leading to a significant difference in cone numbers in the low and normal glucose conditions (low glucose, n=26; normal glucose, n=6, p<0.001, Mann-Whitney U test, (FIG. 1H). Cone cell death occurred predominantly in the central region of the organoid rather than at the edges. This spatial variation is likely attributable to the additional stress experienced by cells in contact with the bottom of the well. The finding that only about half of the cones were lost by the end of seven days in the low glucose medium enabled us to screen for compounds that either slow down cone death or accelerate it.

[0207]

[0174] Next, two compound screens were performed. In the primary screen, all compounds were tested at the same concentration of 10 pM. In the secondary screen, compounds were selected based on the results of the primary screen and retested at multiple concentrations.

[0208] Primary compound screen

[0209]

[0175] In the primary screen, -15,000 organoids distributed across 175 separate 96-well plates were used. Each 96-well plate included eight control wells, consistently positioned. Four of these control wells contained organoids in normal glucose medium with dimethyl sulfoxide (DMSO, 0.1%) but no compounds. The other four contained organoids in low glucose medium (DMSO, 0.1%) without compounds. Each remaining individual well (88 wells) within a 96-well plate Atorney Docket No. : 761131.152320 contained a unique compound, and each compound was present in five different plates, resulting in five replicates of each compound in the screen (FIG. 3A). All compounds were stored in DMSO as the solvent. Although the compounds were stored in 384-well plates, we conducted the screening in 96-well plates because the human retinal organoids were too large to be cultured in 384-well plates.

[0210]

[0176] In preparation for the screen, compounds were transferred from a 384-well plate to their designated locations on 96-well plates and then dissolved in low glucose medium. To initiate the screen, organoids were first moved from flasks containing normal glucose medium to 96-well plates and then washed in low glucose medium. Next, the low glucose medium was removed from the 96-well plates containing the organoids and the compounds, dissolved in low glucose medium, were added. The inventors conducted a 3D confocal scan of organoids with GFP- labeled cones in each well of the 96-well plates at the beginning of the screen and again at the end, seven days later. Next, three algorithms were used to quantify the number of cones at day zero (DO) and day seven (D7), defining the ratio of counts at D7 and DO as the measure of cone survival (FIG. 3 A).

[0211]

[0177] A compound library of 2,707 compounds were screened for their impact on cone survival upon glucose deprivation. The compound library, called ‘Mode of Action library’ (MOA library) contained compounds with known protein targets (Canham, S. M. et al. Systematic Chemogenetic Library Assembly. Cell Chem. Biol. 27, 1124-1129 (2020)). Some compounds had multiple targets, while others had only one (FIG. 3B). Similarly, certain targets were affected by multiple compounds, while others were affected by only one compound (FIG. 3C). The MOA library had a total of 1,662 targets that are involved in a wide range of biological processes (FIG. 3D).

[0212]

[0178] To exclude accidentally empty wells or organoids with little or no labeled cones, a threshold was applied on the DO cone count and removed wells with lower DO counts from the dataset (FIGs. 4A-O). This was necessary since the ratio of D7 and DO counts is sensitive to low DO counts. Furthermore, the inventors observed that the survival of cones was determined not only by the compounds but also by the initial cone count. There was a log-linear relationship between the DO count and cone survival at D7 in low glucose (n=14,529, R2=0.12, p<0.001, 3D- additive- count) with all three cell-counting algorithms (FIGs. 4A-O). To account for this relationship, the values of cone survival were adjusted using a linear transformation yielding the Atorney Docket No. : 761131.152320 quantity ‘adjusted cone survival’. Adjusted cone survival therefore does not depend on the cone count at DO.

[0213]

[0179] The locations of organoids on the 96- well plates did not influence cone survival: the mean adjusted survival at all positions (8.8% maximum difference between positions) remained within one standard deviation of that of the position exhibiting the least variation (12.9%), excluding the normal glucose well positions (FIG. 4H).

[0214]

[0180] To investigate additional potential batch effects in the screen, the distribution of the mean adjusted cone survival of the eight control organoids were examined: four in normal and four in low glucose; first across the 175 separate 96-well plates (FIGs. 3E-F and FIGs. 4A-O), second across the 35 experiments, each consisting of five 96-well plates with the same compound (FIGs. 4A-O), and third, across the six independent organoid productions used for the primary screen (FIG. 3G-I and FIG4. 4A-O). The inventors found no major differences between batches at any level. The mean adjusted cone survival of normal and low glucose control organoids was significantly different across all 35 experiments and across all six organoid productions, using all three cell-counting algorithms (p-values<0.001, Mann-Whitney U test). Cone survival values showed strong and significant correlations across the three cell counting algorithms (R=0.92- 0.97, p-values<0.001, Pearson correlation, (FIG. 5), suggesting that the quantification of cone survival is robust across the different algorithms.

[0215]

[0181] After accounting for potential confounding variables and batch effects, the inventors proceeded to analyze the outcome of the primary screen. The mean adjusted cone survival of most compounds was not significantly different from the mean adjusted cone survival of the low glucose control. However, one set of compounds significantly impacted cone survival negatively (‘cone-damaging compounds’, p-values<0.05, ANCOVA with Benjamini Hochberg correction for multiple testing), while another set of compounds showed a beneficial effect on cone survival (‘cone-saving compounds’) (FIG. 3J and FIGs. 5A-H).

[0216] Secondary screen: cone-damaging compounds

[0217]

[0182] In order to validate the cone-damaging and cone-saving compounds detected in the primary screen and to assess the concentration dependence of their actions, secondary screens were performed.

[0218]

[0183] First, the inventors revisited the 33 most damaging compounds selected from a set of 146 compounds that caused significant damage beyond that induced by the low glucose medium in Atorney Docket No. : 761131.152320 the primary screen (n=5 for each compound, p-values<0.05, ANCOVA with Benjamini Hochberg correction for multiple testing, (Appendix Table A-l)). These compounds were investigated at four concentrations (0.01, 0.1, 1, 10 pM) in five replicates using normal glucose medium. Normal glucose medium was used to confirm the damaging effects of these compounds on cones of healthy organoids. Furthermore, each 96-well plate included four wells with only DMSO in normal glucose medium, serving as a negative control (FIG. 6A). As for the positive control, Staurosporine, a nonselective ATP-competitive kinase inhibitor known for inducing apoptosis was utilized (Karaman, M. W. el al. A quantitative analysis of kinase inhibitor selectivity. Nat. Biotechnol. 26, 127-132 (2008) and Belmokhtar, C. A., Hillion, J. & Segal - Bendirdjian, E. Staurosporine induces apoptosis through both caspase-dependent and caspaseindependent mechanisms. Oncogene 20, 3354-3362 (2001)). This was tested also in five replicates at each of the four concentrations.

[0219]

[0184] Most compounds (29 out of 33) again induced a significant decrease in the number of cones compared to the negative control (n=5 for each compound and concentration, minimum p- value<0.05, ANOVA with Benjamini Hochberg correction for multiple testing, (FIG. 6B). Of these compounds, nine caused a more significant decrease in cone numbers than the positive control Staurosporine, which reduced cone numbers by 76%. The remaining compounds reduced cone numbers by at least 38% (Appendix Table A-2, FIG.6B, FIGs. 7A-M, and FIGs. 8A-Y).

[0220]

[0185] A variety of dose-response curves were observed for cone-damaging compounds used in the secondary screen that could be clustered into four groups. The first cluster included compounds that led to cone death only at the highest concentration (10 pM), such as an ITK kinase inhibitor and a Beta catenin inhibitor. The second cluster of curves had an action threshold of 1 pM and included a BCL2L1 inhibitor, an AP-1 inhibitor, an immunoproteasome inhibitor, and an AAA ATPase p97 inhibitor. The third cluster of curves had an action threshold of 0.1 pM, for example a sodium ionophore had such a curve. For the fourth cluster of curves, cone death increased linearly with the logarithm of compound concentration. Most of these curves belonged to HD AC I / II inhibitors (FIG. 6C-O, and FIGs. 8A-Y).

[0221]

[0186] Of the 146 compounds that caused significant damage to cones in the primary screen (p- values<0.05, ANCOVA with Benjamini Hochberg correction for multiple testing), 19 were identified as HD AC I / II inhibitors (Appendix Table A-l, FIGs. 6P and 6Q). Furthermore, in the secondary screen, seven of the 28 compounds that significantly damaged cones were HD AC I / II Atorney Docket No. : 761131.152320 inhibitors (FIG. 6B and FIGs. 7A-M). To determine whether this high number of HDAC I / II inhibitors is a result of bias in the MO A library towards HDAC I / II inhibitors or whether HDAC I / II inhibitors tend to damage cones more frequently, the results of the primary screen were reanalyzed. The inventors calculated the probability that the mean adjusted cone survival for a randomly selected set of 45 compounds is lower than the mean adjusted cone survival for the 45 different HDAC I / II inhibitors in the MOA library. This probability was smaller than 0.0001, implying that, on average, the 45 HDAC I / II inhibitors in the MOA library cause more damage to cones than a random selection of the same number of other compounds.

[0222]

[0187] To systematically investigate whether modulating any specific target is significantly more harmful to cones than modulating other targets, the inventors first selected targets that had a minimum of three compounds listed in the MOA library. A total of 660 such targets were selected (FIG. 3C). Next, the probability of observing a lower mean adjusted cone survival when randomly selecting the same number of compounds was calculated, in comparison to the compounds associated with the target. 10 targets were identified with a p-value of less than 0.0001 and less than 0.05 after Benjamini Hochberg correction for multiple testing. These targets belonged exclusively to class I / II HDACs (FIG. 6Q). Furthermore, when evaluating the percentage of compounds that led to significant cone damage among all compounds targeting each specific target, HDACs had the highest values (FIGs. 7A-M). Each HDAC I / II target was associated with 9-29 distinct compounds, out of which 44-67% induced significant damage to cones. Interestingly, compounds that acted on Sirtuins, which are class III HDACs, had no influence on cone survival (FIG. 6P, FIG. 6Q, and FIG. 7A-M). HDAC I / II inhibitors often affect multiple HDAC I / II targets and a significant negative correlation was found between the number of HDAC I / II targets of a specific inhibitor and adjusted cone survival (p<0.001, R=-0.6, Spearman correlation). Therefore, cones are specifically sensitive to HDAC I / II inhibition, and HDAC I / II inhibitors with a wide range of targets are more likely to result in cone damage than those that are more selective (FIG. 6R).

[0223]

[0188] Cones were also highly sensitive to the inhibition of tubulins (FIG. 6P, FIG. 6Q, and FIG. 7M). The probability that the mean adjusted cone survival for a random set of 10 compounds was lower than that of the 10 distinct tubulin inhibitors in the MOA library was 0.002. Of the 10 tubulin-targeting compounds, four resulted in a significant decrease in cone numbers. Notably, three of these compounds had a broad target range, affecting 19-20 different tubulins. Atorney Docket No. : 761131.152320

[0224] Secondary screen: cone-saving compounds

[0225]

[0189] Seven compounds in the primary significantly increased cone survival. The inventors proceeded with these compounds as well as 24 other compounds that had the highest effect in protecting cones during glucose deprivation in the primary screen. These 31 compounds were tested at four different concentrations (0.01, 0.1, 1, and 10 pM) in five replicates in low glucose medium. Each 96-well plate included four wells containing only DMSO in normal glucose medium as a positive control, and four wells containing only DMSO in low glucose medium as a negative control (FIG. 9 A).

[0226]

[0190] The inventors confirmed that four out of the 31 compounds tested in the secondary screen have a significant positive impact on cone survival after correction for multiple testing (n=5 for each compound and concentration, minimum p-values<0.05, ANCOVA with Benjamini Hochberg correction for multiple testing, (Appendix Table A- 3 and FIG. 9B-E, FIG. 10A-O, FIG. 11A-Z and AA). These four compounds include an inhibitor of HSP90AA1 (‘HSP90 inhibitor 1 ’), an inhibitor of both HSP90AA1 and HSP90AB1 (‘HSP90 inhibitor 2’), an inhibitor of MTOR, PIK3CA, PIK3CB, and PIK3CD (‘MTOR inhibitor 1 ’), and an inhibitor of PDGFRA and PDGFRB (‘PDGFR inhibitor 1’)- The two HSP90 inhibitors demonstrated stronger activity at lower concentrations (0.1 or 1 pM) and less activity at a concentration of 10 pM (FIGs. 9B-E). The dose-response curves of the MTOR inhibitor and the PDGFR inhibitor showed similar patterns, being effective only at the highest concentration of 10 pM (FIG. 9B-E).

[0227]

[0191] To understand the relationship between the four compounds and their targets in the context of cone protection, the results of the primary screen were re-analyzed, focusing on the targets of the four inhibitors that were confirmed to protect cones (HSP90AA1, HSP90AB1, MTOR, PIK3CA, PIK3CB, PIK3CD, PDGFRA, and PDGFRB). Five compounds in the MOA library that target HSP90AA1 were found, four of which resulted in adjusted cone survival higher than 80% (although some of these were not significant in the primary screen). For all other targets, the percentages of compounds with a positive effect on cone survival were only between 11 and 33% (FIGs. 9F-H and FIGs. 12A-M). These results suggest that HSP90AA1 is the target of HSP90 inhibitors 1 and 2 in cones. Additionally, they suggest that the other two compounds (MTOR inhibitor 1 and PDGFR inhibitor 1), which are both kinase inhibitors, have different causal targets in human cones than those originally listed in the MOA library. Atorney Docket No. : 761131.152320

[0228]

[0192] To systematically examine whether modulating particular targets has a greater positive impact on cones compared to other targets, the inventors conducted an analysis focusing on 660 targets that had at least three partner compounds listed in the MOA library. To rank targets in their ability to protect cones, the probability was calculated of observing a higher mean adjusted cone survival in the primary screen when randomly selecting the same number of compounds in comparison to the compounds associated with the target. HSP90AA1 emerged as one of the topranked targets (p<0.00001 and p<0.01 after Benjamini Hochberg correction for multiple testing). Targets such as HSP90AB1, MTOR, PIK3CA, PIK3CB, PIK3CD, PDGFRA, and PDGFRB were not significant because a large proportion of compounds acting on these targets had no impact on cone survival (FIGs. 9F-H, and FIGs. 12A-M). TP53 was a further significant target (p<0.00001 and p<0.01 after Benjamini Hochberg correction for multiple testing), for which there were three compounds in the library, two inhibitors and one expression enhancer. However, both inhibitors and the expression enhancer increased cone survival in the primary screen, and the enhancer had no significant effect after retesting, suggesting that TP53 is not a target for cone protection.

[0229]

[0193] To further explore the connection between the four validated compounds that protect cones and their targets, the inventors compared available data on IC50 (the concentration at which a compound shows 50% of its maximum inhibitory effect) with the effect on cone survival of inhibitors of HSP90AA1, HSP90AB1, MTOR, PIK3CA, PIK3CB, PIK3CD, PDGFRA, and PDGFRB. A significant negative correlation was found between the reported IC50s and the adjusted cone survival for the inhibitors of HSP90AA1 (R=-0.7, Spearman correlation, p=0.03, (FIG. 12). This suggests that compounds with lower IC50 values (indicating greater potency) are linked to higher adjusted cone survival. However, the IC50s for the inhibitors of HSP90AB1, MTOR, PIK3CA, PIK3CB, PIK3CD, PDGFRA, and PDGFRB were not significantly correlated with cone survival. These findings further confirm that HSP90AA1 is a target that, when inhibited, effectively protects cones from the effects of glucose starvation at day seven. Therefore, HSP90 inhibitor 1 was renamed as ‘HSP90AA1I-1 ’ and HSP90 inhibitor 2 as ‘HSP90AA1I-2’. On the other hand, HSP90AB1, MTOR, PIK3CA, PIK3CB, PIK3CD, PDGFRA, and PDGFRB are not causal targets that affect organoid cone survival. Since MTOR inhibitor 1 and PDGFR inhibitor 1 are kinase inhibitors, we renamed them as ‘Cone-Saving Atorney Docket No. : 761131.152320

[0230] Kinase inhibitor 1’ (CS-KI-1), and as ‘Cone-Saving Kinase inhibitor 2’ (CS-KI-2), respectively (FIGs. 9I-K).

[0231]

[0194] The effects of HSP90AA1I-1, CS-KI-1, and CS-KI-2 were tested on organoids under normal glucose conditions. None of the compounds had a significant effect after seven days compared to the normal glucose control conditions (FIG. 13).

[0232]

[0195] Additional tests were conducted on the three compounds HSP90AA1I-1, CS-KI-1, and CS-KI-2 over a 14-day period. These compounds were administered in the concentrations that had the strongest effect during the secondary screen: 1 pM for HSP90AA1I-1 and 10 pM for CS- KI-1 and CS-KI-2. Organoids were treated with these compounds in low glucose medium and performed imaging after 7 and 14 days. Using both normal and low glucose media with DMSO (without the compounds) as negative and positive controls, respectively (FIGs. 9L-9M).

[0233]

[0196] HSP90AA1I-1 showed significant protection of cones from death after seven days but became detrimental to cones after 14 days compared to the low glucose control (n=10, 7 days: p<0.001, 14 days: p=0.01, Mann-Whitney U test, FIG. 9L). In contrast, CS-KI-1 and CS-KI-2 had a significant rescuing effect on cones at both seven and 14 days (low glucose, n=10; CS-KI- 1, n=9, 7 days: p<0.001, 14 days: p=0.002; CS-KI-2, n=10, 7 days: p<0.001, 14 days: p<0.001, Mann-Whitney U test, FIG. 9M and FIG. 9N). These findings suggest that HSP90AA1 inhibition is detrimental to cone survival in the long term and that the protective effect of CS-KI- 1 and CS-KI-2 on cones is of long duration.

[0234] Effect of HSP90AA11-1 , CS-KI-1, and CS-KI-2 on rod photoreceptor death

[0235]

[0197] HSP90AA1I-1, CS-KI-1, and CS-KI-2 each had a protective effect on cones after seven days of glucose starvation and we examined whether they would offer a similar protection to rods. To do this, we used the promoter ProA330, which targeted rods in human retinal organoids. When AAV9-PHP.eB capsid-coated AAVs that expressed GFP under the control of the ProA330 were introduced into human retinal organoids, GFP expression was observed in rods with a specificity of 98 ± 3% (n=6) and an efficacy of 38 ± 3% (n=6) (FIGs. 14A and 14B). ProA330 also drove specific expression in rods of mouse retina in vivo with a specificity of 99.7% ± 0.5% and an efficacy of 41 ± 7% (n=3 retinas, 2 mice, FIG. 15A-B).

[0236]

[0198] Similar to cones, rods also died during glucose starvation, with a survival by day seven of 51% in low glucose and 89% in normal glucose. The number of remaining rods was significantly different in low and normal glucose (low glucose, n=l 1, normal glucose, n=12, p<0.001, Mann- Atorney Docket No. : 761131.152320

[0237] Whitney U test, (FIGs. 14C-14D). Rod survival dropped further after 14 days to 37% in low glucose and 77% in normal glucose (low glucose, n=9, normal glucose, n=6, p<0.001, Mann- Whitney U test).

[0238]

[0199] Treatment with 10 pM CS-KI-1 or 10 pM CS-KI-2 led to an increase in rod survival after seven days of starvation (low glucose, n=l 1; CS-KI-1, n=18, p=0.002; CS-KI-2, n=18, p<0.001, Mann-Whitney U test, FIG. 14D). However, only CS-KI-2 had a significant protective effect after 14 days (p<0.001, Mann-Whitney U test). In contrast to cones, the inventors did not detect a significant protective or detrimental effect of HSP90AA1I-1 on rod photoreceptors at any time.

[0239] CS-K-1 and CS-KI-2 nonfunctional analogs for identifying causal targets and transcriptional changes

[0240]

[0200] A problem with identifying targets of CS-KI-1 and CS-KI-2 as well as transcriptional changes caused by CS-KI-1 and CS-KI-2 is that these compounds are known inhibitors of MTOR and PDGFR, respectively. At the same time, they also interact with unknown pathways that protect cones. As the inventors argued before, the cone protection effect is most likely independent of both MTOR and PDGFR inhibition since other inhibitors of MTOR or PDGFR used in the primary screen did not save cones. Therefore, the inventors used the following strategy to find MTOR- and PDGFR-pathway-independent targets of CS-KI-1 and CS-KI-2 as well as to identify transcriptional changes induced by CS-KI-1 and CS-KI-2. An MTOR inhibitor used in the primary screen that did not protect cones but had a very similar chemical structure to CS-KI-1 was identified, which was named CS-KI-1A (CS-KI-1 analogue). Similarly, the inventors identified a PDGFRA inhibitor used in the primary screen that did not protect cones but had a very similar structure to CS-KI-2, which was named CS-KI-2A (FIG. 16A-G).

[0241]

[0201] The inventors repeated experiments with 10 pM CS-KI-1, CS-KI-1A, CS-KI-2, CS-KI- 2A to assess their effectiveness in preventing cone death induced by glucose starvation. As in the primary screen CS-KI-1 A did not improve cone survival compared to low glucose and its effect was significantly different from that of CS-KI-1 (n=9, p=0.002, Mann-Whitney U test, FIG. 16B). The same relation was observed between CS-KI-2A and low glucose and CS-KI-2 (n=10, p<0.001, Mann-Whitney U test, FIG. 16A-G).

[0242]

[0202] The inventors then looked for targets of CS-KI-1 and CS-KI-2 that are not targets of CS- KI-1 A and CS-KI-2A, respectively, using kinase profiling. Similarly, they looked for differential Atorney Docket No. : 761131.152320 changes in transcription caused by CS-KI-1 and CS-KI-1A, as well as by CS-KI-2 and CS-KI- 2A.

[0243] Transcriptomic changes in cones and rods induced by cone-saving compounds

[0244]

[0203] Dual color retinal organoids were generated with green-fluorescent cones and red- fluorescent rods by transducing them with AAV9-PHP.eB capsid-coated ProA7-GFP and ProA330-tdTomato AAVs simultaneously. This allowed the inventors to isolate cones and rods from the same organoids using fluorescence-activated cell sorting (FIGs. 17A-E). Subsequently, their transcriptomes were analyzed separately using bulk RNA-sequencing.

[0245]

[0204] The inventors aimed to identify genes and pathways involved in the survival of cones or rods, specifically those whose expression is altered by CS-KI-1 compared to CS-KI-1 A and low glucose controls, or by CS-KI-2 compared to CS-KI-2A and low glucose controls. In addition, the effect of HSP90AA1I-1 inhibition on photoreceptor transcriptomes was analyzed. The transcriptomes of cones and rods in normal glucose control organoids and in organoids exposed to seven days of glucose starvation in the presence or absence of HSP90AA1I-1, CS-KI-1, CS- KI-1 A, CS-KI-2 or CS-KI-2A were determined.

[0246]

[0205] Cells that were GFP positive expressed marker genes for cones, while tdTomato-positive cells expressed marker genes for rods. This was observed in both the normal and the low-glucose conditions, indicating, on the one hand, the effective isolation of the two cell types and, on the other hand, that the transcriptomic identity of cones and rods was not affected by glucose starvation (FIGs. 18A-C).

[0247]

[0206] The annotated target genes of HSP90AA1I-1 , namely HSP90AA1 and HSP90AB1 , were highly expressed in both cones and rods. Expression of the annotated target genes of CS-KI-1, including MTOR, PIK3CA, PIK3CB, and PIK3CD, was low. Moreover, the annotated target genes of CS-KI-2, PDGFRA and PDGFRB, were not or barely expressed in cones and rods (FIG. 18). These findings further support the notion that HSP90AA1 and HSP90AB1 are targets of HSP90AA1I-1 in cones, while PDGFRA and PDGFRB are not targets of CS-KI-2 in cones and rods.

[0248]

[0207] The remaining glucose is low in normal glucose medium after seven days and this may already subject organoids to a state of starvation. Therefore, the inventors included a condition in which organoids received media exchanges every other day (‘untreated’ control). No differentially expressed genes were found when comparing cones and rods in normal glucose Atorney Docket No. : 761131.152320 relative to untreated cones and rods (FIGs. 19A-K). Principal component analysis showed the transcriptome of cones in low glucose to be close to the transcriptome of cones in normal glucose. This was also true for rods. Treatment with HSP90AA1I-1 induced a strong shift in the transcriptomes of both cones and rods (FIG. 16G). CS-KI-1 or CS-KI-1A treated rods differed markedly from untreated rods, which was not the case for cones. CS-KI-2 and CS-KI-2A both caused minor shifts in photoreceptor transcriptomes (FIG. 16G).

[0249]

[0208] Consistent with the principal component analysis, the inventors identified only a limited number of genes differentially expressed between normal and low glucose controls: four genes were downregulated in cones, of which HSPA6 was the only gene also downregulated in rods when comparing normal to low glucose conditions (FIGs. 19A-K). Following HSP90AA1I-1 treatment, cones exhibited differential expression relative to the low glucose condition in 776 genes, with 169 genes upregulated and 607 genes downregulated. In rods, 423 genes were differentially expressed, including 92 upregulated and 331 downregulated genes (FIGs. 19A-K). Among these, 47 upregulated and 223 downregulated genes were differentially expressed in both cones and rods. Gene set enrichment analysis (GO terms), revealed that genes involved in RNA processing, which includes transcription, splicing, and translation, were upregulated in both cones and rods treated with HSP90AA1I-1 compared to the low glucose controls. This upregulation explains the significant number of genes differentially expressed. Additionally, genes associated with the unfolded protein response were upregulated in cones (Molecular Signature Database). This finding aligns with the known function of HSP90 as a molecular chaperone that assists in protein folding.

[0250]

[0209] For CS-KI-1, we examined genes that showed differential expression when comparing the transcriptomes of samples treated with CS-KI-1 against those treated with CS-KI-1 A and the low glucose control samples. The inventors sought to identify genes that are differentially expressed in CS-KI-1 compared to low glucose controls, but not CS-KI-1 A and the low glucose controls. 22 upregulated and 15 downregulated genes were identified in cones, and in rods, and 39 upregulated and 130 downregulated genes were found (FIGs. 16H-J and FIGs. 21A-D). Notably, 10 either upregulated or downregulated genes were common to both cones and rods. Gene set enrichment analysis (Molecular Signature Database) revealed that apoptotic genes were downregulated in both rods and cones. Moreover, cones exhibited downregulation of inflammatory response genes, including those in TNF-alpha signaling via NFKB and Interferon Atorney Docket No. : 761131.152320

[0251] Alpha responses. This suggests that the downregulation of both inflammatory and noninflammatory cell death pathways could be involved in enhancing cone survival (FIGs. 22A-H).

[0252]

[0210] The inventors adopted a similar approach for CS-KI-2, examining genes differentially expressed when comparing CS-KI-2-treated samples to those treated with CS-KI-2A and to low glucose controls. Consistent with the principal component analysis, CS-KI-2 treatment resulted in fewer differentially expressed genes. In cones, 10 significantly upregulated genes were identified, with HMGCS1, MSM01, INSIGI, and ACAT2I also showing significant upregulation in rods. Additionally, HTR2C was found to be downregulated in cones (FIGs. 16H- J). Gene set enrichment analysis in both cones and rods indicated that genes involved in mTORCl signaling and cholesterol homeostasis were upregulated following CS-KI-2 treatment. Furthermore, genes related to fatty acid metabolism showed upregulation in cones (FIGs. 22A- H).

[0253]

[0211] These findings indicate that treatment with HSP90AA1I-1, CS-KI-1, or CS-KI-2 induces highly distinct gene expression alterations in photoreceptors, each manifesting varying degrees of transcriptomic changes. Despite numerous shared expression modifications across treatments in both rods and cones, there are also notable cell type-specific effects.

[0254] Photoreceptor-saving targets of CS-KI-1 and CS-KI-2 revealed by kinase profiling

[0255]

[0212] To investigate causal targets of CS-KI-1 and CS-KI-2 for saving cones or rods, biochemical kinase profiling was conducted for these compounds and their nonfunctional analogues, CS-KI-1 A and CS-KI-2A. The inventors assessed the activity of 350 human kinases after treatment with each of the four compounds, comparing their activities at 10 pM against a vehicle control (Appendix Table A-4, FIGs. 23A-D).

[0256]

[0213] CS-KI-1 and its nonfunctional analogue CS-KI-1 A had little effect on the activities of most of the 350 kinases, however, there were a few exceptions. As expected, both CS-KI-1 and CS-KI-1 A induced complete inhibition of MTOR. Remarkably, the activity of only one kinase, the gamma 1 form of casein kinase 1 (CSNK1G1), was fully suppressed by CS-KI-1 but not influenced at all by CS-KI-1A (Appendix Table A-4, FIGs. 23A-D). CSNK1G1 is therefore a potential target for the cone- and rod-saving effects of CS-KI-1 that is independent of MTOR inhibition.

[0257]

[0214] Similarly, the activity of most kinases was not influenced by CS-KI-2 or its nonfunctional analog CS-KI-2A. Both CS-KI-2 and CS-KI-2A induced full inhibition of PDGFRA. The Atorney Docket No. : 761131.152320 activity of only one kinase, mitogen-activated protein kinase 11 (MAPK11) was fully blocked by CS-KI-2 but not inhibited at all by CS-KI-2A. Indeed CS-KI-2A increased activity of MAPK11 (Appendix Table A-4, FIGs. 23A-D). MAPK11 is thus a potential target for the cone- and rodsaving effects of CS-KI-2 that is independent of PDGFRA inhibition.

[0258]

[0215] Therefore, the inventors tested three known inhibitors of casein kinase 1 (CK-1) or MAPK1 1 on both organoid cones and rods using the two-color organoids (GFP in cones and tdTomato in rods) described above at either 10 or 1 pM inhibitor concentrations. Strikingly, all three CK-1 inhibitors significantly improved cone survival at one or both concentrations (CK1-I- 1, 10 pM, p<0.001; 1 pM, p=0.04; CK-l-I-2, 1 pM, p=0.01; CK1-I-3, 1 pM, p=0.01; n=14, Mann-Whitney U test with Benjamini Hochberg correction for multiple testing). This was also true for rods (CK1-I-1 10 pM, p=0.01; CK1-I-2 10 pM, p=0.009; CK1-I-3, 1 pM, p=0.009; n=7, Mann-Whitney U test with Benjamini Hochberg correction for multiple testing). Two out of three MAPK11 inhibitors had a significant positive effect on cone survival (MAPK11-1-2, 10 pM, n=14, p=0.01; MAPK11-I-3, 10 pM, n=13, p=0.01) and one of the MAPK11 inhibitors significantly improved rod survival (MAPK11-1-3 IpM, n=7, p=0.009; Mann-Whitney U test with Benjamini Hochberg correction for multiple testing, Appendix Table A-5, FIGs. 23E and 23F).

[0259]

[0216] MAPK11 and CSNK1G, along with other casein kinase 1 -encoding genes, are expressed in both organoid rods and cones, as well as in human retina rods and cones, both in the fovea and the periphery (FIG. 24a-c).

[0260] Discussion of results of Example 1

[0261] Large-scale compound screen in human organoids

[0262]

[0217] The inventors have performed a cell type-focused compound screen in -20,000 human organoids using 2,707 compounds with annotated targets. A modified AMASS method (Cowan, C. S. et al. Cell Types of the Human Retina and Its Organoids at Single-Cell Resolution. Cell 182, 1623-1640. e34 (2020)) was used to produce replicable, multilayered human retinal organoids in large quantities. The death of cones was induced by lowering glucose for seven days and monitored cell death by imaging GFP that was expressed specifically in cones. The inventors identified compounds that protected cones, compounds that damaged cones, and compounds that had no effect. The results of the primary screen, including the names and unique Atorney Docket No. : 761131.152320 identifiers of all the compounds, their annotated targets, and their effect on cone survival are publicly available online at ConeTargetedCompoundScreen.iob.ch.

[0263]

[0218] Among the photoreceptors, the inventors have focused on cones since the dysfunction of cones leads to blindness, while rod dysfunction leads to no or minor visual disabilities (Zeitz, C., Robson, A. G. & Audo, I. Congenital stationary night blindness: An analysis and update of genotype-phenotype correlations and pathogenic mechanisms. Prog. Retin. Eye Res. 45, 58-110 (2015)). Cones were labeled with AAVs carrying a cone-specific promoter (Juttner, J. et al. Targeting neuronal and glial cell types with synthetic promoter AAVs in mice, non-human primates and humans. Nat. Neurosci. 22, 1345-1356 (2019)). The use of AAVs has the advantage over using organoids with genetically labeled cell types in that the target cell type can be rapidly changed across organoids with the same genetic background. Different genetic backgrounds can lead to variation in the structure and cell-type composition of retinal organoids (Cowan, C. S. etal. Cell Types of the Human Retina and Its Organoids at Single-Cell Resolution. Cell 182, 1623-1640.e34 (2020)). AAV-based labeling allowed the inventors to test some of the compounds on rods of organoids grown from the same induced pluripotent cell line, using AAVs carrying a rod-specific promoter.

[0264]

[0219] To find molecules that either protect or damage cones, the screen had to satisfy several conditions. First, that the inventors could compare the number of cones before and after the induction of death in each organoid. This is important since the number of cones varies across individual organoids. Second, that the time period in which death happens is short, within days. The reason for this is practical: it allows the testing of more organoids and compounds. Furthermore, organoids do not need a medium exchange within a few days, thus allowing live- imaging of the same organoids in the same positions. The short time period to detect cone death required that the degeneration of cones is induced synchronously and progresses rapidly within and across organoids. An alternative would have been the use of patient-derived or CRISPR- engineered human organoids with either primary or secondary cone degeneration. However, cone degeneration in such organoids has so far not been observed. If it is observed in the future, it is likely to happen over a long period of time and asynchronously. Third, that during the period in which cone death occurs, organoids should reach a state in which about half of the cones die and half remain alive, thus allowing a search for compounds that protect cones and those that damage cones. Fourth, the use of a large number of organoids. On the one hand, this allows for Atorney Docket No. : 761131.152320 the screening of many compounds; on the other hand, the large numbers allow study of potentially confounding variables that affect cone death. Such a confounding variable was the number of cones before starvation: the percentage of cones dying in the low glucose condition is lower in small organoids with fewer cones. Interestingly, the fact that human retinal organoids need to grow for ca. 30 weeks to yield developed cones did not hinder the screen. Since batch-to- batch variability in cone survival was not detected, different batches of organoids could be initiated in a short time period, one after the other, and thus many organoids could be produced semi-parallel.

[0265]

[0220] The inventors developed three cell-counting algorithms for counting cones from the stack of images taken of each organoid. Each image stack was -260 MB and the entire dataset was -5 TB. The 3D-additive-count was used as the primary measure, since MIP-count loses information on the edges of the organoids, where different cones are merged in the maximum intensity projection, and since the 3D-count is computationally time consuming.

[0266]

[0221] In the course of this work, the inventors developed a promoter, Pro A330, that allows specific labeling of rods in human organoids. Thus, it was possible to mark cones and rods in the same organoid using ProA7-driven GFP and ProA330-driven tdTomato from two different AAVs. In the future, these dual color organoids will enable human retinal organoid screens focused on rods and cones simultaneously.

[0267]

[0222] Since most organoids have more than one cell type, and in many organs diseases affect specific cell types, the methods of and the lessons learned from the cell type-focused screen the inventors conducted in human retinal organoids are likely to be useful for performing large-scale screens in other types of human organoids.

[0268] Compounds that damage cones and HD AC inhibition

[0269]

[0223] The inventors identified 146 compounds that caused significant damage to cones in human retinal organoids. HD AC I / II inhibitors were found with a wide range of targets lead to significant damage to cone photoreceptors. This damaging effect is proportional to the logarithm of the compound concentration. More selective HD AC inhibitors resulted in less damage to cones in human organoids. It was shown that inhibiting HDACs broadly in the developing mouse retina using trichostatin-A reduces the expression of transcription factors, including Otx2, Nrl, and Crx, which are important for rod development. Additionally, inhibiting HDACs in mouse retinal explant cultures resulted in a complete loss of rod photoreceptors (Chen, B. & Cepko, C. Atorney Docket No. : 761131.152320

[0270] L. Requirement of histone deacetylase activity for the expression of critical photoreceptor genes. BMC Dev. Biol. 7, 78 (2007)). Conversely, overexpression of Hdac4 in a mouse model of retinal degeneration extended the survival of photoreceptors (Chen, B. & Cepko, C. L. HDAC4 regulates neuronal survival in normal and diseased retinas. Science 323, 256-259 (2009)). Taken together, this work on cones of human retinal organoids together with the work on rods in mouse retina (Chen, B. & Cepko, C. L. Requirement of histone deacetylase activity for the expression of critical photoreceptor genes. BMC Dev. Biol. 7, 78 (2007) and Chen, B. & Cepko, C. L. HDAC4 regulates neuronal survival in normal and diseased retinas. Science 323, 256-259 (2009)) suggests that broad HDAC-inhibition is damaging to both cone and rod photoreceptors. This is particularly relevant because various HD AC inhibitors are currently being tested in clinical trials or have already been approved for cancer treatment (Eckschlager, T., Pich, J., Stiborova, M. & Hrabeta, J. Histone Deacetylase Inhibitors as Anticancer Drugs. Ini. J. Mol. Sci. 18, 1414 (2017)). Therefore, it will be important to monitor the structure and function of the retina in patients receiving these treatments.

[0271]

[0224] Interestingly, some studies have found that broad inhibition of HDACs by trichostatin-A in mouse models of retinal degeneration can have positive effects on cones Samardzija, M. el al. HD AC inhibition ameliorates cone survival in retinitis pigmentosa mice. Cell Death Differ. 28, 1317-1332 (2021) and Trifunovic, D. et al. HDAC inhibition in the cpfll mouse protects degenerating cone photoreceptors in vivo. Hum. Mol. Genet. 25, 4462-4472 (2016)), and another study has suggested that targeted inhibition of HDAC6 positively impacts the cones of mice (Sundaramurthi, H. et al. Selective Histone Deacetylase 6 Inhibitors Restore Cone Photoreceptor Vision or Outer Segment Morphology in Zebrafish and Mouse Models of Retinal Blindness. Front. Cell Dev. Biol. 8, 689 (2020)). Currently, it is unclear why the impact of broad HDAC inhibition on cone cells differs between humans and mice.

[0272] Compounds that protect human cones

[0273]

[0225] Considerable effort has been made to find ways to protect cones in animal models of retinal degeneration (e.g,. see Narayan, D. S., Wood, J. P. M., Chidlow, G. & Casson, R. J. A review of the mechanisms of cone degeneration in retinitis pigmentosa, Acta Ophthalmol. (Copenh.) 94, 748-754 (2016), Ait-Ali, N. et al. Rod-derived cone viability factor promotes cone survival by stimulating aerobic glycolysis. Cell 161, 817-832 (2015), Amamoto, R., Wallick, G. K. & Cepko, C. L. Retinoic acid signaling mediates peripheral cone photoreceptor survival in a Atorney Docket No. : 761131.152320 mouse model of retina degeneration. eLife 11, e76389 (2022), Byrne, L. C. et al. Viral-mediated RdCVF and RdCVFL expression protects cone and rod photoreceptors in retinal degeneration. J. Clin. Invest. 125, 105-116 (2015), Leveillard, T. et al. Identification and characterization of rod- derived cone viability factor. Nat. Genet. 36, 755-759 (2004), Mohand-Said, S. et al. Normal retina releases a diffusible factor stimulating cone survival in the retinal degeneration mouse. Proc. Natl. Acad. Sci. U. S. A. 95, 8357-8362 (1998), Pardue, M. T. & Allen, R. S.

[0274] Neuroprotective strategies for retinal disease. Prog. Retin. Eye Res. 65, 50-76 (2018), Punzo, C., Kornacker, K. & Cepko, C. L. Stimulation of the insulin / mTOR pathway delays cone death in a mouse model of retinitis pigmentosa. Nat. Neurosci. 12, 44-52 (2009), Sahel, J. -A. & Leveillard, T. Maintaining Cone Function in Rod-Cone Dystrophies. Adv. Exp. Med. Biol. 1074, 499-509 (2018), Wang, S. K., Xue, Y. & Cepko, C. L. Microglia modulation by TGF-pi protects cones in mouse models of retinal degeneration. J. Clin. Invest. 130, 4360-4369 (2020), Wang, S. K., Xue, Y. & Cepko, C. L. Augmentation of CD47 / SIRPa signaling protects cones in genetic models of retinal degeneration. JCI Insight 6, el 50796 (2021), Wang, S. K., Xue, Y., Rana, P., Hong, C. M. & Cepko, C. L. Soluble CX3CL1 gene therapy improves cone survival and function in mouse models of retinitis pigmentosa. Proc. Natl. Acad. Sci. U. S. A. 116, 10140-10149 (2019), Xue, Y. & Cepko, C. L. Gene Therapies for Retinitis Pigmentosa that Target Glucose Metabolism.

[0275] Cold Spring Harb. Perspect. Med. A041289 (2023) doi: 10.1101 / cshperspect.a041289, Xue, Y. et al. Chromophore supply modulates cone function and survival in retinitis pigmentosa mouse models. Proc. Natl. Acad. Sci. U. S. A. 120, e2217885120 (2023), Xue, Y. et al. AAV-Txmp prolongs cone survival and vision in mouse models of retinitis pigmentosa. eLife 10, e66240 (2021), and Yang, Y. et al. Functional cone rescue by RdCVF protein in a dominant model of retinitis pigmentosa. Mol. Ther. J. Am. Soc. Gene Ther. 17, 787-795 (2009) and some identified modifiers of cone death are currently being evaluated in clinical trials (SparingVision. A Phase I / II Study to Assess the Safety and Tolerability of a Single Subretinal Administration of SPVN06 Gene Therapy in Subjects With Rod-Cone Dystrophy (RCD) Due to a Mutation in the RHO, PDE6A, or PDE6B Gene. https: / / clinicaltrials.gov / study / NCT05748873 (2023)). However, no treatment for protecting cones in photoreceptor diseases such as macular degeneration or retinitis pigmentosa has yet received approval for use in humans.

[0276]

[0226] In this study, the inventors adopted a complementary approach by screening compounds based on their ability to enhance human cone survival in organoids. Atorney Docket No. : 761131.152320

[0277]

[0227] Cone death was induced by glucose starvation not only because this triggers synchronous and rapid cone death, but also because it has been demonstrated that enhanced glucose uptake and glycolysis promote cone photoreceptor survival in animal models of photoreceptor degeneration. This suggests that cones experience starvation-induced death in some photoreceptor diseases (Ait-Ali, N. et al. Rod-derived cone viability factor promotes cone survival by stimulating aerobic glycolysis. Cell 161, 817-832 (2015), Punzo, C., Kornacker, K. & Cepko, C. L. Stimulation of the insulin / mTOR pathway delays cone death in a mouse model of retinitis pigmentosa. Nat. Neurosci. 12, 44-52 (2009), Whalley, K. Cones go hungry. Nat. Rev. Neurosci. 10, 84-85 (2009), Bovolenta, P. & Cisneros, E. Retinitis pigmentosa: cone photoreceptors starving to death. Nat. Neurosci. 12, 5-6 (2009), and Krol, J. & Roska, B. Rods Feed Cones to Keep them Alive. Cell 161, 706-708 (2015)). The extent to which glucose starvation mirrors what occurs in degenerative diseases requires future assessment. In primary and secondary screens, the inventors isolated four compounds that had a significant protective effect on cones after seven days of glucose starvation.

[0278]

[0228] Two of the four compounds that protected cones, HSP90AA1I-1 and HSP90AA1I-2, target the same protein, HSP90. An earlier study demonstrated that a single dose of an HSP90 inhibitor improved visual function and delayed photoreceptor degeneration in a P23H transgenic rat model (Aguila, M. et al. Hsp90 inhibition protects against inherited retinal degeneration. Hum. Mol. Genet. 23, 2164-2175 (2014)). Despite the protective effects on photoreceptors observed in both human organoids and rats, we argue that inhibiting HSP90 is not suitable for preserving human cones. First, inhibiting HSP90 caused significant damage to cones in human organoids after 14 days of treatment. Second, HSP90 inhibition resulted in major alterations in the transcriptomes of both cone and rod photoreceptors in human organoids. HSP90 has been described as an orchestrator of transcription, a finding that aligns with our results Sawarkar, R. & Paro, R. Hsp90@chromatin. nucleus: an emerging hub of a networker. Trends Cell Biol. 23, 193— 201 (2013), Khurana, N. & Bhattacharyya, S. Hsp90, the Concertmaster: Tuning Transcription. Front. Oncol. 5, (2015), Calderwood, S. K. & Neckers, L. Hsp90 in Cancer, in Advances in Cancer Research vol. 129 89-106 (Elsevier, 2016)). Third, administering HSP90 inhibitors systemically to dogs was found to induce damage to photoreceptors and to impair vision (Kanamaru, C. et al. Retinal toxicity induced by small-molecule Hsp90 inhibitors in beagle dogs. J. Toxicol. Sci. 39, 59-69 (2014)). Atorney Docket No. : 761131.152320

[0279]

[0229] The other two compounds that protected cones, CS-KI-1 and CS-KI-2, are kinase inhibitors. Three pieces of evidence suggest that the currently labeled targets, including MTOR (CS-KI-1) and PDGFRA (CS-KI-2), are not responsible for the effects of CS-KI-1 and CS-KI-2 in cones. First, many inhibitors targeting the same labeled targets had no impact on the survival of cones. Second, the IC50 values of different inhibitors were not correlated with the magnitude of the protective effect on cones. Third, the targets of CS-KI-2 (PDGFRA and PDGFRB) are not or barely expressed in organoid cones.

[0280]

[0230] Transcriptomic analysis of photoreceptors treated with CS-KI-1 identified differentially expressed genes relative to CS-KI-1 A and low glucose that lead to the downregulation of stress responses as well as inflammatory and non-inflammatory cell death pathways. Both apoptotic and necrotic cell death have been described as potential pathways for disease-related photoreceptor degeneration (Marigo, V. Programmed Cell Death in Retinal Degeneration: Targeting Apoptosis in Photoreceptors as Potential Therapy for Retinal Degeneration. Cell Cycle 6, 652-655 (2007), Sancho-Pelluz, J. et al. Photoreceptor Cell Death Mechanisms in Inherited Retinal Degeneration. Mol. Neurobiol. 38, 253-269 (2008), Murakami, Y. et al. Necrotic cone photoreceptor cell death in retinitis pigmentosa. Cell Death Dis. 6, e2038-e2038 (2015), Kakavand, K. et al. Photoreceptor Degeneration in Pro23His Transgenic Rats (Line 3) Involves Autophagic and Necroptotic Mechanisms. Front. Neurosci. 14, 581579 (2020), and Punzo, C., Kornacker, K. & Cepko, C. L. Stimulation of the insulin / mTOR pathway delays cone death in a mouse model of retinitis pigmentosa. Nat. Neurosci. 12, 44-52 (2009)).

[0281]

[0231] Interestingly, CS-KI-2 elicited a distinct response characterized by the upregulation of a smaller set of genes involved in cholesterol homeostasis and mTORCl signaling. Previous research in a mouse model of retinitis pigmentosa demonstrated that activation of the mTOR pathway can delay cone cell death (Punzo, C., Kornacker, K. & Cepko, C. L. Stimulation of the insulin / mTOR pathway delays cone death in a mouse model of retinitis pigmentosa. Nat. Neurosci. 12, 44-52 (2009)).

[0282]

[0232] By performing a kinase screen using CS-KI-1 and CS-KI-2 and their nonfunctional chemical analogs CS-KI-1 A and CS-KI-2A, we identified MTOR- and PDGFRA-independent kinase targets of these compounds: CSNK1G1 for CS-KI-1 and MAPK11 for CS-KI-2. The inventors then showed that inhibitors of casein kinase 1 (CSNK1G1 is a member of the casein kinase 1 family) and inhibitors of MAPK11 protect both cones and rods. CK-1 inhibition has Atorney Docket No. : 761131.152320 been identified before as a potential target to counteract neurodegeneration (Perez, D. I., Gil, C. & Martinez, A. Protein kinases CK1 and CK2 as new targets for neurodegenerative diseases. Med. Res. Rev. 31, 924-954 (2011), Catarzi, D. et al. Casein Kinase 18 Inhibitors as Promising Therapeutic Agents forNeurodegenerative Disorders. Curr. Med. Chem. 29, 4698-4737, Baier, A. & Szyszka, R. CK2 and protein kinases of the CK1 superfamily as targets for neurodegenerative disorders. Front. Mol. Biosci. 9, 916063 (2022)). Identifying casein kinase 1 and MAPK11 as elements in cone- or rod-protecting pathways could pave the way to the discovery of more potent compounds acting on the same targets, as well as to other means of interfering with these targets specifically in cones or rods.

[0283] Materials and Methods for Example 1

[0284] Generation of retinal organoids

[0285]

[0233] Retinal organoids were generated as previously described22, with the modifications given below. All experiments in this study were performed using organoids that were 30- to 32 weeks old.

[0286] Induced pluripotent stem cell culture

[0287]

[0234] Organoids were derived from the induced pluripotent stem cell line 01F49i-N-B722. The cells were cultured at 37°C and 5% CO2 in a humidified incubator, using mTesRl medium (STEMCELL Technologies, #85850) on Matrigel-coated (Corning, #356230) 6-well plates (Corning, #3516). The culture medium was replaced daily and cells were passaged weekly using 0.5 mM EDTA (Invitrogen, #15575020) in PBS without CaC12 / MgC12 applied for 3-5 min to facilitate detachment of cells as small clumps for subsequent seeding.

[0288] Embryoid body formation and culture

[0289]

[0235] Induced pluripotent stem cells were detached and a single-cell suspension was created using 0.5 mM EDTA (Invitrogen, #15575020) for 3 min, followed by a 3-min Accutase (Thermo Fisher Scientific, #00-4555-56) treatment at 37°C. Embryoid body formation took place in 256 microwell-hydrogels with -250-300 cells seeded per microwell. The hydrogels were generated using a MicroTissues 3D Petri Dish micro-mold (Sigma Aldrich, Z764000) and 2% agarose (Thermo Fisher Scientific, #R0491). Each hydrogel was cultured in a 12-well plate (Corning, #3513) in neural induction medium DMEM / F12 (GIBCO, #31331-028), 1% N2 Supplement Atorney Docket No. : 761131.152320

[0290] (GIBCO, #17502-048), 1% NEAA Solution (Sigma, #M7145) and 2 mg / mL heparin (Sigma, #H3149-50KU) for one week with daily medium exchanges. Embryoid bodies that formed in one 256 micro well-hydrogel were detached from the hydrogel and distributed evenly across three wells of a Matrigel (Corning, #356230)-coated 6-well plate (Corning, #430166).

[0291] Early organoid culture and checkerboard scraping

[0292]

[0236] Organoids in 6-well plates cultured with daily medium exchanges started to form 2D confluent structures. For the first 16 days, they were cultured in neural induction medium. The medium was subsequently changed to 3 parts DMEM (GIBCO, #10569-010): 1 part F12 medium (GIBCO, #31765-027) (‘3:1 medium’), supplemented with 2% B27 without vitamin A (GIBCO, #12587010), 1% NEAA Solution (MERCK, #M7145), and 1% penicillin / streptomycin (GIBCO, #15140-122). Checkerboard scraping was performed between days 28 and 30 of culture as described previously (Dowling, J. E. The Retina: An Approachable Part of the Brain, Revised Edition. (Belknap Press: An Imprint of Harvard University Press, Cambridge, Mass, 2012)).

[0293] 3D-organoid culture

[0294]

[0237] Aggregates from four wells of a 6-well plate were transferred to one 175 cm2 tissue culture flask (Thermo Scientific, #159926) previously treated with an anti-adherence solution (StemCell Technologies, #07010). Flasks containing organoids were filled with 35 - 45 mL of medium, which was replaced 1-3 times per week. The flasks were maintained in 3:1 medium for 6 weeks of culture. The medium was supplemented subsequently with an additional 10% FBS (Millipore, # ES-009-B) and 100 pM Taurine (Sigma, #T0625-25G) until week 10. Until week 14, the medium was further supplemented with 1 pM retinoic acid (Sigma, #R2625). After this period, the retinoic acid concentration was reduced to 0.5 pM and the B27 supplement was replaced with N2 supplement (GIBCO, #17502-048) for the remaining duration of the culture. For easy access to organoids for experiments, they were transferred to round cell culture dishes (Thermo Fischer, #101VR20). Aggregates lacking neuroepithelium were removed just before the experiments.

[0295] Organoid fixation, sectioning and staining

[0296]

[0238] Organoids were fixed in paraformaldehyde for 4 h at 4°C and washed three times for 10 min each in PBS. They were then submerged in PBS containing 30% sucrose for cryopreservation. Fixed organoids were stored at -80°C. Atorney Docket No. : 761131.152320

[0297]

[0239] For sectioning, the organoids were embedded in a solution of 7.5% gelatine and 10% sucrose in PBS. The embedded samples were then frozen and sectioned into 25-pm-thick slices using a cryostat (MICROM International, #HM560).

[0298]

[0240] Immunostaining was carried out as described previously (Dowling, J. E. The Retina: An Approachable Part of the Brain, Revised Edition. (Belknap Press: An Imprint of Harvard University Press, Cambridge, Mass, 2012)). Briefly, slides were dried for 30 min at room temperature, then rehydrated in PBS for 5-10 min. They were then blocked with a solution containing 10% normal donkey serum (Sigma, #S30-100ML), 1% BSA (Sigma, #05482-25G), 0.5% Triton X-100 (Sigma, #T9284500ML), and 0.02% sodium azide (Sigma, #S2002-25G) at room temperature for 1 h. Sections were then treated with primary antibodies (Appendix Table A-6) in a similar blocking solution but with 3% normal donkey serum for 24 h. After three washes in PBS with 0.1% TWEEN 20 (Sigma, #P9416100ML) for 10 min each, the slides were exposed to secondary antibodies (Thermo Fisher Scientific, donkey secondary antibodies conjugated to Alexa Fluor 488, 568, or 647) diluted 1 :500 and Hoechst 33342 (Thermo Fisher, #62249) diluted 1 : 10,000 in the same buffer as the primary antibodies for 2 h. This was followed by two 10-min washes in PBS with 0.1% Tween and a 15-min wash in PBS. Slides were finalized with ProLong Gold (Thermo Fisher Scientific, #P36934) before sealing.

[0299] Imaging stained cryosections

[0300]

[0241] Images of representative regions of the organoids were captured using a spinning disc confocal microscope (Olympus IXplore SpinSR). The microscope was adjusted to either 20x or 40x magnification and images were taken across multiple Z-planes. All captured images are shown as maximum intensity projections.

[0301] AA V production

[0302]

[0242] Adherent HEK293T cells (ATCC, #CRL3216) were cultured in a 5-layer CellSTACK (3,180 cm2; Corning, # CLS3319) for AAV vector production. These cells were co-transfected with an AAV transgene plasmid, an AAV helper plasmid encoding the AAV Rep2 and Cap proteins for the selected AAV9-PHP.eB capsid (Chan, K. Y. et al. Engineered AAVs for efficient noninvasive gene delivery to the central and peripheral nervous systems. Nat. Neurosci. 20, 1172-1179 (2017)), and the pHGTl-Adenol helper plasmid carrying adenoviral genes (kindly provided by C. Cepko, Harvard Medical School, Boston, USA) using PEIMAX (Polyscience, #POL24765-1). Plasmids were mixed in 98 mL DMEM (Thermo Fischer, #11965- Atorney Docket No. : 761131.152320

[0303] 092) and incubated for 5 min. PEIMAX was then added to the DMEM-diluted DNA. After an additional 10-min incubation, the DNA-PEIMAX complex was added to the cells. After 60 h, the culture medium was supplemented with 250 mL fresh DMEM containing 1% Pen-Strep (Thermo Fischer, #15140-122). AAV vectors present in cells and the culture medium were harvested approximately 5 days post-transfection.

[0304] Purification of AA Vs

[0305]

[0243] AAVs were purified either from cell culture medium alone or from both cells and cell culture medium. The cell culture supernatant was first cleared by centrifugation at 1400 x g for 15 min (5920R; Eppendorf) and then filtered through a 0.45-pm PES filter (Merck Millipore, #S2GPU02RE). The cell pellet was resuspended in 11 mL lysis buffer (150 mM NaCl, 20 mM Tris-HCl pH 8.0) and subjected to three freeze-thaw cycles. To remove cell debris, the cell lysate was centrifuged at 4,000 x g for 30 min and the resulting supernatant filtered through a 0.45-pm filter.

[0306]

[0244] Both the filtered cell culture medium and the cell lysate were treated with Turbonuclease (Accelagen, #N0103L) at 50 U / mL for 1 h at 37°C. The sample was then loaded onto an affinity column (POROS CaptureSelect AAVX; ThermoFisher, #A36652) and eluted with a solution of 0.1M glycine (Merck, #1.04201.1000), 0.25M arginine (Sigma, A5006), 0.2 M NaCl (pH 2.7; Sigma, 31434), following an extensive wash with 20 times the column volume of 500 mM NaCl, 50 mM Tris at pH 7.3 (Merck, 93350), and 0.01% Pluromc F-68 (Thermo, #24040032). The eluted AAVs were immediately neutralized with 1 / 11 volume of 1 M Tris-HCl pH 10. The purified AAV vectors were then concentrated as needed in sterile PBS + 0.001% Pluronic F-68 using a spin filter (Amicon Ultra Centrifugal Filter Units; Millipore Sigma, UFC910096; molecular cutoff 100 kDa).

[0307] AA V titration

[0308]

[0245] Encapsidated viral DNA was quantified using TaqMan RT-PCR (Thermo Fischer, #4444557) targeting the ITR sequences (forward primer; reverse primer; probe: [6F AM], see Table 7) relative to a linearized ITR-containing plasmid as a standard. Prior to quantification, AAV particles were denatured using Proteinase K (Thermo Fischer, #11501515). The titers were then calculated and expressed as genome copies per mL.

[0309] Bulk AA V transduction of organoids Atorney Docket No. : 761131.152320

[0310]

[0246] For large-scale experiments (FIG. 14, FIG. 16, FIG. 2, FIG. 4, FIG. 5, FIG. 7, FIG. 8, FIG. 10, FIG. 11, FIG. 12, and FIG. 15), organoids were transduced with AAVs in their original flask (Sigma Aldrich, #Z764000). AAVs were diluted in culture medium to a concentration of 1 x 1013to 2.5 x 1013genome copies per mL. The flasks were placed upright and the medium aspirated from the organoids. AAV solution was then added at 8 mL per flask and the flasks incubated in the upright position for 24 h. Following this, 32 mL of medium was added to each flask and the flasks were then laid flat. After a further 24 h, the medium was exchanged completely. The transduced organoids were cultured for an additional 4-5 weeks at 37°C and 5% CO2 with a medium exchanged once a week.

[0311] Low-throughput imaging

[0312]

[0247] All non-screening imaging (FIG. 1, FIGs. 9G-9I, FIG. 14, FIG. 16, and FIG. 13) was conducted using a spinning disk confocal microscope (Olympus IXplore SpinSR) with a 4x or a lOx objective. For live imaging, organoids were kept in a humidified chamber maintained at 37°C with 5% CO2. The contrast and brightness settings for images captured from the same organoid across different timepoints were the same.

[0313] Glucose starvation

[0314]

[0248] After 30 weeks of maturation and four weeks after AAV transduction, organoids were transferred into an ultra-low attachment U-bottom 96-well plate (Corning, #7007) with 150-200 pL medium. The remaining medium was then reduced to approximately 60 pL per well.

[0315]

[0249] The low glucose starvation medium was composed of 3: 1 medium supplemented with an additional 10% heat- inactivated FBS (Millipore, #es-009-b), N2 supplement (GIBCO, #17502-048), 100 pM taurine (Sigma, #T0625-25G), and 0.5 pM retinoic acid. Instead of the standard DMEM, DMEM with no glucose (Thermo Fisher, #11966025) was used. The normal glucose medium was prepared similarly but with regular DMEM containing 25 mM glucose (Thermo Fisher, #10569010). The low glucose medium still contained a small amount of glucose due to the Fl 2 medium (GIBCO, #31765-027) and possibly the FBS.

[0316]

[0250] Prior to the addition of the respective experimental conditions, organoids including the normal glucose controls were washed twice with 120 pL of low glucose medium. This process was conducted manually or, for screening experiments, with a 96-well head Selma pipettor (Cybio, #OL7001-26-212) fitted with 60-pL tips (Cybio, #OL3800-25-735-P).

[0317] Glucose consumption measurement Atorney Docket No. : 761131.152320

[0318]

[0251] Organoids were transferred to an ultra-low attachment U-bottom 96-well plate (Corning, #7007) and subjected to glucose starvation. On each measurement day, 5 pL of medium was collected from the 180 pL of medium for each of the 10 organoids per condition. For the initial measurement, which involved only medium without organoids, three replicates were taken. The glucose concentration was subsequently determined using a Glucose Colorimetric Detection Kit (Invitrogen, #EIAGLUC). The assay results were read using a Hidex Sense Microplate Reader. Compound preparation, dilution, and addition

[0319]

[0252] A set of 2,707 annotated compounds selected for screening on retinal organoids was sourced from the Mode-of-action (MO A) compound library (Canham, S. M. et al. Systematic Chemogenetic Library Assembly. Cell Chem. Biol. 27, 1124-1129 (2020)) The compounds, originally at a stock concentration of 10 mM in 100% DMSO, were plated in 384- well low dead volume plates (Labcyte, #LP-0200). Using the ECHO acoustic liquid handler (Labcyte, #Echo 555), 225 nL of the compounds was transferred into sterile 96-well polypropylene U-bottom microplates (Greiner, #65026). These plates were stored overnight at 4°C in a confined environment to prevent evaporation.

[0320]

[0253] The following day, the plates were brought to room temperature and the compounds diluted 666 times by adding 150 pL of low glucose medium with the multidrop combi dispenser (Thermo Scientific, #5840300). Using a 96-well head Selma pipettor (Cybio, #OL7001-26-212) equipped with 60-pL tips (Cybio, #OL3800-25-735-P), 120 pL of culture medium was removed from the ultra-low attachment U-bottom 96-well assay microplates (Corning, #7007) containing the organoids. Then, using the same pipettor, 120 pL of compounds diluted in medium were pipetted from the intermediate 96-well plates into the plates containing the retinal organoids. The assay plates were then incubated (5% CO2; 37°C; humidified environment) in an automated incubator (Thermo, #incubator Cytomat 10 C 450) until imaging. Each compound was tested in five replicates at a final concentration of 10 pM. All vehicle controls were 0.1 % DMSO in low glucose or normal glucose medium. In the secondary screens, the compounds were tested at four different concentrations (10; 1 ; 0.1 and 0.01 pM) using the compound transfer process as in the primary screen.

[0321]

[0254] HSP90AA1I-1, CS-KI-1 and CS-KI-1A (Fig. 4g-h, 5c-d, 6 and Supplementary Fig. 9, 12- 15) were newly synthesized by Enamine. CS-KL2 and CS-KI-2 were purchased from MolPort (FIG. 91, FIG. 14D, FIG. 16, FIG. 13, FIG. 18-FIG. 21). These were dissolved in 90% DMSO Atorney Docket No. : 761131.152320 prior to manual dilution in low glucose medium. The vehicle controls for these experiments involved 0.09% DMSO. If not indicated otherwise HSP90AA1I-1 was added at a concentration of 1 pM and CS-KI-1, CS-KL1A, CS-KI-2 and CS-KI-2A at a concentration of 10 pM. All CK- 1 and MAPK11 inhibitors were purchased from MedChemExpress or StemCell Technologies. Automated imaging

[0322]

[0255] Confocal images for all screening experiments were captured using a 4x objective lens (Olympus UPLS APO, NA=0.16) on an automated spinning disk confocal microscope equipped with a sCMOS camera (Yokogawa, CV7000). The samples were maintained in a 5% CO2 and 37°C environment during acquisition. Images were acquired at 24 different confocal planes, each separated by a 34- pm interval, to cover the entire organoid. This was followed by the acquisition of a stack of seven brightfield images at 100-pm intervals. After image acquisition, each plate was incubated (5% CO2; 37°C; humidified environment) for seven days and then re-imaged using the same procedure.

[0323] Promoter ProA330

[0324]

[0256] The general design and the testing of ProA series promoters have been described previously14. The AAV serotypes used were AAV9-PHP.eB58 for human retinal organoids and AAV8-BP281 for mouse injections.

[0325] Organoid dissociation and FACS-sorting for RNA-seq

[0326]

[0257] For bulk RNA sequencing, organoids at week 26 were co-transduced with a ProA7- GFP14construct (cone-specific promoter driving GFP expression) and ProA330-tdTomato (rodspecific promoter driving tdTomato expression). Four weeks post-transduction, organoids were subjected to their corresponding treatments (untreated, normal glucose, low glucose, and low glucose with either HSP90AA1I-1, CS-KI-1, CS-KI-1A, CS-KI-2 and CS-KI-2A) in 96-well plates. After seven days of treatment, individual organoids were dissociated using the reagents from the Neural Tissue Dissociation Kit (P) (Miltenyi Biotec, #130-092-628).

[0327]

[0258] Each organoid was transferred to a 1.5-mL Eppendorf tube, washed once with 1 mL PBS, and then with 1 mL of provided Buffer X. Subsequently, 25 pL of provided Enzyme P solution was diluted in 1 mL Buffer X and added to the organoids. Organoids were then incubated in the enzyme solution at 37°C with agitation at 900 rpm for 25 min. During this incubation period, the organoids were pipetted up and down using a 1-mL pipette every 5 min to assist dissociation. Then 5 pL of Enzyme A together with 10 pL of Buffer Y were added to the partially dissociated Atorney Docket No. : 761131.152320 organoids, followed by a 15-min incubation at 37°C without shaking. Thereafter the cells from the fully dissociated organoids were handled on ice. The dissociated cells were centrifuged at 300 x g for 5 min at 4°C to pellet the cells and remove residual enzyme solution. The cell pellet was then resuspended in 250 pL PBS and passed through a 70-pm filter (pluriSelect, 43-10070). Prior to FACS-sorting, Hoechst 33342 (Thermo Fisher, 62249) was added to the cell suspension at a 1:10,000 dilution. This was done to allow exclusion of debris from nucleated cells during FACS.

[0328]

[0259] FACS sorting was performed using a FACSAria (BD Biosciences). Up to 500 fluorescent cones and rods were sorted directly into guanidine lysis buffer (0.25 M GuHCl, 24 pM dNTPs,

[0329] 1.8 pM oligo-dT, 1.2 pM DTT, 1 M Betaine) for subsequent RNA extraction and immediately frozen at -70 °C for storage.

[0330] Bulk RNA-sequencing

[0331]

[0260] Cell lysates were processed following the bulk FLASH-seq protocol (Hahaut, V. et al. Fast and highly sensitive full-length single-cell RNA sequencing using FLASH-seq. Nat. Biotechnol. 40, 1447-1451 (2022) Hahaut, V. Bulk FLASH-Seq VI. https: / / protocols.doud / view / bulk-flash-seq-cscvwaw6

[0332] (2023)doi: 10.17504 / protocols.io.3byl4jynolo5 / vl). Briefly, RNA was converted to cDNA fragments using Superscript IV (Thermo Fisher Scientific, #18090200) and amplified with KAPA HiFi HotStart (Roche, #KK2602,). The cDNA was then cleaned using a 0.8x ratio of homebrew SeraMag beads in 18% PEG (CytiviaTm, #GE24152105050250). cDNA concentration and quality were measured using Qubit (Thermo Fisher Scientific, #Q33231) and an Agilent Bioanalyzer (Agilent, #5067-4626). The cDNA was normalized to 200 pg / pL before tagmentation using 0.2 pM of homemade Tn5. Tn5 transposase was produced by the EPFL Protein Facility (Lausanne, Switzerland). The reaction was halted with 0.2% SDS. An indexing PCR was performed to add Nextera index adapters (1 pM, Integrated DNA Technology) using KAPA HiFi reagents (Roche, #KK2102). Libraries were pooled in equal volumes and a final 0.8x cleanup performed with homebrew SeraMag beads before measuring sample concentration and quality. The library pool was normalized and sequenced on Illumina NextSeq MO flowcell (75-8-8-75) at approximately 1 million reads / sample. Basecalling and demultiplexing were performed with bcl2fastq (v2.20, Illumina Atorney Docket No. : 761131.152320

[0333] Kinase profiling

[0334]

[0261] CS-KI-1, CS-KI-1 A, CS-KI-2, and CS-KI-2A were subjected to in vitro kinase profiling against a panel of 350 human wild- type kinases. This profiling was conducted by the Reaction Biology Corporation using their PanQinase assay method, a plate-based assay that measures kinase activity through the transfer of radioactively labeled ATP onto a specific substrate. An analogues assay has been described before (Anastassiadis, T., Deacon, S. W., Devaraj an, K., Ma, H. & Peterson, J. R. Comprehensive assay of kinase catalytic activity reveals features of kinase inhibitor selectivity. Nat. BiotechnoL 29, 1039-1045 (2011)). Briefly, kinase / substrate pairs and cofactors were prepared in a specific buffer, introducing the compounds at a concentration of 10 pM, followed by the addition of a mix of ATP and 33P ATP after approximately 20 min. The reactions, maintained at 25 °C for two hours, were then applied to P81 ion exchange filter papers. Subsequent washing removed unbound phosphate, and kinase activity was quantified by comparing the activity in test samples against vehicle (DMSO) controls, adjusted for background from inactive enzyme controls. Detailed experimental conditions are provided in Appendix Table A-7.

[0335] Quantification and statistical analysis

[0336]

[0262] All quantifications, statistical analyses, and plots were executed using R, Python, ImageJ or GraphpadPrism. All illustrations were created using Adobe Illustrator, while chemical structures were rendered with ChemDraw.

[0337]

[0263] If not stated otherwise, ‘n’ always refers to the number of organoids per condition. The p- values depicted in the figures are not corrected for multiple testing If not indicated otherwise. A summary of the primary screen dataset can be found at https : / / ConeT argetedCompoundS creen. iob . ch.

[0338] Promoter specificity and efficacy analysis

[0339]

[0264] Promoter specificity and efficacy quantification was performed using ImageJ. Maximum intensity projections were calculated and cells were then manually counted using the ImageJ plugin, Cell Counter.

[0340]

[0265] For the ProA7-GFP construct (FIG. IE), five different organoids were analyzed. The specificity was determined by calculating the percentage of all GFP-positive cells that were also ARR3 -positive. Atorney Docket No. : 761131.152320

[0341]

[0266] Efficacy was determined by calculating the percentage of all ARE -positive cells that were also GFP-positive.

[0342]

[0267] For the ProA330-GFP construct (FIG. 14B), three different organoids were analyzed using the methods used for ProA7-GFP. Specificity was determined by calculating the ratio of all GFP-positive cells located in the outer nuclear layer that were not ARR3 -positive. Efficacy was determined by calculating the percentage of GFP-positive and ARR3 -negative cells among all cells of the outer nuclear layer counted by Hoechst staining. The specificity and efficacy in mice were evaluated in a similar manner, using three retinas from two mice (FIG. 15). Specificities and efficacies in the results section are displayed as mean ± sd.

[0343] Cell counting algorithms

[0344]

[0268] To assess cone survival in organoids, an algorithm was designed that locates and counts local maxima in pixel intensity values corresponding to GFP-expressing cells. Three distinct counting approaches were employed: counting was done image-by-image from a 3D confocal stack (referred to as ‘3D-additive-count’), from the entire 3D stack (referred to as ‘3D-count’), and from the maximum intensity projection of the 3D stack (referred to as ‘MIP-count’).

[0345]

[0269] Initially, Gaussian filtering was applied to each image to minimize background noise. Following this, local maxima in pixel intensity were identified within each image using the peak local max function from the Skicit-image package in Python. Any detected local maxima that fell below 1.25 times the frame's average pixel value were disregarded. This was performed in 3D for the 3D-count. These detected local maxima were then subjected to a three-step filtering process to ensure they accurately represented cone cells.

[0346]

[0270] In the first step of filtering, local maxima of low contrast were removed by applying Otsu thresholding to a local Region of Interest (ROI) around the local maximum. If active pixels were detected at the ROI edges, the window size was expanded. This iterative process continued until only inactive pixels were found at the ROI edges. Local maxima corresponding to ROIs exceeding a size of 70 x 70 pixels (113.75 x 113.75 pm) were excluded.

[0347]

[0271] The second filtering step aimed to separate objects that were closely situated. Objects with a diameter ranging from 8.1 to 65 pm and with a perimeter-to-area ratio between 4 and 6.5 were selected for a process known as binary erosion, which effectively separated such adjacent or touching objects. Atorney Docket No. : 761131.152320

[0348]

[0272] In the final filtering step, attributes like object diameter, perimeter-to-area ratio, and the contrast between object foreground and background were analyzed. Only objects with diameters between 6 and 100 pm and a perimeter-to-area ratio between 0.1 and 4 were retained. Low- contrast objects, defined as those for which the foreground was no more than 1.2 times brighter than the background, were also excluded.

[0349]

[0273] All filtering steps for the 3D-count were done in 2D on the z-plane where each local maximum was identified.

[0350]

[0274] In some experiments where noise levels were high, cell candidates where all pixels were below 150 were excluded (FIG. 1H, FIG. 2, FIGs. 9G-9I, and FIG. 23C). The cell counts obtained were normalized to the initial cell count yielding relative cone survival values.

[0351]

[0275] For counting rod photoreceptors (FIGs. 14D-14F, FIG. 23D), slight modifications were made to the parameters of the cone-counting algorithm. For rod photoreceptors, the maximum intensity projections were quantified. The image resolution was enhanced fourfold via cubic interpolation. The minimum allowable diameter for cell candidates was also reduced from 4 pm to 2 pm, and any candidates where all pixels were below an intensity of 200 were excluded.

[0352]

[0276] If not stated otherwise cone-survival was calculated using the counts from the 3D- additive- count algorithm.

[0353] Target categorization

[0354]

[0277] Categorizer software was used to categorize the targets of the MOA compound library. Target categories were assigned to their respective compounds (Na, D., Son, H. & Gsponer, J. Categorizer: a tool to categorize genes into user-defined biological groups based on semantic similarity. BMC Genomics 15, 1091 (2014)). If a compound had multiple targets, the most common category found among the targets was assigned.

[0355] Cell count thresholding

[0356]

[0278] For the primary screen, thresholds were determined after visually inspecting images with the lowest reported DO counts, ensuring the inclusion of as many data points as possible. These thresholds were set uniquely for each quantification algorithm (FIG. 4). The threshold for the secondary screens were the same as for the primary screen (FIG. 9 and FIG. 16).

[0357]

[0279] Similarly, thresholding on rod data was conducted following a visual inspection of images (FIG. 15).

[0358] Adjusted cone survival Atorney Docket No. : 761131.152320

[0359]

[0280] To compensate for the effect of initial cone counts on the survival of glucose deprivation, we calculated an adjusted version of the cone survival. For this, a linear model was fitted using the complete primary screen dataset to explain the cone survival with the logarithm of the scaled cone counts at DO. The obtained regression coefficient was then multiplied with the scaled logarithm of the DO cone counts. Subtracting this term from the original cone survival yielded the adjusted values. This was done separately for all three cone counting algorithms (FIG, 3E and FIG. 4).

[0360]

[0281] This adjustment sometimes led to values higher than 100% and very rarely to values lower than 0%.

[0361]

[0282] Since the cone-damaging secondary screen was done in normal glucose, we analyzed separately the relationship between cone survival and DO counts in a newly calculated linear model. While we found a linear model that significantly explains this relationship, it only accounted for a marginal amount of the explained variation for all three quantification algorithms (n=711, R2=0.007-0.018, p-values<0.001, FIG. 10). Therefore, we did not generate adjusted cone survival values for this dataset.

[0362]

[0283] For the cone-saving secondary screen dataset, we used the linear model originally generated from the primary screen to compute the adjusted values. This primary screen model accurately predicted the DO to cone survival relationship in the secondary screen (n=673-681, R2=0.17-0.22, p<0.001, FIG. 10).

[0363] Well position bias analysis

[0364]

[0284] To account for any potential influence on the results of well position within the 96-well plate, an analysis was performed on the mean adjusted cone survival for each well position, based on the primary screen dataset with the 3D-additive-count. This procedure assumes that most of the compounds under study do not exert a significant effect on cone survival. These mean values were then compared. If the differences between the means were found to fall within the range of the minimum standard deviation observed for the least variable well, it was determined that the well position did not have a significant impact on the outcome. Excluding the positions of the normal glucose control wells, cone survival was not influenced by any of the well positions (FIG. 4).

[0365] Analysis of primary screen data Atorney Docket No. : 761131.152320

[0366]

[0285] To compare cone survival across various compound conditions while controlling for the initial count at DO, an Analysis of Covariance (ANCOVA) was conducted. In this analysis, the dependent variable was the unadjusted cone survival, and the independent variable was the compound condition (low glucose control vs. compound 1 vs. compound 2, etc.). The raw count at DO served as the covariate in the model. P- values were calculated for a two-sided test comparing each compound to the low glucose controls. To identify significant hits from the primary screen, a statistical threshold of p<0.05 was set. The Benjamini-Hochberg correction was employed to account for multiple testing. Consequently, only compounds with an adjusted p-value less than 0.05 were considered significant. The compounds selected for secondary screening were determined based on their p-values and after visual inspection of images.

[0367] Mode of action names

[0368]

[0286] The mode of action for each compound was sourced from Canham et al.( Canham, S. M. et al. Systematic Chemogenetic Library Assembly. Cell Chem. Biol. 27, 1124-1129 (2020)). For compounds subjected to secondary screens, a concise version of their modes of action was manually generated (FIG. 6, FIG. 7, FIG. 8, FIG. 9, FIG. 10, and FIG. 11).

[0369] Clustering cone-damaging compounds from the secondary screen

[0370]

[0287] To categorize compounds from the secondary screen based on cone survivals at four different concentrations, hierarchical clustering was performed using medians of the cone survival values of all significant cone-damaging compounds. The Elbow Method was employed to identify the optimal number of clusters, involving a plot of the total within- cluster sum of squares (WSS) against the number of potential clusters. WSS values were computed for all possible solutions, ranging from 1 to 34 clusters, and an elbow in the curve was observed at four clusters. The resulting clusters were then assigned to all compounds, as depicted in FIG. 6C. One outlier was removed from cluster 3 and one from cluster 4 in FIG. 6C.

[0371] Definition of target classes

[0372]

[0288] HDAC1, HDAC2, HDAC3, HDAC4, HDAC5, HDAC6, HDAC7, HDAC8, HDAC9, HDAC10 and HDAC11 were categorized as HD AC I / IIs. SIRT1, SIRT2, SIRT3 and SIRT 6 were categorized as HDAC Ills. TUBA1A, TUBA1B, TUBA1C, TUBA3C, TUBA3D, TUBA3E, TUBA4A, TUBA8, TUBB, TUBB1, TUBB2A, TUBB2B, TUBB3, TUBB4A, TUBB4B, TUBB6, TUBB8, TUBD1, TUBG1, and TUBG2 were categorized as tubulins. These target classes were used in FIG. 6E, FIG. 6F, FIG. 7. Atorney Docket No. : 761131.152320

[0373] Analysis of the secondary screen cone-saving dataset

[0374]

[0289] In the analysis of the impact of compound targets on cone survival, targets with three or more listed compounds were initially selected (FIG. 3C). For each of these targets, the average of the median adjusted cone survival across all targeting compounds was determined. This average was then compared to a distribution generated by randomly drawing an equal number of compounds and calculating their mean of the median adjusted cone survival.

[0375]

[0290] This process of random drawing was performed 10,000 times initially to create a distribution of mean values. In the analysis of cone-saving targets, the number of these randomly generated means that were higher than the observed mean was determined (FIG. 9E and FIG.

[0376] 12). Conversely, for the cone-damaging targets, the number that were lower was determined (FIG. 6F).

[0377]

[0291] If less than 10 of the random means were found to be higher (or lower, depending on the analysis), the process was repeated with 100,000 random draws to ensure robustness. The p- value for each target was then estimated as the fraction of random means that were found to be higher (or lower) than the observed mean, plus one, divided by the total number of random draws.

[0378]

[0292] Finally, to account for multiple comparisons, these p-values were corrected using the Benjamini-Hochberg method and a significance threshold set at 0.05. However, in FIG. 6F, FIG. 12E, and FIG. 10 the unadjusted p-values are displayed.

[0379] Analysis of IC50

[0380]

[0293] IC50 values for all compounds in the library targeting HSP90AA1, HSP90AB1, MTOR, PIK3CA, PIK3CB, PIK3CD, PDGFRA, and PDGFRB, were sourced from the ChEMBL database (Mendez, D. et al. ChEMBL: towards direct deposition of bioassay data. Nucleic Acids Res. 47, D930-D940 (2019)). This dataset encompassed reported IC50s, even for compoundtarget pairs not present in the MOA library. In instances where multiple IC50 values were noted for a specific compound-target combination, the median of these values was used for subsequent analysis. Spearman correlation coefficients were determined by correlating the median-adjusted cone survival with median IC50 values.

[0381] Analysis of transcriptomes

[0382]

[0294] Sequencing reads were processed into gene counts using Snakemake (v7.21.0), a workflow management system. The workflow consisted of two main steps: read alignment and Atorney Docket No. : 761131.152320 differential gene expression analysis. Reads were aligned against the GRCh38 (Ensembl release 109) reference genome using STAR (v2.7.10b). Both the number of reads per gene (— quantMode GeneCounts) and alignments translated into transcripts coordinates (—quantMode TranscriptomeSAM) were set as outputs. The reference genome was augmented to include sequences from two transgenes (ProA7-GFP and ProA330-tdTomato) used in cell sorting. Read counts per gene and per sample were aggregated using custom Python scripts, and genes expressed in fewer than 5% of the samples were filtered out. DESeq2 (vl.38) was then employed to identify differentially expressed genes, using a log2 fold change threshold of 1 and a 5% significance level after Benjamini-Hochberg correction for multiple hypothesis testing. Principal component analysis was performed using scikit-learn (v.1.2.2) on normalized and standardized gene counts. GSEApy pre-rank was employed to perform gene set enrichment analysis using gene ontology terms (biological process, molecular function and cellular component ontologies), as well as hallmark gene sets from the Human Molecular Signatures Database (MSigDB). For this purpose, genes were ranked based on Wald test statistics provided by DESeq2. Transcripts from ribosomal-protein coding genes were excluded from this analysis, as these genes can be variable or highly expressed irrespective of the tested conditions. Data were normalized to transcript counts per 10,000 adjusted for non-overlapping exon lengths (TPlOk), where lengths were estimated using the R package GenomicFeatures (vl.50.2). Marker genes were identified based on an available adult human peripheral retina atlas (https: / / data.iob.ch), using scanpy’s rank genes groups function.

[0383] Analysis of kinase profiling

[0384]

[0295] Kinase profiling data and the main analysis were provided by Reaction Biology Corporation. Gene expression values were derived from the average gene expression in low glucose cones.

[0385] Example 2. Therapeutic Strategies

[0386]

[0296] This example outlines therapeutic approaches to interfere with and reduce the expression or action of specific genetic targets identified by our organoid compound screen. The target genes are: MAPK11, CSNK1A1, CSNK1D, CSNK1E, CSNK1G1, CSNK1G2, CSNK1G3 Atorney Docket No. : 761131.152320

[0387]

[0297] We describe general strategies to knock down or knock out these genes, which may result in increased survival of photoreceptors in degenerative diseases that cause blindness.

[0388] DNA-Level Therapy: CRISPR-Cas9 Mediated Knockout

[0389]

[0298] CRISPR-Cas9-based systems are used to cleave, edit, or silence target genes. The specificity of these systems relies on guide RNAs (gRNAs) that direct the Cas9 enzyme to specific target genes. The gRNAs can be selected from Tables 3A-3G, which are designed for MAPK11, CSNK1A1, CSNK1D, CSNK1E, CSNK1G1, CSNK1G2 or CSNK1G3, using the spCas9 enzyme and target exonic sequences of the target genes. By using cell-type-specific promoters, the CRISPR-Cas9 machinery can be expressed exclusively in desired cell types, such as rod and cone photoreceptors, leading to cell-type-specific knockouts. mRNA-Level Therapy: siRNA Mediated Knockdown

[0390]

[0299] siRNA-based systems are used to silence specific target genes through RNA interference (RNAi). The specificity of these systems relies on small interfering RNAs (siRNAs) that guide the RNA-induced silencing complex (RISC) to degrade the mRNA of the target gene. The siRNA can be selected from Tables 4A-4G, which target the coding sequences of these genes. mRNA-Level Therapy: shRNA Mediated Knockdown

[0391]

[0300] shRNA-based systems are used to silence specific target genes through RNA interference (RNAi). The specificity of these systems relies on short hairpin RNAs (shRNAs) that are processed within the cell to produce siRNAs, which guide the RNA-induced silencing complex (RISC) to degrade the mRNA of the target gene. The shRNAs can be based on the miR-155 backbone (FIGs. 25A) and can be selected from Tables 5A-5G. Here, the siRNA sequences in Tables 3A-3G (designated as “sense” in Tables 5A-5G) are paired in a short hairpin with an antisense sequence (designed “antisense” in Tables 5A-5G). Using the miR-155 backbone for the shRNAs allows for the expression of the shRNAs via a polymerase II system, enabling the use of cell-type-specific promoters for cell-type-specific shRNA expression and gene knockdown (FIG.

[0392] 25B) mRNA-Level Therapy: ASO Mediated Knockdown

[0393]

[0301] Antisense oligonucleotides (ASOs) are used to modulate target gene expression. They can work through several mechanisms: mRNA degradation, splicing modulation, translation inhibition, and microRNA inhibition. Atorney Docket No. : 761131.152320

[0394]

[0302] mRNA Degradation: ASOs bind to mRNA, recruiting RNase H to degrade the target RNA, preventing protein translation.

[0395]

[0303] Splicing Modulation: By binding to pre-mRNA, ASOs can alter splicing patterns, leading to different protein isoforms or correcting splicing errors.

[0396]

[0304] Translation Inhibition: ASOs block ribosome assembly on mRNA, hindering protein synthesis.

[0397]

[0305] MicroRNA Inhibition: ASOs bind and inhibit microRNAs, increasing the expression of miRNA-targeted mRNAs.

[0398]

[0306] Therefore, ASOs can be designed against our target genes to decrease their expression through multiple mechanisms.

[0399] Protein-Level Therapy: Small Molecules

[0400]

[0307] Small molecule inhibitors are used to inhibit the activity of MAPK11 or CK1 (e.g., CKla, CKlyl, CKly2, CKly3, CK15 and CKle).

[0401] Protein-Level Therapy: Other Molecular Binders

[0402]

[0308] Other molecular binders including protein binders such as antibodies, DARPins and nanobodies that bind MAPK11 or CK1 (e.g., CKla, CKlyl, CKly2, CKly3, CK18 and CKle) are used to inhibit the activity of, mislocated, or cause degradation by the intracellular degradation machinery of MAPK11 or CK1 (e.g., CKla, CKlyl, CKly2, CKly3, CK18 and CKle).

[0403] Therapeutic Strategies for the Treatment of Disease

[0404]

[0309] The therapeutic strategies described above are used to treat a subject with a disease associated with photoreceptor degradation or death. In embodiments the disease is selected from Cone-rod dystrophy, Rod-cone dystrophy, Macular degeneration, Geographic atrophy, AMD, Wet-AMD, Retinitis Pigmentosa, Macular dystrophy, Stargardt, Juvenile macular degeneration, Achromatopsia, Diabetic Retinopathy, Usher Syndrome, Leber Congenital Amaurosis (LCA), X- Linked Juvenile Retinoschisis, and Central areolar choroidal dystrophy. Attorney Docket No.: 761131.152320

[0405] Appendix

[0406] Table A-l. Compound summary for all significant cone-damaging compounds of the primary screen Screens Atorney Docket No.: 761131.152320 Atorney Docket No.: 761131.152320 Atorney Docket No.: 761131.152320

[0407] Attorney Docket No.: 761131.152320

[0408] Table A-2. Compound summary of all re-tested cone-damaging compounds in the secondary screen Atorney Docket No.: 761131.152320 Atorney Docket No.: 761131.152320

[0409] Attorney Docket No.: 761131.152320

[0410] Table A-3. Compound summary of all restested cone-saving compounds in the secondary screen Atorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320

[0411] Attorney Docket No.: 761131.152320

[0412] Table A-4. Kinase profiling results Atorney Docket No.: 761131.152320 Atorney Docket No.: 761131.152320 Atorney Docket No.: 761131.152320

[0413] Attorney Docket No.: 761131.152320

[0414] Table A-5. CK-1 and MAPK11 inhibitors result summary

[0415] Table A-6. Primary antibody list Atorney Docket No. : 761131.152320

[0416] Table A-7. Kinase profiling assay conditions Atorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320 Attorney Docket No.: 761131.152320

[0417] Atorney Docket No. : 761131.152320

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Claims

Atorney Docket No. : 761131.152320CLAIMS1. An inhibitor of mitogen-activated protein kinase 11 (MAPK11), an inhibitor of casein kinase 1 (CK1), or combinations thereof for use in treating a photoreceptor disease.

2. A inhibitor of mitogen-activated protein kinase 11 (MAPK11), an inhibitor of casein kinase 1 (CK1), or combinations thereof for use in inhibiting degeneration or death of photoreceptor cells.

3. The inhibitor of claim 1 or 2, wherein the inhibitor of MAPK11 inhibits the activity, expression, or activity and expression of MAPK11 and the inhibitor of CK1 inhibits the activity, expression, or activity and expression of CK1.

4. The inhibitor of claim 3, wherein the inhibitor of MAPK11 directly inhibits kinase activity of MAPK11.

5. The inhibitor of claim 4, wherein the inhibitor of MAPK11 is a small molecule that directly inhibits the kinase activity of MAPK11.

6. The inhibitor of claim 3, wherein the inhibitor of MAPK11 is a protein binder that directly inhibits kinase activity of MAPK11.

8. The inhibitor of claim 6, wherein the protein binder is an antibody or antigen-binding fragment of an antibody that binds MAPK11 or a non-immunoglobulin scaffold that binds MAPK11.

9. The inhibitor of claim 3, wherein the inhibitor of MAPK11 is a compound that targets MAPK1 1 for degradation.

10. The inhibitor of claim 3, wherein the inhibitor of MAPK11 is a compound that alters, silences, attenuates, or knocks out expression of MAPK11.Atorney Docket No. : 761131.15232011. The inhibitor of claim 10, wherein the inhibitor of MAPK11 comprises a nucleic acid editor that alters to MAPK11 gene to reduce or prevent its expression.

12. The inhibitor of 11, wherein the nucleic acid editor comprises a guide RNA (gRNA) selected from those disclosed in Table 3A.

13. The inhibitor of claim 10, wherein the inhibitor of MAPK11 comprises an siRNA or shRNA that comprises a sequence complementary to (e.g., targets) a sequence in mRNA encoding MAPK11.

14. The inhibitor of claim 13, wherein the inhibitor of MAPK11 comprises an siRNA.

15. The inhibitor of claim 14, wherein the siRNA comprises a nucleotide sequences selected from those disclosed in Table 4A.

16. The inhibitor of claim 13, wherein the inhibitor of MAPK11 comprises an shRNA.

17. The inhibitor of claim 16, wherein the shRNA comprises sense and antisense nucleotide sequences selected from those disclosed in Table 5A.

18. The inhibitor of claim 13, wherein the inhibitor of MAPK11 comprises an antisense oligonucleotide (ASO) that comprises a sequence complementary to (e.g., targets) a sequence in an RNA molecule (e.g., mRNA, pre-mRNA) that codes for MAPK11.

19. The inhibitor of claim 14, wherein the ASO comprises a nucleotide sequences selected from those disclosed in Table 6A.

20. The inhibitor of claim 3, wherein the inhibitor of CK1 directly inhibits kinase activity ofAtorney Docket No. : 761131.15232021. The inhibitor of claim 20, wherein the inhibitor of CK1 is a small molecule that directly inhibits the kinase activity of CK1.

22. The inhibitor of claim 3, wherein the inhibitor of CK1 is a protein binder that directly inhibits kinase activity of CK1.

23. The inhibitor of claim 22, wherein the protein binder is an antibody or antigen-binding fragment of an antibody that binds CK1 or a non-immunoglobulin scaffold that binds CK1.

24. The inhibitor of claim 3, wherein the inhibitor of CK1 is a compound that targets CK1 for degradation.

25. The inhibitor of claim 3, wherein the inhibitor of CK1 is a compound that alters, silences, attenuates, or knocks out expression of CK1.

26. The inhibitor of claim 25, wherein the inhibitor of CK1 comprises a nucleic acid editor that alters to CK1 gene to reduce or prevent its expression.

27. The inhibitor of 26, wherein the gene editor comprises a guide RNA (gRNA) selected from those disclosed in Tables 3B-3G.

28. The inhibitor of claim 25, wherein the inhibitor of CK1 comprises an siRNA or shRNA that comprises a sequence complementary to (e.g., targets) a sequence in mRNA encoding CK1.

29. The inhibitor of claim 28, wherein the inhibitor of CK1 comprises an siRNA.

30. The inhibitor of claim 29, wherein the siRNA comprises nucleotide sequences selected from those disclosed in Tables 4B-4G.

31. The inhibitor of claim 28, wherein the inhibitor of CK11 comprises an shRNA.Atorney Docket No. : 761131.15232032. The inhibitor of claim 31, wherein the shRNA comprises sense and antisense nucleotide sequences selected from those disclosed in Tables 5B-5G.

33. The inhibitor of claim 25, wherein the inhibitor of CK1 comprises an antisense oligonucleotide (ASO) that that comprises a sequence complementary to (e.g., targets) a sequence in an RNA molecule (e.g., mRNA, pre-mRNA) that codes for CK1.

34. The inhibitor of claim 33, wherein the ASO comprises a nucleotide sequences selected from those disclosed in Tables 6B-6G.

35. The inhibitor of any one of the preceding claims wherein the inhibitor of CK1 is an inhibitor of CK1 alpha, CK1 delta, CK1 epsilon, CKlgammal, CKlgamma2, CKlgamma3 or any combination of the foregoing.

36. The inhibitor of any one of claims 1-35, wherein the photoreceptor is a cone photoreceptor, rod photoreceptor or combination thereof.

37. The inhibitor of any one of claims 1 or 3-36 wherein the photoreceptor disease is conerod dystrophy, rod-cone dystrophy, macular degeneration, geographic atrophy, age-related macular degeneration (AMD), wet-AMD, retinitis pigmentosa, macular dystrophy, Stargardt disease juvenile macular degeneration, achromatopsia, diabetic retinopathy, Usher syndrome, Leber congenital amaurosis (LCA), X-linked juvenile retinoschisis, or central areolar choroidal dystrophy.

38. The inhibitor of any one of claims 2-36 wherein the subject in need thereof has cone-rod dystrophy, rod-cone dystrophy, macular degeneration, geographic atrophy, age-related macular degeneration (AMD), wet-AMD, retinitis pigmentosa, macular dystrophy, Stargardt disease, juvenile macular degeneration, achromatopsia, diabetic retinopathy, Usher syndrome, Leber congenital amaurosis (LCA), X-linked juvenile retinoschisis, or central areolar choroidal dystrophy.Atorney Docket No. : 761131.15232039. A method of treating a photoreceptor disease, comprising administering to a subject in need thereof a therapeutically effective amount of an inhibitor of mitogen-activated protein kinase 11 (MAPK11), an inhibitor of casein kinase 1 (CK1), or combinations thereof.

40. A method of inhibiting degeneration or death of photoreceptor cells, comprising administering to a subject in need thereof a therapeutically effective amount of an inhibitor of mitogen-activated protein kinase 11 (MAPK11), an inhibitor of casein kinase 1 (CK1), or combinations thereof.

41. The method of claim 39 or 40, wherein the inhibitor of MAPK11 inhibits the activity, expression, or activity and expression of MAPK11 and the inhibitor of CK1 inhibits the activity, expression, or activity and expression of CK1.

42. The method of claim 41, wherein the inhibitor of MAPK11 directly inhibits kinase activity of MAPK11.

43. The method of claim 42, wherein the inhibitor of MAPK11 is a small molecule that directly inhibits the kinase activity of MAPK11.

44. The method of claim 41, wherein the inhibitor of MAPK11 is a protein binder that directly inhibits kinase activity of MAPK11.

45. The method of claim 44, wherein the protein binder is an antibody or antigen-binding fragment of an antibody that binds MAPK11 or a non-immunoglobulin scaffold that binds MAPK11.

46. The method of claim 41, wherein the inhibitor of MAPK11 is a compound that targets MAPK1 1 for degradation.Atorney Docket No. : 761131.15232047. The method of claim 41, wherein the inhibitor of MAPK11 is a compound that alters, silences, attenuates, or knocks out expression of MAPK11.

48. The method of claim 47, wherein the inhibitor of MAPK11 comprises a nucleic acid editor that alters to MAPK11 gene to reduce or prevent its expression.

49. The method of 48, wherein the nucleic acid editor comprises a guide RNA (gRNA) selected from those disclosed in Table 3A.

50. The method of claim 48, wherein the inhibitor of MAPK11 comprises an siRNA or shRNA that comprises a sequence complementary to (e.g., targets) a sequence in mRNA encoding MAPK11.

51. The method of claim 50, wherein the inhibitor of MAPK11 comprises an siRNA.

52. The method of claim 50, wherein the siRNA comprises a nucleotide sequences selected from those disclosed in Table 4A.

53. The method of claim 50, wherein the inhibitor of MAPK11 comprises an shRNA.

54. The method of claim 53, wherein the shRNA comprises sense and antisense nucleotide sequences selected from those disclosed in Table 5A.

55. The method of claim 50, wherein the inhibitor of MAPK11 comprises an antisense oligonucleotide (ASO) that comprises a sequence complementary to (e.g., targets) a sequence in an RNA molecule (e.g., mRNA, pre-mRNA) that codes for MAPK11.

56. The method of claim 51, wherein the ASO comprises a nucleotide sequences selected from those disclosed in Table 6A.Atorney Docket No. : 761131.15232057. The method of claim 41, wherein the inhibitor of CK1 directly inhibits kinase activity of CK1.

58. The method of claim 57, wherein the inhibitor of CK1 is a small molecule that directly inhibits the kinase activity of CK1.

59. The method of claim 41, wherein the inhibitor of CK1 is a protein binder that directly inhibits kinase activity of CK1.

60. The method of claim 59, wherein the protein binder is an antibody or antigen-binding fragment of an antibody that binds CK1 or a non-immunoglobulin scaffold that binds CK1.

61. The method of claim 41, wherein the inhibitor of CK1 is a compound that targets CK1 for degradation.

62. The method of claim 41, wherein the inhibitor of CK1 is a compound that alters, silences, attenuates, or knocks out expression of CK1.

63. The method of claim 62, wherein the inhibitor of CK1 comprises a nucleic acid editor that alters to CK1 gene to reduce or prevent its expression.

64. The method of 63, wherein the gene editor comprises a guide RNA (gRNA) selected from those disclosed in Tables 3B-3G.

65. The method of claim 62, wherein the inhibitor of CK1 comprises an siRNA or shRNA that comprises a sequence complementary to (e.g., targets) a sequence in mRNA encoding CK1.

66. The method of claim 65, wherein the inhibitor of CK1 comprises an siRNA.

67. The method of claim 66, wherein the siRNA comprises nucleotide sequences selected from those disclosed in Tables 4B-4G.Atorney Docket No. : 761131.15232068. The method of claim 65, wherein the inhibitor of CK11 comprises an shRNA.

69. The method of claim 68, wherein the shRNA comprises sense and antisense nucleotide sequences selected from those disclosed in Tables 5B-5G.

70. The method of claim 62, wherein the inhibitor of CK1 comprises an antisense oligonucleotide (ASO) that that comprises a sequence complementary to (e.g., targets) a sequence in an RNA molecule (e.g., mRNA, pre-mRNA) that codes for CK1.

71. The method of claim 70, wherein the ASO comprises a nucleotide sequences selected from those disclosed in Tables 6B-6G.

72. The method of any one of the preceding claims wherein the inhibitor of CK1 is an inhibitor of CK1 alpha, CK1 delta, CK1 epsilon, CKlgammal, CKlgamma2, CKlgamma3 or any combination of the foregoing.

73. The method of any one of claims 39-72, wherein the photoreceptor is a cone photoreceptor, rod photoreceptor or combination thereof.

74. The method of any one of claims 39 or 41-73 wherein the photoreceptor disease is conerod dystrophy, rod-cone dystrophy, macular degeneration, geographic atrophy, age-related macular degeneration (AMD), wet-AMD, retinitis pigmentosa, macular dystrophy, Stargardt disease juvenile macular degeneration, achromatopsia, diabetic retinopathy, Usher syndrome, Leber congenital amaurosis (LCA), X-linked juvenile retinoschisis, or central areolar choroidal dystrophy.

75. The method of any one of claims 40-73 wherein the subject in need thereof has cone- rod dystrophy, rod-cone dystrophy, macular degeneration, geographic atrophy, age-related macular degeneration (AMD), wet-AMD, retinitis pigmentosa, macular dystrophy, Stargardt disease, juvenile macular degeneration, achromatopsia, diabetic retinopathy, Usher syndrome, LeberAtorney Docket No. : 761131.152320 congenital amaurosis (LCA), X-linked juvenile retinoschisis, or central areolar choroidal dystrophy.