Methods for preparing aptamers for small molecules

Abstract

The present disclosure provides, inter alia, novel functional group-directed methods for preparing aptamers for small molecules, such as those that cannot be obtained using standard protocols. Also provided are aptamers identified and prepared using the methods disclosed herein, compositions containing such aptamers, and methods and kits for treating conditions using the aptamers and / or compositions disclosed herein. One embodiment of the present disclosure is a method for preparing an aptamer for a target molecule.

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims the benefit of U.S. Provisional Patent Application No. 63 / 490,967, filed March 17, 2023, and U.S. Provisional Patent Application No. 63 / 492,958, filed March 29, 2023, which applications are incorporated by reference herein in their entireties.

[0002] Disclosure Areas The present disclosure provides, among other things, novel functional group-directed methods for preparing aptamers for small molecules, such as those not obtainable by standard protocols.

[0003] Government funding This invention was made with government support under grants HDTRA1-16-1-0053 awarded by the Defense Threat Reduction Agency, DK126739, GM138843, and DA045550 awarded by the National Institutes of Health, and 1518715 and 1763632 awarded by the National Science Foundation. The government has certain rights in this invention.

[0004] Incorporation by reference of sequence listing This application contains references to amino acid and / or nucleic acid sequences that have been submitted contemporaneously herewith as a Sequence Listing XML file "CU23271-PCT-seq.xml," created on March 14, 2024, with a file size of 147,925 bytes. The foregoing Sequence Listing is incorporated herein by reference in its entirety pursuant to 37 C.F.R. § 1.52(e)(5). [Background technology]

[0005] Background of the Disclosure Aptamers are oligonucleotide-based receptors isolated from random libraries by cycles of target affinity-based enrichment combined with amplification (1-4). Aptamers can be selected against a variety of small molecules that antibodies cannot select for, i.e., targets that are not recognized by the immune system even when conjugated to carrier proteins, such as neurotransmitters (5) and amino acids (6, 7). Once available, aptamers can be easily engineered into a variety of sensor formats (3, 4), including use as fluorescent (8), electrochemical (9), or electronic biosensors (10).

[0006] One of the major barriers to the widespread application of aptamers in biosensing is the lack of aptamers with adequate affinity for many important low-molecular-weight targets. (3, 4) For example, there are currently no isolated DNA aptamers for two clinically important molecules: the amino acid leucine and the antifungal drug voriconazole. The present disclosure aims to meet these and other needs. Summary of the Invention [Means for solving the problem]

[0007] Summary of the Disclosure Aptamer receptors are important biosensor components, but our ability to identify them depends on the target structure. This disclosure analyzed the contribution of individual functional groups on small molecules to binding within 27 target-aptamer pairs and identified potential obstacles to receptor isolation, such as negative cooperativity between sterically hindered functional groups. To increase the probability of isolating aptamers for important targets such as leucine and voriconazole, for which multiple previous selection attempts have failed, this disclosure designed a specialized strategy focused on overcoming individual structural barriers to successful selection. This approach allows us to go beyond standardized protocols and conduct functional group-guided searches that rely on sequences common to receptors for targets and their analogs to serve as anchors within a broad range of oligonucleotide space where useful reagents may be found.

[0008] By identifying specific structural factors that contributed to selection failure, the present disclosure provides a functional group-guided approach to isolating previously unattainable aptamers. Each target that cannot be adequately addressed by standard selection protocols can now be considered a candidate for functional group-guided approaches. Individual steps developed in this disclosure include insertion reselection, partial motif carryover and immobilization, the use of metal complexes as "protecting" groups, placeholders, and crosslinkers, and the synthesis of simpler analogs designed to overcome steric hindrance. The novel approach disclosed herein can further be combined with traditional protocols, organic receptor cofactors, and modified bases, taking library design into account, enabling the isolation of high-quality aptamers and the engineering of biosensors for previously inaccessible targets.

[0009] Thus, one embodiment of the present disclosure is a method for preparing an aptamer to a target molecule. The method comprises the steps of (a) screening and selecting candidate aptamers to the target molecule through a standard selection protocol; (b) selecting N 22to form a library that is used to identify sequences that recognize at least one functional group on the target molecule; (c) generating a library of random 22-mers in which the sequences identified in step (b) are positioned adjacent to the closed stem of the candidate aptamer; (d) performing functional group binding free energy analysis on the aptamers from the library generated in step (c); and (e) identifying the aptamer with the highest affinity for the target molecule.

[0010] Another embodiment of the present disclosure is an aptamer as disclosed herein, including those identified by the methods disclosed herein.

[0011] Yet another embodiment of the present disclosure is a composition, including a pharmaceutical composition, comprising one or more aptamers disclosed herein, including those identified and prepared by the methods disclosed herein.

[0012] A further embodiment of the present disclosure is a method for treating or ameliorating the effects of a condition in a subject in need thereof, comprising administering to the subject an effective amount of one or more aptamers disclosed herein, including those identified and prepared by the methods or compositions disclosed herein.

[0013] Yet another embodiment of the present disclosure is a kit for treating or ameliorating the effects of a condition in a subject in need thereof, the kit comprising an effective amount of one or more aptamers disclosed herein, including those identified and prepared by the methods disclosed herein or the compositions disclosed herein, packaged with instructions for use thereof.

[0014] To facilitate further description of embodiments of the present disclosure, the following drawings are provided to illustrate the disclosure and are not intended to limit the scope of the disclosure. [Brief explanation of the drawings]

[0015] [Figure 1-1]Figures 1A-1E show analysis of target functional group binding free energies for aptamers derived from stem-loop libraries: (Figure 1A) Using standard protocols, we were unable to isolate aptamers for leucine (1) and voriconazole (2), which share closely spaced carbons (*). (Figure 1B) Aptamer selection driven by small molecule-induced stem closure: An oligonucleotide library with a random loop (N36) is hybridized with the complement of a PCR primer (capture strand). The capture strand is tethered to a column. The column is exposed to the target solution. Sequences that bind to the target and undergo stem stabilization are released, preferentially amplified, and used in the next selection cycle. (Figure 1C) We measured apparent appKD values ​​for aptamers and calculated the free energy of displacement, ΔGD, based on a fluorescence displacement assay associated with the equilibrium between the aptamer (labeled with fluorescein, F) and the complementary oligonucleotide (labeled with the quencher dabcyl, D) used for capture during selection. The target causes a concentration-dependent increase in fluorescence at the indicated equilibrium. KX and KA are the dissociation constants for the target-aptamer complex without competitor and the aptamer-competitor complex without target. (Figure 1D) We isolated the contributions of individual functional groups by subtracting the individual ΔGD values ​​of the aptamer-target pair and corrected these values ​​to account for differences in oligonucleotide quenching. Here, two targets, methylamine (3) and phenylethylamine (4), differ by their benzyl groups. The free energy difference associated with the addition of a benzyl group is ΔΔGGBE (benzyl). The two aptamers used in this calculation are shown. (Figure 1E) Cooperativity is assessed by double functional group displacement cycles. (18) Values ​​of appKD and ΔGD (normalized to the average effect of the oligonucleotides on the equilibrium, in kJ / mol) are shown next to the target, and ΔΔGGBE values ​​are shown next to the fragments.ΔΔGGBE > 0 indicates a decrease in affinity with the addition of functional groups; the ΔGC value (+8.0 kJ / mol) represents the difference between the functional groups added separately (upper horizontal value and left vertical value) and simultaneously (diagonal line), which is interpreted as negative cooperativity when both the benzyl group and the carboxylate are present together in the molecule. [Figure 1-2] Same as above. [Figure 1-3] Same as above.

[0016] [Figure 2-1]Figures 2A-2E show the analysis of ΔGD and ΔΔGG BE from a set of 27 aptamers: (Figure 2A) An exemplary target used to characterize binding optimization to hydrophobic surfaces during selection; hydrophobic / aromatic fragments are shown as brown squares (amines) or green diamonds (amino acids). (Figure 2B) Regression analysis of target ΔGD against the number of heavy atoms (other than hydrogen) in aromatic hydrophobic fragments within the target. A regression line including methylamine and two aromatic amines (3, 4, and 8, larger brown squares) was used to estimate the contribution of hydrophobic surfaces at two aromatic amino acids (6 and 10) and a non-aromatic hydrophobic amine related to leucine (7). Data for four aptamers for 6 are shown individually. Methylene blue (9) is the target with the highest affinity for the aptamer isolated directly from the N36 library. The two amides have higher ΔGD values, the carboxylates have lower ΔGD values ​​(diamonds), and histamine (10) and serotonin (11) have ΔGD values ​​on the regression line. (Figure 2C) Additivity of ΔΔGGBE in analogous compounds (see Figures 18A-18B): Using the average ΔΔGGBE values ​​of the planar indole-methylene-containing molecule pairs and five carboxamides, we estimated the ΔG of the melatonin (13) aptamer. (Figure 2D) Distribution of ΔΔGGBE contributions of selected functional groups for the carboxylate (open diamond, we indicate the position of phenylalanine, 6), carboxamide (circle), guanidinium (triangle), and hydrophobic group (square). We show the rounded mean (line) and standard deviation in kJ / mol. (Figure 2E) Cooperativity (ΔGC) was assessed by double functional group replacement cycles (Figure 1E), and we show the groups added to the methylamine along with the carboxylate to obtain individual amino acids (Figure 17). All data points in Figures 2B-2E are the results of individual selection experiments. The uncertainty of this approach can be assessed by the four aptamers against phenylalanine in Figure 2B, 6, which were isolated in four independent selections. [Figure 2-2] Same as above. [Figure 2-3] Same as above.

[0017] [Figure 3-1]Figures 3A–3F show a multistep, functional group-guided approach to a high-affinity aptamer for leucine: (Figure 3A) Leucine was degraded into two fragments: isobutyl and 2-aminoethanoate. We designed selections to sequentially isolate aptamers that recognize one fragment and then both fragments, thereby reducing the target-associated barrier at each step and increasing the probability of finding a leucine aptamer. The complex of leucine and Cp*Rh(III), 14, as well as other amino acids for which we observed difficult aptamer cross-reactivity (15, 16), are shown. (Figure 3B) Starting with the Cp*Rh(III) aptamer, we performed random insertion of N22 to form the library used to identify iBu.1 sequences, which recognize the isobutyl group. Using the second N22 library, we focused selection pressure on the 2-aminoethanoate group to obtain the leucine aptamer. (Figure 3C) Secondary structures of the related CpLeu1.0, Leu2.1 (minimized from Leu2.0, Figure 16C), and CuLeu1.0. The inserted iBu1 motif is shown in gray in CpLeu1.0, and the carried-over section of the CpRh1.0 aptamer is shown in black. The CpLeu1.0 aptamer binds to Leu in the presence of Cp*Rh(III), while Leu2.1 binds to leucine by itself. The CuLeu1.0 aptamer binds to Leu in the presence of Cu(II) with high affinity (appKD ∼170 nM). (Figure 3D) Double functional group replacement cycle from methylamine (3) to leucine (1). (Figure 3E) Fluorescence versus target concentration in the presence of 40 μM Cu(II) for CuLeu1.0 and four branched-chain amino acids (displacement assay, see Figure 1C). (Figure 3F) Preliminary analytical evaluation of CuLeu1.0 in a pseudohuman serum sample spiked with branched-chain amino acids to mimic values ​​in patients with maple sugar urine disease (MSUD) (Figure 23A, left). Correlation is between measured values ​​of X'Le (sensor response fraction) (dilution 1:500, 100 μM Cu(II)) and the spiked value for {[Leu] + 0.57 * [allo-Ile]}.The high correlation indicates that this sensor is a suitable component of a minimally cross-reactive array for patient monitoring, although dilution may need to be adjusted depending on the targeted range. Allo-Ile is negligible at birth and during the first few days postpartum (11), and therefore we also show correlation in the same sham sample but without allo-Ile (circles). Measurements in Figures 3E and 3F are triplicate and SD is shown. [Figure 3-2] Same as above. [Figure 3-3] Same as above.

[0018] [Figure 4-1]Figures 4A-4B show the selection of voriconazole aptamers using analogs: (Figure 4A) Structures of voriconazole (2), which has three fragments (I-III), and its analog 2a, which has only two (I, II). Voriconazole has one tertiary and one quaternary sp3 carbon. The arrows indicate the perspective used to generate the Newman projections shown below. The anti (I, III) conformation is similar to the observed crystal structure (29). Voriconazole analog 2a was designed by simplifying the largest fragment (III) to reduce complexity and make it a more suitable target for selection. Here, the anti (I, II) conformation is favored and is likely to be the dominant epitope in selection. (Figure 4B) Aptamer Vor1.0 was isolated in a selection protocol using 2 and 2a in parallel. The secondary structure of Vor1.0 is shown as predicted by mFold (top) and as an alternative secondary structure (bottom), which was later confirmed to be the active sensor structure. The structural transformation allowed this aptamer to be captured on a column during the early stages of selection (i.e., the superstructure allows capture) (see Figures 27A-27B). A variant of Vor1.0, Vor1.1.4 (which could not be captured on a column and therefore was not isolated during selection), was converted into a quenching FRET sensor and responded to both 2 and 2.a. Using fluorescence, this sensor detected voriconazole concentrations as low as 3 μM; therefore, this oligonucleotide is a candidate for incorporation into an electrochemical sensor for in vivo monitoring (12). [Figure 4-2] Same as above.

[0019] [Figure 5] FIG. 5 shows a schematic diagram of the NGS sample preparation described in Example 1.

[0020] [Figure 6] FIG. 6 shows the procedure for the Thioflavin T assay described in Example 1 (left, 96 wells; right, 384 wells).

[0021] [Figure 7-1] Figure 7A shows the displacement assay described in Example 1. Figure 7B shows the results for the aptamer with fluorescein (A) and without the quencher. (Left) Receptor / sensor (R) with target (X) but without the complementary oligonucleotide (A). These data show that the target itself has only a small, almost negligible, effect on aptamer fluorescence. Results are for all targets, with the x-axis representing relative concentration from 0 to 100. (Right) The exception is methylene blue. Here, we observed significant quenching that must be considered. [Figure 7-2] Same as above.

[0022] [Figure 8] 8A-8B show the NMR analysis of analog 2a.

[0023] [Figure 9] FIG. 9 shows the HPLC chromatogram of analog 2a.

[0024] [Figure 10] FIG. 10 shows the mass spectrum of analogue 2a.

[0025] [Figure 11] FIG. 11 shows a schematic diagram of the black box approach described in Example 2.

[0026] [Figure 12] FIG. 12 shows the quenching curve of the leucine aptamer described in Example 2.

[0027] [Figure 13] FIG. 13 shows the displacement curve of the leucine aptamer described in Example 2.

[0028] [Figure 14] FIG. 14 shows how all values ​​in the displacement assay are determined.

[0029] [Figure 15] Figure 15 shows average ITC binding curves (fitted to a single site to obtain KD values) and representative heat curves (inset) for targets from three different target classes: amino acids (PHE), amines (HIS), and α-aminoamides (TYRA). The binding curve for tyrosinamide showed reproducible evidence of low- and high-affinity aptamer binding sites. Dissociation constants (KD) determined by ITC and displacement assays (using a competitive model) were similar for phenylalanine and histamine but were significantly different for tyrosinamide, likely due to poor fit when using a single-site binding model. Data used to fit the curves are means ± standard error of the mean for N=3 experiments performed on different days.

[0030] [Figure 16-1] Figure 16A shows the data format for all aptamers tested in this disclosure. Figure 16C shows how fit parameters are reported. Figure 16C shows data for all aptamers tested. Figure 16D shows further characterization of the CuLeu1.0 aptamer: (left), ThT displacement for Cu(II) alone compared to Cu(II) + Leu. The x-axis is the target, either Cu(II) alone, or Cu(II) in the presence of constant Leu (100 μM; no displacement shown), or Leu in the presence of constant Cu(II) (40 μM); (right) ThT dye displacement of Leu (only) in the absence of Cu(II). This also shows selectivity for Ile. Notably, high concentrations of Leu are required to displace ThT. [Figure 16-2] Same as above. [Figure 16-3] Same as above. [Figure 16-4] Same as above. [Figure 16-5] Same as above. [Figure 16-6] Same as above. [Figure 16-7] Same as above. [Figure 16-8] Same as above. [Figure 16-9] Same as above. [Figure 16-10] Same as above. [Figure 16-11] Same as above. [Figure 16-12] Same as above. [Figure 16-13] Same as above. [Figure 16-14] Same as above. [Figure 16-15] Same as above. [Figure 16-16] Same as above. [Figure 16-17] Same as above. [Figure 16-18] Same as above. [Figure 16-19] Same as above. [Figure 16-20] Same as above. [Figure 16-21] Same as above. [Figure 16-22] Same as above. [Figure 16-23] Same as above. [Figure 16-24] Same as above. [Figure 16-25] Same as above. [Figure 16-26] Same as above. [Figure 16-27] Same as above. [Figure 16-28] Same as above. [Figure 16-29] Same as above. [Figure 16-30] Same as above. [Figure 16-31] Same as above. [Figure 16-32] Same as above. [Figure 16-33] Same as above. [Figure 16-34] Same as above. [Figure 16-35] Same as above. [Figure 16-36] Same as above. [Figure 16-37] Same as above. [Figure 16-38] Same as above. [Figure 16-39] Same as above.

[0031] [Figure 17-1]FIG. 17 shows the aptamer*ligand pairs and group binding energies from double functional group displacement cycles. [Figure 17-2] Same as above. [Figure 17-3] Same as above. [Figure 17-4] Same as above.

[0032] [Figure 18-1] Figure 18A shows the values ​​used to demonstrate the additivity of group bond energies, and Figure 18B shows the calculation of group bond energies. [Figure 18-2] Same as above.

[0033] [Figure 19] FIG. 19 shows the selectivity of Leu2.1.

[0034] [Figure 20] Figure 20 shows that support for AAGA as a "compatible" sequence also generates aptamers related to Leu2.1, rather than insertion reselection being absolutely necessary to remove the Cu(II) binding site.

[0035] [Figure 21-1] Figure 21 shows direct selection of Leu aptamers using the Cp*Rh(III) cofactor. Results of an initial attempt to perform direct selection using only the Cp*Rh(III) complex as the cofactor. The first three related sequences were identified that responded to Leu but preferred Phe. All three were tested because the hydrophobic pocket binding to the side chain can be slightly tuned. The final sequence was isolated after counterselection with Phe; cross-reactivity persisted nonetheless. [Figure 21-2] Same as above. [Figure 21-3] Same as above. [Figure 21-4] Same as above.

[0036] [Figure 22]Figure 22 shows that the Newman projection explains specificity through a binding pocket model. The top shows the fit between the hypothetical binding pocket and the Leu side chain, while the bottom shows other amino acids. Ile exhibits steric hindrance, which prevents binding, whereas allo-Ile fits, albeit with a smaller contact area.

[0037] [Figure 23-1] Figure 23A shows the mock sample preparation (left) and sample evaluation (right) for the X'Le study. These evaluations were strictly performed as preliminary screening, with the sensor remaining from selection and no further optimization. Here, we show a typical calibration curve at a 1:500 dilution, which is optimal for the 75-600 μM range. The midpoint of the "pseudo-linear" range can be adjusted by either dilution or mutagenesis to reduce the affinity of the aptamer. For example, in cross-reactive arrays, both quenching and release can be improved by systematically tweaking the aptamer and capture oligonucleotides to increase the signal. All samples were generated in stripped plasma. Actual patient sample values ​​were provided by Karlla Brigatti and Kevin Strauss of the Clinic for Special Children, Strasburg, PA, through the MSUD Family Group, to which we also added a second set with similar values. We then generated identical samples without allo-Ile. Figure 23B shows extended measurements on sham samples: Here, we present a follow-up study, this time over two different days, of CuLeu1.0's ability to measure X'Le and Leu concentrations using sham samples with (left) and without (right) allo-Ile. We recognize that increasing the dilution ratio is beneficial to improve measurements at higher X'Le values. Logically, parallel Leu measurements fit well within the higher precision sensor range. Interestingly, even higher concentrations of Ile and Val have little effect. All measurements are in triplicate. [Figure 23-2] Same as above.

[0038] [Figure 24-1] Figure 24A shows a multi-step selection leading to the Ile aptamer. (A) An insertion library based on the CpRh 1.0 aptamer backbone uses the complex as a placeholder for 2-aminoethanoate. (B) The Ile-Cp*Rh(iii) aptamer (CpRhIle-apt) isolated using insertion reselection. (C) A re-randomized library using the Ile binding sequence to anchor our search. (D) An aptamer recognizing the Ile-Cu(ii) complex (CuIle1.1_apt) isolated from the library in (C). Figure 24B shows data for CpRhIle-apt and CuIle-apt. [Figure 24-2] Same as above. [Figure 24-3] Same as above.

[0039] [Figure 25] Figure 25 shows direct and two-step selection of Glu aptamers using the Cp*Rh(III) cofactor. On the left, we show an example of an aptamer isolated directly from the Cp*Rh(III)*Glu selection chosen for this demonstration. On the right, its analog from the two-step selection. These aptamers have significant sequence overlap in the portion that recognizes Glu only when coordinated with Cp*Rh(III). Subsequent attempts to generate Glu aptamers did not yield sequences that could be reliably identified as responding to Glu with sufficient confidence, because we were unable to exclude coordination with sodium cations. Attempts to use Cu(II) yielded only Cu(II)-sensitive receptors (scavenging Cu2+).

[0040] [Figure 26-1]Figure 26A shows the results for Cu(II)-Leu(direct selection)-aptamer 2. Cu(II)-Leu(direct)-2 is the minimized aptamer initially identified as a promising hit (sequence 02 below). We focused on sequences that represented >1% of the pool (nine met this initial criterion, see below), had a ThT substitution midpoint <20 μM, and selectivity for Ile and Phe (identified as important based on Leu2.0 cross-reactivity). Of those that bound, 01 was eliminated based on its preference for Ile, 03 was eliminated due to its lack of response to Leu, and 04 was eliminated due to cross-reactivity with Phe, and 02 was selected as a candidate for testing in clinical samples. Figure 26B shows the results of follow-up testing, showing ThT substitution. We hypothesized that methionine was an interfering substance that could lead to sensor failure in blinded testing. This finding needs to be taken into consideration when selecting the final sensor. Figure 26C shows that the same structure of Cu(II)-Leu(direct)-2 reappears in other Cu(II)-induced selections with larger libraries when counterselection with Ile is introduced. In selections using the N44 randomized region (uppercase font of the aptamer on the right), we attempted to introduce an additional structural transformation mechanism. [Figure 26-2] Same as above. [Figure 26-3] Same as above. [Figure 26-4] Same as above.

[0041] [Figure 27-1] Figure 27A shows that a particular family of voriconazole-binding three-way conjugates, despite their generality, was excluded from direct selection due to extremely poor interactions with the capture oligonucleotide, which was prevented in Vor1.0 by structural transformation. Figure 27B shows further voriconazole data. [Figure 27-2] Same as above. DETAILED DESCRIPTION OF THE INVENTION

[0042] Detailed Description of the Disclosure Previous studies have repeatedly failed to isolate DNA aptamers for two clinically important molecules: the amino acid leucine (Leu, 1) and the antifungal agent voriconazole (2) (Figure 1A). Aptamers for detecting blood leucine levels can be used to rapidly resolve false positives during newborn screening for maple syrup urine disease (MSUD) (11, 6). Furthermore, we sought to extend our success with vancomycin detection (12) and isolate receptors that could be used for voriconazole therapeutic monitoring (13). Our attempt was a variation of target-guided stem closure-based selection (Figure 1B) (14, 15). In this approach, an oligonucleotide library containing a random 36-mer region within is immobilized via a 5'-primer region that hybridizes to a tethered capture sequence. Potential aptamers hybridized on the column can be liberated by interaction with unmodified targets in solution, which can stabilize stem formation upon displacement (Figure 1B).

[0043] Because RNA aptamers had previously been isolated using leucine-tethered affinity columns, it was surprising that we had not previously been able to isolate DNA aptamers to leucine (16). Similarly, voriconazole should have been an obvious target due to its aromatic surface and heteroatoms. However, we were unable to adapt an aptamer (17) that reportedly cross-reacts with the azole class of antifungal drugs as a sensor component (8, 12), nor was we able to isolate a new specific aptamer. These two seemingly unrelated targets, with significantly different molecular weights, share a nearby pair of sterically hindered carbons (Figure 1A), which motivated us to pursue a broader understanding of the general relationship between target structure and the outcome of highly standardized selections. The goal was a generalizable approach for isolating aptamers when other standard methods failed.

[0044] Thus, one embodiment of the present disclosure is a method for preparing an aptamer to a target molecule. The method comprises the steps of (a) screening and selecting candidate aptamers to the target molecule through a standard selection protocol; (b) selecting N 22 to form a library that is used to identify sequences that recognize at least one functional group on the target molecule; (c) generating a library of random 22-mers in which the sequences identified in step (b) are positioned adjacent to the closed stem of the candidate aptamer; (d) performing functional group binding free energy analysis on the aptamers from the library generated in step (c); and (e) identifying the aptamer with the highest affinity for the target molecule.

[0045] As used herein, "standard selection protocols" with respect to aptamers include, for example, those based on affinity separation of binding and non-binding oligonucleotides. In the context of small molecules, protocols often involve, for example, chemically modifying target small molecules and attaching them to a solid-state matrix.

[0046] Non-limiting exemplary target molecules include ammonia, glycinamide, methylamine, phenylethylamine, glycine, phenylalanine, methylbutylamine (1-amino-3-methylbutane hydrochloride), tryptamine, methylene blue, histamine, serotonin, tryptophan, melatonin, L-dopa (3,4-dihydroxy-L-phenylalanine), norepinephrine, epinephrine, GABA (γ-aminobutyric acid), GABA-amide (4-aminobutyric acid), glutamine, phenylalanine amide, tyrosinamide, leucine, tyrosine, tyramine, agmatine, arginine, dopamine, voriconazole, Cp * Rh(III) (pentamethylcyclopentadienyl rhodium(III) chloride), Leu-Cp *Rh(iii), and Leu-Cu(ii). In some embodiments, for example, the target molecule is leucine or voriconazole.

[0047] As used herein, an "aptamer" is a short, single-stranded sequence of artificial DNA, RNA, XNA, or peptide that binds to a specific target molecule or family of target molecules. Aptamers can replace antibodies in many biotechnology applications, such as immunoassays, including enzyme-linked immunosorbent assays (ELISAs), Western blots, immunohistochemistry (IHC), and flow cytometry. Aptamers can also be used as therapeutic agents, functioning as agonists or antagonists of their ligands. The ability of aptamers to reversibly bind to molecules such as proteins makes them useful in drug delivery systems and the controlled release of therapeutic biomolecules.

[0048] Another embodiment of the present disclosure is an aptamer disclosed herein, including those identified by the methods disclosed herein. In some embodiments, the aptamer has one of the following structures: [ka] [ka] [ka] [ka] [ka] [ka] [ka] [ka] [ka] [ka] [ka] [ka] [ka]

[0049] Yet another embodiment of the present disclosure is a composition, including a pharmaceutical composition, comprising one or more aptamers disclosed herein, including those identified and prepared by the methods disclosed herein.

[0050] A further embodiment of the present disclosure is a method for treating or ameliorating the effects of a condition in a subject in need thereof, comprising administering to the subject an effective amount of one or more aptamers disclosed herein, including those identified and prepared by the methods or compositions disclosed herein.

[0051] Yet another embodiment of the present disclosure is a kit for treating or ameliorating the effects of a condition in a subject in need thereof, the kit comprising an effective amount of one or more aptamers disclosed herein, including those identified and prepared by the methods disclosed herein or the compositions disclosed herein, packaged with instructions for use thereof.

[0052] The kit may also include suitable storage containers, e.g., ampoules, vials, tubes, etc., for each compound of the present disclosure (which may, for example, be in the form of a pharmaceutical composition) and other reagents, e.g., buffers, balanced salt solutions, etc., for use in administering the active agent to a subject. The aptamer and / or pharmaceutical composition of the present disclosure and other reagents may be present in the kit in any convenient form, e.g., in solution or in powder form. The kit may optionally further include a packaging container having one or more compartments for containing the aptamer and / or pharmaceutical composition and other optional reagents.

[0053] As used herein, " condition " refers to the disease or disorder that is the current or potential target of aptamer as a therapeutic agent.Non-limiting examples of such conditions include age-related macular degeneration, myasthenia gravis, acute myeloid leukemia, percutaneous coronary intervention, thrombotic microangiopathy and carotid artery disease, cardiopulmonary bypass to maintain stable anticoagulation, type 2 diabetes, diabetic nephropathy, multiple myeloma and non-Hodgkin's lymphoma, chronic inflammatory disease, progressive malignant prostate disease, viral infection, lupus, migraine, epidermal hyperproliferative disease, septic shock, acute respiratory distress syndrome (ARDS) and combinations thereof.

[0054] As used herein, "treat," "treating," "treatment," and their grammatical variants refer to subjecting an individual subject to a protocol, regimen, process, or therapy that is desired to achieve a physiological response or outcome in the subject, e.g., a patient. In particular, the methods and compositions of the present disclosure can be used to delay the onset of disease symptoms, or delay the onset of a disease or condition, or prevent the progression of disease manifestation. However, because not all subjects treated can respond to a particular treatment protocol, regimen, process, or therapy, treatment does not require that each and every subject or subject group, e.g., a patient population, achieve a desired physiological response or outcome. Thus, a given subject or subject group, e.g., a patient population, may not respond to treatment or may respond poorly to treatment.

[0055] As used herein, "ameliorate," "ameliorating," and grammatical variations thereof, mean to reduce the severity of symptoms of a disease in a subject.

[0056] As used herein, a "subject" is a mammal, preferably a human. In addition to humans, categories of mammals within the scope of this disclosure include, for example, agricultural animals, veterinary animals, laboratory animals, etc. Some examples of agricultural animals include cows, pigs, horses, goats, etc. Some examples of veterinary animals include dogs, cats, etc. Some examples of laboratory animals include primates, rats, mice, rabbits, guinea pigs, etc.

[0057] In the present disclosure, an "effective amount" or "therapeutically effective amount" of an aptamer or pharmaceutical composition is an amount of such aptamer or composition sufficient to produce the beneficial or desired results described herein when administered to a subject. Effective dosage forms, modes of administration, and dosages can be determined empirically, and making such determinations is within the skill of one in the art. It will be understood by those skilled in the art that dosages will vary depending on the route of administration, rate of excretion, duration of treatment, the identity of any other drugs administered, the age, size, and species of the subject, and similar factors well known, for example, in the fields of medicine and veterinary medicine. Generally, an appropriate dose of an aptamer or pharmaceutical composition according to the present disclosure is the amount of the compound or composition that is the lowest dose effective to produce the desired effect with no or minimal side effects. An effective dose of an aptamer or pharmaceutical composition according to the present disclosure may be administered as two, three, four, five, six, or more subdoses administered separately at appropriate intervals throughout the day.

[0058] The aptamers, compositions, or pharmaceutical compositions of the present disclosure can be administered in any desired and effective manner: as an ointment or eye drops for oral ingestion or for topical administration to the eye, or for parenteral or other administration in any suitable manner, such as intraperitoneally, subcutaneously, topically, intradermally, by inhalation, intrapulmonary, rectally, intravaginally, sublingually, intramuscularly, intravenously, intraarterially, intrathecally, or intralymphaticly. Furthermore, the aptamers, compositions, or pharmaceutical compositions of the present disclosure can be administered in combination with other treatments. The aptamers, compositions, or pharmaceutical compositions of the present disclosure can be encapsulated or otherwise protected from gastric juices or other secretions, if desired.

[0059] The compositions or pharmaceutical compositions of the present disclosure are pharmaceutically acceptable and comprise one or more active ingredients mixed with one or more pharmaceutically acceptable carriers or diluents, and optionally one or more other compounds, drugs, ingredients and / or materials. Regardless of the route of administration selected, the compounds / compositions / pharmaceutical compositions of the present disclosure are formulated into pharmaceutically acceptable dosage forms by conventional methods known to those skilled in the art. See, for example, Remington, The Science and Practice of Pharmacy (21 st Edition, Lippincott Williams and Wilkins, Philadelphia, PA. More generally, "pharmaceutically acceptable" means useful in preparing compositions that are generally safe, non-toxic, and not biologically or otherwise undesirable, and includes those acceptable for veterinary and human pharmaceutical use.

[0060] Pharmaceutically acceptable carriers or diluents are well known in the art (see, e.g., Remington, The Science and Practice of Pharmacy (21 stEdition, Lippincott Williams and Wilkins, Philadelphia, PA. and The National Formulary (American Pharmaceutical Association, Washington, DC)), sugars (e.g., lactose, sucrose, mannitol, and sorbitol), starch, cellulose preparations, calcium phosphates (e.g., dicalcium phosphate, tricalcium phosphate, and calcium hydrogen phosphate), sodium citrate, water, aqueous solutions (e.g., saline, sodium chloride injection, Ringer's injection, dextrose injection, dextrose and sodium chloride injection, lactated Ringer's injection), alcohols (e.g., ethyl alcohol, propyl alcohol, and benzyl alcohol), polyols (e.g., glycerol, Examples of suitable carriers or diluents include hydroxybenzoates (hydroxybenzoates, ...

[0061] The compositions or pharmaceutical compositions of the present disclosure may optionally contain additional components and / or materials commonly used in such compositions. These components and materials are well known in the art and include: (1) fillers or extenders, such as starch, lactose, sucrose, glucose, mannitol, and silicic acid; (2) binders, such as carboxymethylcellulose, alginate, gelatin, polyvinylpyrrolidone, hydroxypropylmethylcellulose, sucrose, and acacia; (3) humectants, such as glycerol; (4) disintegrants, such as agar-agar, calcium carbonate, potato or tapioca starch, alginic acid, certain silicates, sodium starch glycolate, cross-linked sodium carboxymethylcellulose, and sodium carbonate; and (5) solution retarders. (6) absorption enhancers, such as quaternary ammonium compounds; (7) wetting agents, such as cetyl alcohol and glycerol monostearate; (8) absorbents, such as kaolin and bentonite clay; (9) lubricants, such as talc, calcium stearate, magnesium stearate, solid polyethylene glycol, and sodium lauryl sulfate; (10) suspending agents, such as ethoxylated isostearyl alcohol, polyoxyethylene sorbitol, and sorbitan esters, microcrystalline cellulose, aluminum metahydroxide, bentonite, agar, and tragacanth; (11) buffering agents; (12) excipients, such as Lactose, milk sugar, polyethylene glycol, animal and vegetable fats, oils, waxes, paraffin, cocoa butter, starch, tragacanth, cellulose derivatives, polyethylene glycol, silicones, bentonite, silicic acid, talc, salicylates, zinc oxide, aluminum hydroxide, calcium silicate, and polyamide powders; (13) inert diluents, e.g., water or other solvents; (14) preservatives; (15) surfactants; (16) dispersing agents; (17) controlled-release or absorption retardants, e.g., hydroxypropyl methylcellulose, other polymer matrices, biodegradable polymers, liposomes, microspheres, aluminum monostearate, gelatin, and waxes;(18) Opacifiers; (19) Adjuvants; (20) Wetting agents; (21) Emulsifying and suspending agents; (22) Solubilizers and emulsifiers, such as ethyl alcohol, isopropyl alcohol, ethyl carbonate, ethyl acetate, benzyl alcohol, benzyl benzoate, propylene glycol, 1,3-butylene glycol, oils (especially cottonseed oil, peanut oil, corn oil, germ oil, olive oil, castor oil, and sesame oil), glycerol, tetrahydrofuryl alcohol, polyisoprene, methylparaben ... These include: (23) propellants, such as chlorofluorohydrocarbons and volatile unsubstituted hydrocarbons, e.g., butane and propane; (24) antioxidants; (25) agents that render the formulation isotonic with the blood of the intended recipient, e.g., sugars and sodium chloride; (26) thickening agents; (27) coating materials, e.g., lecithin; and (28) sweeteners, flavorings, coloring agents, perfumes, and preservatives. Each such ingredient or material must be "acceptable" in the sense of being compatible with the other ingredients of the formulation and not toxic to the subject. Suitable ingredients and materials for a selected dosage form and intended route of administration are well known in the art, and acceptable ingredients and materials for a selected dosage form and method of administration can be determined using ordinary skill in the art.

[0062] The formulations may be presented in unit-dose or multi-dose sealed containers, for example, ampoules and vials, and may be stored in a freeze-dried condition requiring only the addition of a sterile liquid carrier or diluent, for example, water for injections, immediately prior to use. Extemporaneous injection solutions and suspensions may be prepared from sterile powders, granules, and tablets of the kind described above.

[0063] The following examples are provided to further illustrate the methods of the present disclosure. These examples are illustrative only and are not intended to limit the scope of the disclosure in any way. [Example]

[0064] Example 1 method general Unless otherwise noted, chemicals were purchased from Sigma-Aldrich Co. (St. Louis, MO). Oligonucleotides were ordered from Integrated DNA Technologies (Coralville, IA or Morrisville, NC) and used as received.

[0065] Selection Procedure Our general selection procedure has been previously reported. (41) All selections were performed directly or under close supervision by a single individual (KY) to maximize aptamer comparability through consistent decision-making regarding the choice of target concentration range, number of pre-washes, inclusion of counter-targets and their concentrations (if present). An example of a selection flowchart showing the decision-making at each step is shown in Nakatsuko et al., 2018 (5).

[0066] Standard desalted oligonucleotides were used for libraries and primers as listed in Table 1. HPLC purification was used for fluorophore-conjugated oligonucleotides. All oligonucleotides were dissolved in nuclease-free water and stored at -20°C. Each PCR consisted of an initial cycle at 95°C for 2 minutes, followed by N cycles of [95°C for 15 seconds, 60°C for 20 seconds, and 72°C for 30 seconds], and ended with a single cycle at 72°C for 2 minutes. PCR runs consisted of 11 ± 2 cycles. Phosphate-buffered saline (PBS), pH 7.4 (Corning, Corning, NY), containing 2 mM MgCl2 and, optionally, 5 mM KCl, was used for selection, as shown in Table 2. [Table 1-1] [Table 1-2] [Table 1-3] [Table 2-1] [Table 2-2]

[0067] A general protocol in which target concentration is decreased in successive selection steps is as follows. Semi-quantitative PCR was used to guide decision-making at each step (i.e., comparing band densities on gels). If the difference between the pre-wash in the previous selection step and the first wash in the next step remained constant and bands remained visible, the target concentration was reduced by half and selection continued. After three additional selection-amplification cycles, if there was no increase in band density between the final pre-wash and the first wash for a target, the last cycle in which a difference was observed was sequenced. The assumption was that the step contained the fraction responding to the lowest target concentration. Selection (exact conditions) varied across targets, but selection was typically stopped after less than 20 cycles.

[0068] Sequencing and sequence analysis Due to the long-term nature of this project, aptamer selection early in the study was performed in conjunction with Sanger sequencing of the resulting selection pool. Aptamer pools selected later in the study were sequenced using next-generation sequencing (NGS). At the transition, we performed both sequencing methods in parallel on one model target (tyrosine) and observed no differences in the top three aptamers identified. The sequencing methods for each target are listed in Table 2.

[0069] For Sanger sequencing, the procedure was essentially the same as described (41), with ThT substitution used to screen all sequences for target binding. For NGS sequencing, we used overlap extension PCR to increase the sequence length to >140 bp for NGS (Amplicon NGS Service, Genewiz, South Plainfield, NJ). As shown below, we constructed longer overhanging NGS primers to include the 5' end of the partial sequence of each forward / reverse primer (F / R) (Table 1). The same PCR conditions were applied to the longer primers. The extended NGS PCR products were purified using a PCR purification column (ThermoFisher Scientific, Waltham, MA). Sample concentrations were normalized according to the guidelines from the sequencing service. We ranked the sequences by the number of reads provided by Genewiz and analyzed for convergent motifs. Analysis was performed in Excel in conjunction with applicable online programs (e.g., AptaSUITE, https: / / drivenbyentropy.github.io / ). NGS sample preparation is also shown in Figure 5.

[0070] Thioflavin T dye displacement for screening aptamer-target interactions Based on the ranking by read count (high to low), we typically selected at least five sequences from each selection pool and computationally folded them into 2D structures using mFold (http: / / www.unafold.org / mfold / applications / dna-folding-form.php) (42). From the predicted 2D structure, candidate sequences were truncated to reduce the terminal stems to 5–6 base pairs. The truncated sequences were used in a thioflavin T (ThT) dye displacement assay. The length of the oligonucleotide sequences was typically 44 ± 2 nucleotides at this step. The sequences were subjected to standard desalting and purification. We used a published ThT assay procedure (43) using the buffer conditions used for selection. The ThT procedure is demonstrated in Figure 6.

[0071] The oligonucleotides were first placed in boiling water for 5 minutes, removed, and allowed to cool to room temperature. The ThT dye solution was mixed with an equal volume of the aptamer solution and incubated at room temperature for approximately 40 minutes, protected from light. During incubation, a target solution (2x aptamer concentration) was prepared and then mixed with the ThT / oligo solution and incubated for an additional 40 minutes. The final aptamer concentration was 400 nM, while the ThT dye was 4 μM. Fluorescence measurements were performed in triplicate in 96- or 384-well black plates using a FlexStation II or SpectraMax5 microplate reader (Molecular Devices, San Jose, CA). ThT fluorescence spectra were recorded at excitation wavelengths of 425 nm and emission wavelengths of 490 nm, respectively. The 50% signal maximum was used to compare relative aptamer-target affinity. From among the candidates, we selected the sequences with the highest relative target binding. If there are sequences with high counts in sequencing but little dye substitution, we order such candidates in FAM / Dab format.

[0072] Displacement assay The aptamer candidates selected by ThT screening were further characterized using a fluorescence displacement assay. Fluorescein (FAM)-conjugated aptamers were used in their precleaved form. Capture oligonucleotides were labeled with the fluorescent quencher Dabcyl (Dab). The aptamers and capture strands for each target are listed in Figure 16C. The FAM / Dab assay was performed in two steps according to the following flowchart:

[0073] The dissociation constant of the interaction between the aptamer and its capture strand was determined in the first step. This step was also used to determine the ratio of Dabcyl-labeled capture oligonucleotide to FAM-labeled aptamer used in the next step. Each capture oligonucleotide was tested in serial dilutions starting from 500 nM with 50 nM of its corresponding aptamer.

[0074] Aptamer to quenching oligonucleotide ratios that resulted in approximately 80-90% quenching were selected for competition assays with each target. Target ratios were 3x, 5x, or 10x aptamer concentration using 50 nM aptamer (see Figure 16C for ratios for specific targets). Before fluorescence determination, each FAM-labeled aptamer and the corresponding dabcyl-labeled capture strand were mixed at a predetermined ratio, placed in boiling water for 5 minutes, and allowed to cool to room temperature. Target response curves were obtained by mixing dilutions of the target solution with an equal volume of the oligonucleotide solution. The solution was incubated at room temperature in the dark for approximately 40 minutes. Samples were analyzed in triplicate in a 384-well black plate using a Victor II microplate reader (PerkinElmer, Waltham, MA) with FAM excitation / emission at 480 nm / 525 nm. Controls were performed using fluorescently labeled aptamers in the presence of their targets without quencher-labeled capture strands to determine the effect of the target on quenching. Detailed information can be found in Figures 7A-7D.

[0075] Synthesis of voriconazole analogue 2a Materials and equipment All solvents and reagents for chemical synthesis were purchased from commercial sources and used without further purification. Deuterated solvents were purchased from MilliporeSigma (St. Louis, MO). All reactions were performed under nitrogen. Thin-layer chromatography was performed on silica gel plates (fluorescent indicator UV 254 The test was carried out on a glass substrate (pre-coated with 0.25 mm thick). 1 H and 13 C-NMR spectra were recorded on a 400 MHz NMR spectrometer (Agilent Technologies, Santa Clara, CA) using CDCl as the solvent. Chemical shifts are reported in parts per million (ppm) and are referenced to the residual solvent peak ( 1 H-NMR shows 7.26 ppm of CDCl3. 13(77.2 ppm in CDCl3 for C-NMR). Abbreviations used in NMR spectra are s = singlet, d = doublet, t = triplet, and m = multiplet. Diode array detector and C 18 Low-resolution electrospray mass spectra and chromatograms were obtained using a single quadrupole liquid chromatograph mass spectrometer (LCMS-2020, Shimadzu Corporation, Kyoto, Japan) equipped with a column (SunFire, 50 mm × 2.1 mm, 5 μm, Waters Corp., Milford, MA).

[0076] Synthesis of 2-(2,4-difluorophenyl)-1-(1H-1,2,4-triazol-1-yl)propan-2-ol (analog 2a) [ka] Magnesium bromide ethyl etherate (2.80 g, 10.84 mmol, 2.4 equiv.) was added to a stirred solution of 1-(2,4-difluorophenyl)-2-(1H-1,2,4-triazol-1-yl)ethan-1-one (1.00 g, 4.48 mmol) in dichloromethane (anhydrous, 20 ml). The reaction mixture was stirred at room temperature for 1.5 hours. The mixture was then cooled in an ice / water bath, and methylmagnesium bromide solution (3 M in ether, 4.1 ml, 12.3 mmol, 2.7 equiv.) was added dropwise. The resulting mixture was allowed to warm slowly to room temperature and stirred for 3 days. The reaction was quenched with saturated ammonium chloride in water (20 ml). The product was extracted with dichloromethane (20 ml × 3). The combined organic phase was concentrated. The residue was purified by column chromatography (silica gel, CH2C2 / MeOH: 100:1 to 100:2) to give the desired product as a white solid (480 mg) (yield = 44.8%). 1H-NMR (400 MHz, CDCl3): 7.92 (1H, s), 7.84 (1H, s), 7.54-7.47 (1s, m), 6.81-6.72 (2H, m), 4.73 (1H, d, J=14.0 Hz), 4.63 (1H, br. S), 4.45 (1H, d, J=14.4 Hz), 1.58 (3H, s). 13 C-NMR (100 MHz, CDCl3): 163.61, 163.48, 161.13, 161.01, 160.03, 159.91, 157.57, 157.45, 150.92, 143.97, 128.97, 128.91, 128.88, 128.82, 126.98, 126.94, 126.85, 126.81, 111.26, 111.23, 111.05, 111.02, 104.29, 104.04, 104.03, 103.77, 72.75, 72.71, 57.95, 57.90, 25.85, 25.82. LC-MS:C 11 H 12 F2N3O[M+H] + Calculated m / z = 204.09; Found: 240.0. HPLC: C 18 Column (SunFire, 2.1 × 50 mm, 5 μm); flow rate = 0.2 mL / min; mobile phase: HO (with 0.1% formic acid / B (B = MeCN with 0.1% formic acid, B-gradient (starting from 8%, increasing to 100% in 15 min, holding at 100% for 3 min, decreasing to 5% in 2 min)); 20 min; RT = 8.14 min; 91.1% at 254 nm.

[0077] NMR analysis, HPLC chromatogram, and mass spectral data for analog 2a can be found in Figures 8-10.

[0078] Isothermal titration calorimetry The absorbance ratio of the aptamer was determined (260 nm / 280 nm < 1.8) prior to the ITC experiment to confirm DNA purity. ITC experiments were performed using a MicroCal iTC200 isothermal titration calorimeter (Malvern, Worcestershire, UK). The aptamer was first heated to 95 °C for 5 min and slowly cooled to room temperature to reduce intermolecular interactions and promote the formation of native secondary structures. The reference cell contained 1x PBS (300 μL) containing 2 mM MgCl2. The sample cell contained the aptamer (300 μL, 5 μM) in 1x PBS also containing 2 mM MgCl2. The target (50 μM) in the same buffer was titrated into the sample cell using sequential 1.5 μL injections until saturation of the thermal change was observed.

[0079] The area under the curve was integrated to calculate the enthalpy change (kcal / mol) for each target injection. The molar ratio was plotted against the enthalpy of each injection to obtain the ITC binding curve. The titration curves were fitted to a one-site binding model using Origin software. The slope of the isotherm gives the association constant. Its reciprocal is the dissociation constant, which was used to calculate ΔG: ΔG=RTln(K D )

[0080] Example 2 Rationale for displacement assays, K D Calculations and ITC Data introduction Our approach is to view aptamer selection as a black box and to select stem-loop libraries, here N 36 The solution is to use σ as a constant and thus an integral part of the black box (Figure 11). The target and its "winning" aptamer are the input and output, respectively. We ask: "Does a relationship exist between target structure and output, and if so, can this relationship be used to search for aptamers when the selection that produced the output fails or when the output is insufficient?"

[0081] For the purposes of this study, we limit ourselves to the relationship between target structure and outcome from an organic chemistry perspective. Information content, mutagenesis, N 36 Other approaches using the same set of aptamers are possible, such as focusing on the structural space of stem-loop oligonucleotides, the influence of capture sequences, selectivity, or other features of the target (e.g., the number of specific bonds or Connolly accessible surface). These approaches are interesting but beyond the current scope.

[0082] We need a parameter that can quantify the effect of controlled changes in target structure on output. This parameter has a range of three orders of magnitude (approximately 10 -8 ~10 -5 K for their targets (M) D The values ​​should be consistently applicable to a large set of aptamers and should reflect something that influences the selection, both known and unknown, while ignoring all interactions irrelevant to the selection. The parameters should be as simple as possible and calculated under the same assumptions for all aptamers (to avoid cherry-picking and various biases). Results obtained using the parameters should pass the tests described herein and be in full agreement with the chemical insights.

[0083] As has been extensively studied in a similar fashion by the Li group (14), fluorescent displacement assays using capture oligonucleotides and aptamers as obtained from selection are suitable for obtaining this parameter because this type of displacement assay directly reflects the equilibrium and selection pressures within the column affinity domain that cannot be reproduced by other methods (e.g., isothermal titration calorimetry (ITC), see below).

[0084] There are three main components in a fluorescent displacement assay: a fluorescently labeled aptamer receptor (R), a partially complementary capture oligonucleotide labeled with a quencher (A), and a target (ligand) for the aptamer (X). These components are used in the same form as those used in selection, except that R and A are labeled with a fluorescent reporter and quencher, respectively, and the assay parameter [A] is adjusted to achieve similar quenching levels across different aptamers. We investigated 27 aptamers as "data points" rather than as biosensor components that needed to be optimized (which is beyond the scope of the current study). In a biosensor, both the aptamer and the quencher can be optimized (e.g., see Figure 4D for the voriconazole aptamer).

[0085] In its simplest form, the fluorescence displacement assay considers aptamer-receptor / capture strand hybridization in the absence of target, followed by target concentration-dependent capture strand displacement. The equilibrium governing hybridization and displacement is oligonucleotide-specific. Hybridization positions the capture strand quencher (dabcyl) next to the aptamer fluorophore (fluorescein, FAM), and all secondary interactions are brought to a first-order equilibrium. [ka]

[0086] The fluorescence displacement assay consists of two experimental steps. First, we investigate the K that governs the equilibrium between R and A. A ("quenching curve"). Second, we obtain the apparent equilibrium constant K' that governs the interaction between R and X in the presence of a fixed concentration of A. X This is a "displacement assay" in which the target concentration is titrated while the concomitant increase in fluorescence is measured.

[0087] If the quenching conditions are kept relatively similar (i.e., between 80-90% of the fluorescence of R itself without A), K' X The value of (the midpoint of equilibrium, X 50% ) and the change in free energy with target addition is characteristic of the target in the context of selection. By comparing the aptamer-target free energies, we can extract the contributions of individual target functional groups. The actual K, which is the affinity normalized across interactions with the capture oligonucleotide, X To calculate the value, we choose from several models of increasing complexity.

[0088] The dissociation constant (K A ) In our assay, similar to our previously reported studies (5, 6), we obtained K A Here, we perform a four-parameter logistic (4PL) curve fit (e.g., in Quest Graph™ 4-parameter logistic (4PL) curve calculator, AAT Bioquest, Inc., January 4, 2023) to derive B max ("No quenching") is obtained. At this point, B max It is important to perform a reality check to not allow values ​​to be more than about 2% higher than the fluorescence of the aptamer alone or in the presence of the maximum target concentration.

[0089] Half maximum value of quenching, K A is half of the value of a in the presence of an infinite amount of capture oligonucleotide containing a quencher. Again, confirmation is required that the total quenching should not be less than approximately 2% of the fluorescence of the aptamer receptor alone. An example using the leucine aptamer is shown in Figure 12.

[0090] In this disclosure, we use all aptamers as selected without attempting stem or substitution optimization for analytical purposes. Because library capture is one of the evolutionary pressures applied during target-free column washes, we predict that aptamers that can bind to more than one capture strand oligonucleotide and still be released upon exposure to the target will be evolutionarily advantageous. Indeed, we observed that many of our targets interact with more than one capture oligonucleotide in solution, with Hill coefficients ranging from 0.85 to 2.66. Importantly, a number such as 1.8 does not mean we have 1.8 capture oligonucleotides; it means, for example, that two oligonucleotides mildly interfere with each other. This is neither evidence nor even a suggestion that this occurs on the column due to steric constraints on the capture oligonucleotides. A further complicating factor that makes HC interpretation difficult is that all of our values ​​are composites of microscopic constants where the aptamer and quencher are in various stages of hybridization and have different affinities.

[0091] We always perform further validation to look for large discrepancies in the fit for the region of the quenching curve between 20 and 80%. If necessary, we manually adjust the parameters to obtain a more realistic curve fit. We then calculate the K for each aptamer along with the R and A sequences. A The values ​​are shown in Figure 16C.

[0092] The apparent dissociation constant (K') for the aptamer-target interaction X ) In our assay, K' is obtained from a competition assay in which displacement of a dabcyl-labeled complementary capture oligonucleotide (A) from a fluorescein-labeled aptamer (R) is observed while titrating the target (X). X We again performed a four-parameter logistic (4PL) curve fit to derive B max("maximum release"), half-maximum release, K' X or X 50% , the minimum value (i.e., the starting point or value in the presence of infinite amounts of capture Dab / aptamer-FAM), and the Hill coefficient are obtained. The latter parameter for all aptamers in our primary set is always fitted to be between 0.85 and 1.25, treated as a 1:1 binding between X and R. At first glance, even if two target molecules bind to one aptamer molecule, one target molecule dominates in quenching (or aptamer release from the column). Notably, in PRISM, this is "log(agonist) vs. response—variable slope."

[0093] To ensure this, after determining all K'x and Kx values, we calculate the average contribution of the oligonucleotides to the free energy of displacement and correct all values ​​for that average contribution as if the assay conditions were exactly the same. While this protocol is not necessary in most situations, it can help us focus only on data that show significant differences with and without the correction. An example using the leucine aptamer is shown in Figure 13.

[0094] Allostery for modeling capture strand-aptamer-target interactions We can calculate all constants using either the competitive model (which we have used in the past) or the allosteric model (which we present here).While which model is used has no practical impact on the further use of aptamers, we provide it as a starting point for future studies.We based this analysis on Ehlert, 1987 (18), and the basic equations and terminology are as follows: [ka]

[0095] In this scheme:

[0096] K A is the dissociation constant for the interaction between a fluorescent aptamer and a complementary oligonucleotide labeled with a quencher.

[0097] K X is the dissociation constant for the interaction between the fluorescent aptamer and its target (small molecule ligand).

[0098] The value α is the number of times that the presence of A or X, respectively, x or K A (The effect is reciprocal and, by definition, cooperative.) At high concentrations, the target becomes fully competitive (i.e., the target completely displaces the quencher-labeled capture strand). In this case, the following equation reduces to a simpler form:

[0099] Ehlert derives the following equation to describe the bonding of X in the presence of A:

number

[0100] In this equation:

[0101] The value Y is the aptamer (reporter) bound to the ligand X ([Y] = [XR] + [XRA]).

[0102] K X The ' value is the apparent dissociation constant of X (i.e., estimated by the target concentration at half-maximal displacement).

[0103] R T denotes the total receptor concentration. In our case, R T is the aptamer concentration added to the solution.

[0104] We apply the proviso stated by Ehlert (p. 189): "In many cases, it is more economical to estimate the binding parameters of an unlabeled drug by measuring the binding of a fixed concentration of radioligand in the presence of various concentrations of unlabeled drug."

[0105] All K A Values ​​are in nM and all [A] T The total competitor concentrations were between 150 and 500 nM for similar quenching levels, which were fixed independently of this project, i.e., during the initial characterization of our set.

[0106] K at saturating target concentration A Obtaining the alpha coefficient from According to Ehlert, the coefficient α is estimated at the saturating concentration of X using the following formula (p. 189):

number

[0107] K' X ( app K D ) and K from α X Acquisition of Classical competitive antagonism occurs at high values ​​of α such that:

number

[0108] At lower α, we observe allosteric antagonism:

number

[0109] Our values ​​of α range from 3 to over 100. Lower values ​​of α typically result in a 2-3 fold change in calculated affinity in our case, which is negligible in the context of our limited conclusions.

[0110] If interested, modeling the next level of complexity would require using, for each aptamer, the microscopic binding constants, one or two capture strands, and one or two target molecules, as appropriate, and their individual effects on fluorescence and quenching. That level of complexity could be pursued with several aptamers by combining approaches used, for example, to generalize the Monod-Wyman-Changeux framework (45). A window into the rigorous mathematical treatment of up to three interacting molecules and the complexity that can be encountered when studying the binding equilibrium of more than two entities has been provided by Siegel and colleagues (46), but it is also possible to extend this approach to ITC experiments (see below and also (47)). However, these additional levels of complexity were deemed unlikely to be beneficial for our analysis, which requires individual, special considerations and assumptions for each aptamer.

[0111] app K D ΔG from D Calculating values ΔG Bis defined in medicinal chemistry as the energy input to a system to dissociate a ligand from its complex. ΔG is the energy released by a system when a ligand is added. D The energy has a negative value. In FIG. 1B, we accordingly use ΔG in the formula D =-RTln(1 / app K D ), which indicates ΔG D =RTln( app K D ) is the same as

[0112] This can lead to some confusion because we also define the free energy contribution of a functional group to substitution using the letter B rather than D, and these have opposite signs. This makes some of the language complicated (favorable contributions becoming negative), but regardless of this choice, it all works exactly the same as long as it is used consistently.

[0113] The present inventors have D Use the values ​​to calculate pairwise ΔG D The influence of individual target functional groups on the selection is assessed by calculating and then subtracting the K values ​​(Figure 2). Because the levels of quenching are relatively identical (i.e., the contribution from the presence of the oligonucleotide is small), we used the allosteric model to estimate K. X and then averaging them across all targets is roughly constant at 3.5 + / - 0.7 kJ / mol (see note below), we use the "as is" app K D However, in some cases, ΔΔG GBE When values ​​are close to 0 and substitution energies are close, we need to avoid overinterpreting small differences. Therefore, we set ΔG so that the contribution of each oligonucleotide is exactly 3.5 kJ / mol. DBy adjusting the value, correction is introduced, and in any case, any conclusion that depends on this change is excluded.That is, if the contribution due to the quenching level is calculated to be exactly 3.0 kJ / mol, we add 0.5 kJ / mol to this value to adjust it to 3.5 kJ / mol.This "brings" all the aspects of the competitor oligonucleotide of the assay to exactly the same level, and replaces the need to adjust all the assay conditions endlessly.Importantly, we avoid interpreting the results. Note: Correction factors and corrected ΔG D Description

[0114] appΔGD is calculated from the midpoint of the displacement assay, X50%. We assume that the contribution of the oligonucleotide is identical (i.e., the aptamer with fluorescein is quenched to the same level) for each case within a pair, although the two values ​​can be directly subtracted to obtain the functional group contribution to the binding energy. We make this assumption by using, for example, ΔG calculated through either the allosteric or competitive model. B Regarding the average (ΔG D -ΔG B ) values ​​(see Table 2). We obtain, for example, that in the allosteric model, the mean contribution of oligonucleotides is 3.5 + / - 0.7 kJ / mol, with an extreme range of 2.8 to 5.9 kJ / mol (ammonia and arginine). This cautions us not to overinterpret closely spaced data points, especially when subtracting pairs at the extremes of this distribution.

[0115] In order to minimize the influence of the heterogeneous contribution of the oligonucleotides containing Dabcyl to quenching, we adjust (add or subtract) each data point by bringing the value of each data point to the same level of 3.5 kJ / mol.As a precaution, we avoid making any statements about data points that are significantly different compared with other data points.In effect, we use this process to eliminate data points whose uncertainty affects our conclusions.For example, the impact on these data points is minimal: [Table 7]

[0116] Representative ITC experiment and some notes. When possible, isothermal titration calorimetry (ITC) is widely accepted as the gold standard for characterizing the affinity of a ligand for a receptor. D and therefore performed ITC on representative aptamer-target pairs as an additional method for determining ΔG. However, several issues complicate ITC for use with small aptamer receptors binding to small targets.

[0117] Our primary goal is to define the influence of the target and its functional groups on our ability to select aptamers, which is not the same as defining aptamer-target binding per se. The key difference lies in the additional equilibria established with the aptamer in the presence of the capture oligonucleotide, which induces new conformations for the aptamer itself and for the aptamer in the presence of the target. These additional equilibria could, in principle, be investigated by ITC by studying the binding of the capture oligonucleotide and aptamer and attempting to reproduce the selective pressure created by having all three species simultaneously present: the aptamer, the capture strand, and the target. By design, the displacement assay reproduces the capture oligonucleotide-aptamer equilibrium and the subsequent influence of the target on this equilibrium in a much more direct manner, reproducing the primary thermodynamic driving force for the release of aptamer candidates from the column in the aptamer selection process. Furthermore, the displacement assay strictly focuses the observable interactions on those that cause an increase in fluorescence, which is the result of the same chemical process that causes the aptamer to be released from the column.

[0118] To obtain measurable heat changes in ITC for small receptors and small ligands, even with microcalorimetry, we needed to use higher aptamer concentrations (50 nM in displacement assays versus 5 μM in ITC) and therefore higher target concentrations. Some of our targets have limited solubility in the selected buffer and / or aggregate. Furthermore, although we heated and cooled the aptamer solution before ITC, aptamer-aptamer interactions can still occur at the aptamer concentrations required for high signal-to-noise in isothermal calorimetric titrations. Furthermore, some targets (or target classes) show evidence of multisite binding.

[0119] On the next page, we present examples of ITC for three aptamer-target pairs representing different target classes (i.e., amines, amino acids, and α-aminoamides) where the targets were soluble and the results were reproducible (Figure 15). In the case of amides, we observed the complexification of multiple binding sites, which apparently did not affect release from the column, thus pointing to another advantage of the fluorescent displacement assay for the purposes of this study. Several other aptamer-target pairs had complexities that prevented us from obtaining clear dissociation constants and thus using ITC across the entire set to describe the influence of target functional groups on selection. Therefore, although ITC was not suitable for our purposes, it could certainly be used in the future to "shed light" on the box, in conjunction with more detailed structural studies of individual aptamers.

[0120] Example 3 Analysis of the free energy of oligonucleotide displacement across related targets We collected 27 aptamers, 23 of which were newly isolated in this study (Table 3). The novel aptamers were obtained directly from the selection without further optimization and were identified as the highest-affinity receptors targeting amines, amino acids, and their analogs. Previously, when working with individual aptamers, we focused on aptamer dissociation constants obtained by a fluorescence quenching assay, which reports the competition of a fluorescently labeled aptamer with a quencher-labeled capture oligonucleotide (Figure 1C, Tables 1 and 2; this assay is adaptable to a model of allosteric antagonism that accounts for partial release upon binding (18)). To characterize the influence of the target on the selection outcome, we instead needed to compare the target's ability to outcompete the capture oligonucleotide. Therefore, we investigated the substitution of oligonucleotide competitors used in the affinity column during selection. app K D (midpoint response or X 50% ), which is the free energy of substitution ΔG DFor example, the free energy of binding (ΔG B ), in contrast to ΔG D governs the set of global equilibria that influence the release of aptamer from the column upon target addition. ΔG D and ΔG B The difference between is mainly due to the contribution of the capture oligonucleotides present at equilibrium. [Table 3-1] [Table 3-2]

[0121] The targets (Figure 16C) and their aptamers (Figure 16C) were organized into 42 related pairs (Figure 1D), each differing by the addition or transformation of a single functional group; for example, methylamine (3) and phenylethylamine (4) differ by the addition of a seven-carbon benzyl group (Figure 1D). We calculated the ΔΔG GBE We defined ΔG as the free energy difference associated with the equilibrium positions that influences the relative outcomes of the two selections due to the presence of additional functional groups or transformations. Furthermore, we defined ΔG as the free energy difference that governs the equilibrium independent of target or capture oligonucleotide binding. D The part of the aptamer is similar across all aptamers, and they are the two ΔG D We assume that the relative ΔΔG GBE An estimate of the value can be extracted (Figure 1D). The related concept of functional group-related binding free energy contributions is often used in ligand optimization in medicinal chemistry when receptors are shared between targets (19, 20). In addition to nearly identical selection conditions, two important assumptions were required to extend the concept of functional group free energy contributions to selection:

[0122] First, there are about 10 possible 21There are random 36-mers. In the selection, we selected approximately 10 of these sequences. 14 sparse sampling allows us to treat the properties of the isolated aptamers, represented here by the "best" aptamers from each selection, as characteristics of the selection conditions, libraries, and targets. Because the selections of novel and previously identified aptamers differed only in their targets, we attributed the large variations in aptamer properties to the effects of structural differences between targets, i.e., specific functional groups.

[0123] Second, the contribution of functional groups to selection can be based solely on well-known noncovalent interactions (20, 23). Therefore, to a first approximation within a set of closely related analogs, we predict that additive effects can be isolated. We expect that systematic nonadditivity in thermodynamic cycles, e.g., cooperativity (ΔG C ) (24), we can analyze nonadditivity and generate hypotheses regarding barriers to aptamer isolation (Figure 1E). Conversely, if our assumption is correct, after initial selection failures, we can perform functional group analysis of the target to identify structural barriers that may lead to these failures and design selection protocols that improve our chances of isolating an aptamer.

[0124] We performed the following three studies using available aptamers to evaluate these hypotheses. Although each study was individually limited by small sample size, together they strongly supported our reasoning. First, we analyzed the four highest affinity aptamers for phenylalanine from four separate selections and found similar ΔG within less than 3 kJ of each other.D value (and estimated ΔG B values) were obtained (Figure 2B, Table 4). This is consistent with the affinities of the acquired aptamers, which are regularly distributed in oligonucleotide space, and thus represent reproducible characteristics of the selection. These findings support the target-related ΔG D This suggests that the large differences in should reflect differences in functional groups rather than different selection. [Table 4-1] [Table 4-2] ΔG D is X 50% It is calculated from ΔG B is K D or α K D are calculated from K A and X 50%, assuming either competition or allosteric antagonism, and identical binding sites on R for both X and A.

[0125] Second, we investigated the ΔG D We observed a correlation between the ΔG value and the number of heavy (non-hydrogen) atoms in the target's hydrophobic fragment (Figures 2A-2B). Methylene blue (9), the molecule with the largest hydrophobic surface, yielded the highest affinity of all targets. The correlation between methylamine (3) and two planar aromatic amines (4 and 8) in our set indicates that the applied selection pressure directly optimizes affinity in proportion to the hydrophobic surface, i.e., based on the functional groups present, and we found that the two ΔG D Subtracting the values ​​supports the argument that the effects of structural changes can be isolated. We note that the close proximity of methylbutylamine (7), histamine (10), and serotonin (11) to the regression line of aromatic amines (3, 4, 8) provides an indication that functional group-based optimization is common, but caution is needed not to overinterpret these results in the absence of further structural information. (24)

[0126] Third, we calculated the average ΔΔG from two planar indole-containing amines and five primary carboxamides. GBE Adding the values ​​(Figures 18A-18B), we obtain the experimentally determined ΔG for melatonin (13), a planar molecule containing an indole and a secondary carboxamide. B The values ​​were in close agreement with those of the control (Figure 2C, ΔΔG GBE Adding values ​​increases ΔG B Thus, our protocol simultaneously optimizes the presence of multiple functional groups, a property we can use to interpret deviations from additivity. Our standard selection protocol (Figure 1B) relies on target-induced oligonucleotide displacement to overcome background "noise" in the form of more common ligand-independent oligonucleotide release from the column (20, 25). Target functional group combinations that reduce the affinity of common aptamers are achieved by reducing the aptamer's target occupancy. This reduces the probability of isolating candidate aptamers in early selection steps, which is critical for successful selection.

[0127] We used the regression lines for aromatic amines (3, 4, 8) (Figure 2B) to calculate the ΔG for aptamer-target complexes of two related aromatic amino acids, phenylalanine (6) and tryptophan (12). D We estimated the effect of additional carboxylates on the ATP value and observed that the addition of a carboxyl group mimicked the loss of one to two receptor hydrophobic contacts to the heavy atom, which is intuitively consistent with introducing a polar carboxylate near a primarily hydrophobic pocket. Furthermore, our analysis of double functional group replacement cycles (Figures 1E, 2E, and 17) revealed substantial negative cooperativity while adding negative charges near mismatched groups, such as hydrophobic residues (in phenylalanine and tryptophan). These structural arrangements were then identified as likely to reduce the probability of aptamer isolation against leucine.

[0128] Example 4 Functional group-guided selection for leucine We extended our analysis to hypothesize that the two adjacent out-of-plane carbons and carboxylate, all in leucine, act synergistically to minimize the contact surface and reduce the affinity of typical aptamers, thus allowing competing ligand-independent release mechanisms to prevail and suppressing the desired outcome. To overcome this problem, we separated the selection steps for alkyl(isobutyryl) and α-amino-carboxylate groups (Figures 3A-3B). We first implemented a protocol to identify a sequence, iBu.1, that reliably contains a binding motif for the isobutyl group. We then used Cp, a Cp specifically isolated for this purpose, as a temporary placeholder for sequences interacting with the carboxyl and amino groups. * Starting with the Rh(III)-binding aptamer (CpRh1.0) (26), we inserted random 22-mer regions into CpRh1.0, representing iBu, to generate a new library (note: we can screen the complete 22-mer sequence space). From this library, we identified Cp * We selected aptamers such as CpLeu1.0 that bound to leucine in the presence of the Rh(III) cofactor. Although we could immediately exclude CpLeu1.0 from further consideration as a Leu sensor due to its complex mechanism of interaction with leucine, reflected in the sharp threshold behavior of the fluorescent sensor (see Figure 16C), we knew that the inserted sequence iBu must contain a binding motif for the Lue side chain.

[0129] Next, we designed a 22-mer library with iBu.1 positioned adjacent to the stem. From this library, we identified Leu2.1 using elution with leucine without cofactors (Figure 3C). The Leu2.1 aptamer exhibited a K of approximately 10 mM. D(Figure 16C), and had a preference for Leu over Ile of approximately 4:1 (Figure 19). Negative cooperativity (ΔG C ) is large (>10 kJ / mol), providing an explanation for the difficulty of our initial selection (Figure 3D).

[0130] We identified homologous regions I–III in CpLeu1.0 and Leu2.1, two of which, II and III, originated from the inserted random region outside of iBu.1. Short Leu2.1 aptamers should have been abundant in any initial pool; furthermore, the isolation of motifs II and III in a controlled insertion reselection study (Figure 20) indicated that motif I is not absolutely required for Leu aptamers. However, due to its seemingly low affinity, Leu2.1 required a predefined compatible sequence within I to increase the probability of isolation by reducing the required sequence length in the newly inserted random region.

[0131] The Leu2.1 aptamer had millimolar target affinity, which was insufficient for use in testing newborns with MSUD (11). Furthermore, Leu2.1 preferred phenylalanine over leucine (Figure 19), which is consistent with the Cp * This was a major problem in our previous selection, which used Rh(III) as a cofactor (Figure 21 and Table 5). [Table 5]

[0132] Therefore, we added the aminophilic cofactor Cu(II) (27) in the final step of the selection to improve affinity and selectivity. We hypothesized that Cu(II) functions as a protecting group that neutralizes the action of the carboxylate through complexation with the 2-amino-ethanoate group. Complexation allows hydrophobic DNA monomer residues better access to the leucine side chain, improving affinity and selectivity. Consistent with our hypothesis, we observed a 44-mer loop, a conserved section of iBu.1, and a high affinity (K) for leucine. D We identified the aptamer CuLeu1.0, which has a specific binding affinity of approximately 170 nM (Figure 3C).

[0133] Although CuLeu1.0 had selectivity for leucine over isoleucine, valine, and phenylalanine, we observed strong cross-reactivity with allo-isoleucine (Figure 3E, Newman projection in Figure 22). Allo-isoleucine metabolites were not used in the aptamer counterselection because their concentrations are negligible at birth. Currently, newborn screening is performed by mass spectrometry (11), which integrates isobaric species to obtain the XLe value (XLe = Leu + Ile + allo-Ile + 2OHPro). Therefore, our aptamer sensor is a candidate for the development of a rapid test to address false positives in MSUD by showing a lack of a steady increase in X'Le values ​​in consecutive measurements, where X'Le is, for example, [Leu] + 0.57. * [allo-Ile] (Figure 3F and Figures 23A-23B). However, because allo-Ile concentrations increase after a few days of age, a fully specific aptamer-free monitoring strategy requires cross-reactive arrays (26, 28), for which CuLeu1.0 is a suitable component.

[0134] A multi-step approach using Cu(II) has been shown to *This approach can be generalized to amino acids that display side chains distant from the Rh(III) complex (CuIle1.1, see Figures 24A-24B). This approach does not work for amino acids that carry chelating groups other than 2-aminoethanoate, such as glutamate (Figure 25). For comparison, we performed a single-step Leu selection with Cu(II) as a cofactor. We isolated a receptor with approximately 5-fold lower affinity than CuLeu1.0. The two most abundant sequences preferred isoleucine or methionine (Figures 26A-26C, Table 6). These aptamers are candidates for arrays. [Table 6-1] [Table 6-2]

[0135] Example 5 A structure-guided approach to aptamers for voriconazole Leucine (1) is closely related to the other amino acids in our target set. In contrast, voriconazole (2) exemplifies the application of a structure-guided approach to an unrelated molecule. We initially attributed our failure to select voriconazole to its limited solubility (approximately 200 μM). Nevertheless, selection using a soluble voriconazole phosphate analog also failed. Similar to leucine, we hypothesized that voriconazole possesses a sterically crowded environment (Figure 4A), forcing its fragments (structural subunits) to adopt a propeller-like conformation, as revealed in the crystal structure (30). This sterically crowded conformation was hypothesized to result in suboptimal access to the hydrophobic surfaces within DNA that require interactions with fragments I–III (Figure 4A). One possible retrosynthetic separation (31) afforded the simplified, less crowded, and easily synthesized alcohol analog 2a (Figure 4A).

[0136] Initial attempts, starting with 2a at a high concentration, failed, resulting in the exclusive generation of analog-binding aptamers, despite the separate introduction of voriconazole in later cycles. Further conformational analysis using Newman projection revealed that 2a likely represented the dominant epitope during selection, with fragments I and II positioned at the anti-. Conversely, for voriconazole, the structural subunit is gauche (Figure 4A). Inspired by approaches to circumvent epitope immunodominance (32), we mixed 2 and 2a at their maximum respective concentrations in the initial selection steps, and then progressively eliminated only the analog. We hypothesized that this procedure maximized the probability of liberating aptamers that bind to similar conformations of the target and its analog, which could be important in early selection rounds. In contrast to previous failures, this modification yielded two aptamers (Figures 27A-27B) that responded to 2 and 2a (Figures 4B-4C), confirming the benefit of adding the analog.

[0137] The mechanism underlying the improved selection strategy for voriconazole is partially unknown, as we cannot exclude the possibility that the analog minimizes target aggregation. Nevertheless, the presence of 2a in the early cycles likely ensures improved target-receptor occupancy and reinforces the low effective concentration of monomeric voriconazole in a conformation capable of triggering the aptamer. The isolated aptamers did not bind to fluconazole, suggesting that they are not cross-reactive aptamers across classes (28, 29, 17) and that a stabilizing interaction occurs in 2 with group III (Figure 4A).

[0138] Mutagenesis studies showed that our lead aptamer, Vor1.0, is a destabilized three-way junction (Figures 4C-4D), which we converted into the FRET sensor Vor1.1.4 (Figure 4D). The latter exhibits sufficient sensitivity for testing as an electrochemical sensor for in vivo use (12). Despite their generality, this particular family of voriconazole-binding three-way junctions was excluded from direct selection due to their extremely poor interaction with the capture oligonucleotide, which was prevented in Vor1.0 by structural transformation (Figures 4C and 27A-27B). These observations reveal a complex balance between positive and negative selection pressures in our protocol. Our new procedure, as demonstrated through the selection of leucine and voriconazole, shifts the balance of selection in our favor by addressing the stochastic barriers assigned to crowded (and other suboptimal) substructures within the target.

[0139] Example 6 conclusion In traditional organic synthesis, a schematic concept of functional groups and their reactivity guides us to transformations involving the relationship between nuclei and electron clouds. (33) Here, in structure-guided aptamer selection, a similar concept directs random exploration through the space of complementary interactions between targets and aptamer receptors. We have developed multiple approaches that can be used in functional-group-guided selection, including insertion reselection, partial motif carryover and immobilization, the expanded use of metal complexes as "protecting" groups, placeholders, and crosslinkers, and the synthesis of simpler analogs designed to overcome steric or conformational hindrances. These approaches, with consideration for library design (25), can be further explored and optimized and combined with each other and with traditional protocols (3, 4), organic receptor cofactors (6, 34), and modified bases (35), enabling the isolation of high-quality aptamers and the engineering of biosensors for previously inaccessible targets.

[0140] We have addressed three themes where our approach may provide information for further investigation. First, there is the problem of natural selection for complex functions in a hypothetical preprotein, RNA world (36). Acting as trial and error explorers (37), we repurposed simple sequence fragments to discover new functions, building on earlier work on cofactor use in RNA catalysis (38). Second, our idea of ​​uncovering selection barriers for optimal receptors can be reversed to provide insights into finding small molecule drugs that specifically modulate natural nucleic acid targets (39). And third, we provide an extensive set of sequences with confirmed target binding that can be used to refine training sets for computational design (40). References 1. AD Ellington, JW Szostak, In vitro selection of RNA molecules that bind specific ligands. Nature 346, 818-822 (1990). 2. C. Tuerk, L. 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Tejavibulya, et al., Hydrogel microfilaments toward intradermal health monitoring. iScience, 21, 328-340 (2019). 9. B. S. Ferguson, et al., Real-time, aptamer-based tracking of circulating therapeutic agents in living animals. Sci. Transl. Med. 5, 213ra165 (2013). 10. C. Zhao et al., Implantable aptamer-field-effect transistor neuroprobes for in vivo neurotransmitter monitoring. Science Advances 7:eabj7422 (2022). 11. K. Stroek, et al., Evaluation of 11 years of newborn screening for maple syrup urine disease in the Netherlands and a systematic review of the literature: Strategies for optimization. JIMDreports 54, 68-78 (2020). 12. P. Dauphin-Ducharme et al., Electrochemical aptamer-based sensors for improved therapeutic drug monitoring and high-precision, feedback-controlled drug delivery. ACS Sens. 4, 2832-2837 (2019). 13. H. Elewa, E. El-Mekaty, A. El-Bardissy, M. H. H. Ensom, K. J. Wilby, Therapeutic drug monitoring of voriconazole in the management of invasive fungal infections: A critical review, Clin. Pharmacokinet. 54, 1223-1235 (2015). 14. R. Nutiu, Y. Li, In vitro selection of structure-switching signaling aptamers. Angew. Chem. Int. Ed. 44, 1061-1065 (2005). 15. M. Rajendran, A. D. Ellington, Selection of fluorescent aptamer beacons that light up in the presence of zinc. Anal. Bioanal. Chem. 390, 1067-1075 (2008). 16. M. Yarus, Amino acids as RNA ligands: A direct-RNA-template theory for the code’s origin. J. Mol. Evol. 47, 109-117 (1998). 17. G. R. Wiedman, Y. Zhao, D. S. Perlin, A Novel, Rapid, and low-volume assay for therapeutic drug monitoring of posaconazole and other long-chain azole-class antifungal drugs. mSphere, 3, ee00623-18 (2018). 18. F. J. Ehlert, Estimation of the affinities of allosteric ligands using radioligand binding and pharmacological null methods.” Mol. Pharm. 33, 187-194 (1987). 19. S. M. Free, J. W. 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Szostak, Informational complexity and functional activity of RNA structures. J. Am. Chem. Soc. 126, 5130-5137 (2004). 26. A. Buryak, K. Severin, A chemosensor array for the colorimetric identification of 20 natural amino acids. J. Am. Chem. Soc. 127, 3700-3701 (2005). 27. Z. Liu et al., Tuning the reactivity of nitriles using Cu(II) catalysis - potentially prebiotic activation of nucleotides. Chem. Sci. 35, 7052-7057 (2018). 28. K.-A. Yang, R. Pei, D. Stefanovic, M. Stojanovic, Optimizing cross-reactivity with evolutionary search for sensors. J. Am. Chem. Soc. 134, 1642-1647, (2012). 29. W. Yang, et al., In vitro isolation of class-specific oligonucleotide-based small-molecule receptors. Nucleic Acids Res. 47, e71 (2019). 30. K. Ravikumar, B. Sridhar, K. D. Prasad, Ak. K. S. Bujanga Rao, Voriconoazole, an antifungal drug. Acta Cryst. E63, 0565-0567 (2007). 31. E. J. Corey, The Logic of Chemical Synthesis. John Wiley & Sons (1989). 32. D. Angeletti, I. Kosic, J. J. S. Santos, J. W. 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[0141] All documents cited in this application are incorporated herein by reference as if fully set forth herein.

[0142] The embodiments described in this disclosure can be combined in various ways. Any aspect or feature described with respect to one embodiment can be incorporated into any other embodiment mentioned in this disclosure. While various novel features of the principles of the present invention have been shown, described, and pointed out as applied to specific embodiments thereof, those skilled in the art will understand that various omissions, substitutions, and changes can be made without departing from the spirit of the present disclosure. Those skilled in the art will understand that the principles of the present invention can be practiced in embodiments other than those described, which are presented for purposes of illustration and not limitation.

Claims

1. 1. A method for preparing an aptamer for a target molecule, comprising: (a) screening and selecting candidate aptamers against said target molecule through standard selection protocols; (b) N ２２ modifying the candidate aptamers by having random insertions of to form a library used to identify sequences that recognize at least one functional group on the target molecule; (c) generating a library of random 22-mers in which the sequences identified in step (b) are positioned adjacent to the closed stem of the candidate aptamer; (d) performing functional group binding free energy analysis on the aptamers from the library generated in step (c); (e) identifying the aptamer with the highest affinity for the target molecule; A method comprising:

2. The target molecule may be ammonia, glycinamide, methylamine, phenylethylamine, glycine, phenylalanine, methylbutylamine (1-amino-3-methylbutane hydrochloride), tryptamine, methylene blue, histamine, serotonin, tryptophan, melatonin, L-dopa (3,4-dihydroxy-L-phenylalanine), norepinephrine, epinephrine, GABA (γ-aminobutyric acid), GABA-amide (4-aminobutyric acid), glutamine, phenylalanine amide, tyrosinamide, leucine, tyrosine, tyramine, agmatine, arginine, dopamine, voriconazole, Cp ＊ Rh(III) (pentamethylcyclopentadienyl rhodium(III) chloride), Leu-Cp ＊ 2. The method of claim 1, wherein the metal ion is selected from the group consisting of Rh(iii), and Leu-Cu(ii).

3. 2. The method of claim 1, wherein the target molecule is leucine or voriconazole.

4. The following structure: 【Chemistry 5-1】 【Chemistry 5-2】 【Chemistry 5-3】 【Chemistry 5-4】 【Transformation 5-5】 [Transformation 5-6] [Transformation 5-7] [Transformation 5-8] 【Chemistry 5-9】 【Chemistry 5-10】 【Chemistry 5-11】 【Chemistry 5-12】 【Chemistry 5-13】 An aptamer having the formula:

5. A composition comprising one or more aptamers prepared according to the method of claim 1 and a pharmaceutically acceptable carrier, adjuvant, or vehicle.

6. A composition comprising one or more aptamers of claim 4 and a pharmaceutically acceptable carrier, adjuvant, or vehicle.

7. A method for treating or ameliorating the effects of a condition in a subject in need thereof, comprising administering to the subject an effective amount of one or more aptamers prepared according to the method of claim 1, one or more aptamers described in claim 4, or a composition described in claim 5 or 6.

8. 8. The method of claim 7, wherein the condition is selected from the group consisting of age-related macular degeneration, myasthenia gravis, acute myeloid leukemia, percutaneous coronary intervention, thrombotic microangiopathy and carotid artery disease, cardiopulmonary bypass to maintain stable anticoagulation, type 2 diabetes, diabetic nephropathy, multiple myeloma and non-Hodgkin's lymphoma, chronic inflammatory diseases, progressive malignant prostate disease, viral infections, lupus, migraine, epithelial hyperproliferative diseases, septic shock, acute respiratory distress syndrome (ARDS), and combinations thereof.

9. 8. The method of claim 7, wherein the subject is selected from the group consisting of humans, veterinary animals, and agricultural animals.

10. The method of claim 7 , wherein the subject is a human.

11. A kit for treating or ameliorating the effects of a condition in a subject in need thereof, the kit comprising an effective amount of one or more aptamers prepared according to the method of claim 1, or one or more aptamers described in claim 4, packaged together with instructions for use thereof.

12. 10. A kit for treating or ameliorating the effects of a condition in a subject in need thereof, comprising an effective amount of the composition of claim 5 or 6 packaged together with instructions for its use.

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