174 results about "Posttranslational modification" patented technology

The invention belongs to the technical field of biology, and particularly relates to a nano antibody-proximity marker enzyme fusion protein and application thereof. Specifically, the present disclosure provides a fusion protein for proximity labeling wherein the fusion protein is operably linked together by (a) a nanobody and (b) a proximity labeling enzyme; optionally, a peptide linker is also included between the nano antibody and the proximity marker enzyme. The nano antibody-proximity marker enzyme fusion protein disclosed by the invention is obtained through in-vitro expression and purification, target protein is targeted by using an antibody, and the nano antibody-proximity marker enzyme fusion protein does not depend on an overexpression system and has compatibility to various cell types, tissues and clinical fixed samples; proteins with post-translational modification and various organelles, such as membraneless organelles, can be targeted; and the positioning accuracy rate reaches 100%.

This disclosure provides nanoparticle compositions, and use thereof for isolating and measuring proteins, protein degrader action, and cells. The disclosed nanoparticles can be identified by barcodes that reveal the identity of and post translational modifications to the bound protein using image processing techniques described herein.

The invention discloses a protein mass spectrum coding method based on self-supervised learning, and the method comprises the steps: guaranteeing the consistency of model input through the preprocessing steps of data enhancement, normalization, sequence length standardization and the like; by constructing a self-supervised learning task and utilizing a multi-head attention mechanism of a Transform architecture, efficient extraction of global and local features of mass spectrum data is realized; through an autoregressive encoder training framework, the model can automatically learn the internal structure of mass spectrum data without a large amount of labeled data, and high-dimensional coding representation with robustness and generalization ability is generated. According to the method, the workload of manual feature design is remarkably reduced, and the generated coding representation can be applied to downstream tasks such as mass spectrum data quality evaluation, protein identification and quantification, post-translational modification identification and biomarker discovery, and has wide applicability and high efficiency; and an innovative intelligent solution is provided for proteomics research.

The invention belongs to the technical field of medical diagnosis, and discloses a quantum multicolor immune digital pathological diagnosis analysis system, which comprises the following steps: acquiring high-resolution digital images of an immunohistochemical or immunofluorescence slice and a slide, and analyzing multicolor signal distribution in the images to obtain a quantum chromatographic image set; pixel-level color separation and intensity quantization are carried out on the quantum chromatographic image set, and a quantum intensity index set of each pixel is generated; performing multi-target color overlay analysis and post-translational modification protein specificity evaluation on the quantum intensity index set to construct a multi-color modification index set; identifying a single cell boundary and a multi-cell community based on the multicolor modification index set, and extracting a cell morphological parameter and a spatial adjacency relation to obtain a cell quantum analysis set; performing consistency correction and traceable recording by applying an automatic quality control mechanism, and generating a digital diagnosis report; the accuracy of accurate qualitative and quantitative analysis of immunohistochemistry and immunofluorescence is greatly improved.

The invention discloses a functional protein mining and screening method and device, which combines multi-dimensional bioinformatics analysis such as protein structure prediction, protein function annotation, protein cluster mining and the like with an artificial intelligence method based on a protein big language to construct a process for mining and screening a functional protein. Protein structure analysis is introduced, and proteins with similar functions are explored by utilizing association of protein structures and functions and constructing a structure similarity map. The protein large language model can contain characteristic parameters related to protein functions, such as a protein structure, post-translational modification and biophysical characteristics, and reveals the inherent functional relevance of the protein in a vector matrix form. By introducing the two analysis means and combining with the traditional sequence-based protein function annotation method, the sequence similarity and affinity are lower, but proteins with corresponding functions are excavated and screened out, so that biomacromolecules can be utilized more efficiently and accurately.

Novel systems and methods for drug design and screening exploiting dynamics of protein post-translational modifications are provided.

The invention discloses a multispectral intelligent identification system for protein post-translational modification sites, comprising: a spectral data acquisition module for controlling different spectrum analyzers to perform spectrum scanning and analog-to-digital conversion and formatting on protein samples in parallel to obtain multiple protein multispectral original data; the intelligent analysis module is used for carrying out preprocessing and feature extraction on the multi-spectral original data of each protein to obtain a plurality of standardized spectral feature vectors; fusing each standardized spectral feature vector to obtain a multi-dimensional feature vector, inputting the multi-dimensional feature vector into a pre-trained modification site recognition deep learning model, and outputting a recognition result list, the recognition result list comprises the positions of the recognized protein post-translation modification sites in the protein sequence and modification types corresponding to the protein post-translation modification sites; and the result output module is used for visually displaying and exporting the identification result list. According to the method, the accuracy and flux of protein post-translational modification site recognition are remarkably improved.

The present invention includes a mutant Dnase1LS having at least about a 95% identity with a nucleic acid sequence encoding the protein of SEQ ID NO: 2-8 for a mutant Dnase1LS comprising at least one mutation for post-translational modification or attachment of a molecule to the mutant Dnase1LS to increase the serum half-life of the mutant Dnase1LS, nucleic acids encoding the same, host cells, and methods of making the mutant Dnase1LS.

The invention relates to the technical field of genetic engineering, in particular to recombinant human collagen as well as a preparation method and application thereof. The recombinant human collagen provided by the invention is a polypeptide containing an amino acid sequence such as SEQ ID No.1. The recombinant human collagen disclosed by the invention is expressed at a high level outside cells, the culture is easy to amplify, the target protein can be produced at high yield by utilizing a high-density fermentation mode, secretory expression is beneficial to separation and purification of an expression product and reduction of production cost, and the recombinant human collagen has a certain post-translational modification function, such as glycosylation and the like, on the expressed foreign protein.

The present invention relates to a mammalian cell comprising a gene encoding a polypeptide of interest, wherein the polypeptide of interest is expressed comprising one or more posttranslational modification patterns. These modifications are useful for example in glycoprotein production where the antibodies with the modifications have an enhanced antibody-dependent cell-mediated cytotoxicity (ADCC). The present invention also relates to methods for producing the glycoproteins and compositions comprising the glycoproteins, and their uses.

The present invention provides a novel expression system comprising a mammalian selectable marker that promotes the desired post-translational modification of a glycoprotein. Specifically, the present invention includes methods and compositions for achieving optimal recombinant protein expression in mammalian cells by using a selectable marker system based on a GPT gene of mammalian origin. The present invention includes methods for promoting the selectivity of recombinant proteins and increasing expression copies and protein yields in mammalian cells, and methods for using the GPT expression system.

The invention discloses a green algae expression method and application of recombinant human serum albumin, and belongs to the technical field of biology. Aiming at the problems of high cost and incomplete post-translational modification of the existing recombinant protein expression system, the invention provides a technical scheme for efficiently expressing human serum albumin by using green algae. The method comprises the following steps: carrying out codon optimization on a human serum albumin gene sequence, introducing a recombinant vector into green algae cells, and screening transgenic algae strains through a culture medium containing a resistance agent, culturing the transgenic algal strain, splitting the algal cells and separating the recombinant albumin. According to the method, efficient production of the human serum albumin is achieved through a green alga expression system, and the product has a correct folding structure and biological activity and is mainly used for preparing medical plasma substitutes, drug carriers and biological agents.

The invention discloses a method for detecting polypeptide sequence difference and post-translational modification thereof based on a nanopore system, the nanopore system is constructed in the method, and the nanopore system comprises an alpha-hemolysin nanopore and octa-amino modified gamma-cyclodextrin embedded in the nanopore; the amino acid sequence of the alpha-hemolysin nanopore comprises mutation sites M113R and T145R, and the alpha-hemolysin nanopore is characterized in that the alpha-hemolysin nanopore According to the detection method, polypeptide with negative charges enters a nanopore under the driving of external voltage, an ion current blocking signal is recorded, and the polypeptide sequence difference and post-translational modification are analyzed according to blocking amplitude, duration, noise characteristics and event frequency. The method can detect a peptide chain with the length of 2-10 amino acid residues, can distinguish the post-translational modification state in homopolypeptide composed of 4-10 amino acids and polypeptide by single amino acid resolution, and can be used for protein enzyme digestion product analysis, oligopeptide drug detection and rapid polypeptide identification under the condition of no mass spectrum.

Disclosed herein are high performance biomarkers and kits for the early detection of small cell lung cancer (SCLC), which can be used to identify, diagnose and treat SCLC patients in the early stage. Methods of diagnosing and treating SCLC in a subject can include detecting the presence of an autoantibody that specifically binds to one or more epitopes of an antigen in a biological sample obtained from the subject, wherein the one or more epitopes of the antigen comprise a post-translational modification; diagnosing the subject with SCLC when the presence of the autoantibody is detected in the biological sample; and treating the SCLC in the subject by administering a chemotherapy regimen, an immunotherapy regimen, an antibody, surgical and / or radiation therapy. In one example, post-translational modifications targeted by autoantibodies include citrullination, isoaspartic acidification, and / or cancer-specific glycosylation.

Provided herein are populations of anti-CD20 antibody proteins having a specified post-translational modification range. Methods of use and methods of manufacture of such anti-CD20 antibody protein populations are also provided.

Disclosed herein are methods for preparing a biological sample for single-cell analysis which will simultaneously provide single-cell RNA, single-cell extracellular protein, single-cell cytoplasmic protein, and single-cell transcription factor readouts while preserving cellular heterogeneity. Some methods disclosed herein allow for the detection of proteins including the detection of the level of proteins and / or the detection of post translational modifications of proteins.

The invention discloses a preparation method and application of high-activity recombinant collagen, and relates to the field of biological medicine, and the preparation method comprises the following steps: S1, providing engineering bacteria containing a recombinant collagen expression vector, and performing seed culture; s2, inoculating the seed solution into a fermentation culture medium for fermentation culture; s3, in the fermentation process, when the thallus density reaches a preset value, a signal factor without an animal source is added into a fermentation system, and the signal factor is bionic polypeptide; s4, after the signal factors are added, the fermentation conditions are adjusted, and target collagen expression is induced; according to the preparation method and the application of the high-activity recombinant collagen, an endogenous metabolic network of bacteria is actively regulated and controlled by accurately adding animal-source-free bionic polypeptide signal factors in the fermentation process of engineering bacteria, and correct folding and specific post-translational modification of target collagen are induced; therefore, the hydroxylation rate and the biological activity of the recombinant collagen are improved, and the structure and the function of the recombinant collagen are closer to those of natural collagen of a human body.

The invention relates to a recombinant hirudin fusion protein, a coding gene and a prokaryotic expression method and application of the recombinant hirudin fusion protein. The recombinant hirudin fusion protein comprises an HMg variant amino acid sequence and a fusion tag. The recombinant hirudin fusion protein has the advantages that the hirudin variant in poecilobdella manillensis is adopted to construct an efficient prokaryotic expression system, the hirudin yield and activity are improved under the condition that post-translational modification is not needed, the anticoagulant efficiency and the production process of the recombinant hirudin fusion protein provide an important basis for development of a new generation of antithrombotic drugs, and the recombinant hirudin fusion protein has wide application prospects. The progress of cardiovascular disease treatment and hirudin production is expected to be promoted.

UBAS is a critical El-activating enzyme in the UFMylation pathway, a post-translational modification process implicated in neurodegenerative diseases and cancers. Here, a high-throughput screening (HTS) assay was developed to identify inhibitors of UBAS from various compound libraries. Eighteen novel UBAS inhibitors were identified, belonging to several distinct chemical scaffolds with low micromolar IC50 values. These inhibitors demonstrated selectivity for UBAS over other El enzymes, including UBA1, and showed efficacy in inhibiting endogenous UFMylation in HEK293T cells. The identified inhibitors not only provided valuable tools for studying UFMylation but also represented potential therapeutic candidates for diseases associated with dysregulated UFMylation, such as Alzheimer's disease and cancer.

A processor is configured to implement a machine learning model that is trained to select transcripts in blood for distinguishing neurodegenerative diseases. The algorithm is developed via machine learning and leverages concepts associated with blood-based changes in mRNA gene expression for differentiating patients of any neurodegenerative disease regardless of the proteins or their post-translational modifications occurring in disease.

This invention discloses a complete set of reagents for detecting the interaction between post-translational modified proteins and their ligands. The complete set of reagents of this invention consists of four reagents: A, B, C, and D. A is composed of a biomolecule named R linked to a protein named X; B contains a biomolecule named L; R and L may be the same or different and interact with each other, with a phase transition occurring after the interaction between R and L; C is a polymer formed from a C monomer, wherein the C monomer consists of a monomer named mc, a reporter group named α, and a group named Y. C Molecules obtained by linking biomolecules, with two or more mc molecules, can form polymers; D is composed of molecules named X L The modified protein and its name is Y. D It is composed of biomolecules linked together; Y C With Y D There are interactions between them. This invention achieves high enrichment of interacting proteins and ligands in phase change droplets, amplifies weak interaction signals, and makes them easy to detect.

Methods and apparatuses for the identification and / or characterization of properties of a macromolecule based on mass spectrometry data. Specifically, described herein are methods and apparatuses for converting peptide-level data into a pseudo-intact mass spectra. Also described herein are methods and apparatuses for converting peptide-level data into a pseudo-electropherogram. The methods may be well suited for analyzing proteins and protein complexes, including estimating properties of post-translational modifications of the proteins and protein complexes. Methods may include generating a theoretical graph or spectrum based on peptide-level mass spectrometry data. In some embodiments, the theoretical graph may be a theoretical intact mass spectrum or a theoretical charge distribution spectrum.

This application relates to antibodies or combinations of antibodies or antigen¬ binding fragment(s) thereof that comprise a first binding unit that binds to a first epitope of a target protein that harbors a post-translational modification (PTM) and a second binding unit that binds to a second epitope of a target protein that does not harbor the PTM, as well as antibody fusion molecules and multispecific antibodies or antigen-binding fragments thereof that bind to same.

Compositions and methods are described for the delivery of a fully human post-translationally modified (HuPTM) monoclonal antibody (“mAb”) or the antigen-binding fragment of a mAb against human vascular endothelial growth factor (“hVEGF”)—such as, e.g., a fully human-glycosylated (HuGly) anti-hVEGF antigen-binding fragment—to the retina / vitreal humour in the eye(s) of human subjects diagnosed with ocular diseases caused by increased neovascularization, for example, neovascular age-related macular degeneration (“nAMD”), also known as “wet” age-related macular degeneration (“WAMD”), age-related macular degeneration (“AMD”), and diabetic retinopathy.

Provided are methods and compositions for the delivery of fully human post-translationally modified therapeutic monoclonal antibodies and antigen-binding fragments thereof. The fully human post-translationally modified therapeutic monoclonal antibodies may be preferably delivered by gene therapy methods, particularly as a recombinant adeno-associated virus (rAAV) vector to the appropriate tissue. Methods of manufacture of the AAV vectors, pharmaceutical compositions and methods of treatment are also provided. In addition, provided are methods of producing therapeutic antibodies that are "biobetters" as fully human post-translationally modified. These fully human post-translationally modified therapeutic antibodies may be administered to a subject in need of treatment with the therapeutic antibody.

The invention provides a proteomics complex post-translational modification large-scale rapid identification method which comprises the following steps: preprocessing original protein data of a sample to obtain a primary signal peak cluster and a candidate secondary signal peak set corresponding to each primary signal peak; determining a first-level signal peak and a second-level signal peak pair based on the first-level signal peak cluster and the candidate second-level signal peak set; based on a pre-trained deep learning model and the peak pair of the first-level signal peak and the second-level signal peak, obtaining a matching score of the peak pair of the first-level signal peak and the second-level signal peak; and constructing a target pseudo secondary spectrogram based on the matching score, and performing open search on the target pseudo secondary spectrogram to obtain an identification result containing post-translation modification. According to the method, deconvolution can be carried out on the complex secondary spectrogram under methods including independent collection, the target pseudo secondary spectrogram which can be directly used for open type search is generated, and then accurate identification and deep analysis of accidental modification signals are achieved.

The invention discloses a specific anti-ITSN1-S-K1068 lysine lactylated antibody and a preparation method and application thereof.The preparation method comprises the following steps that 1, ITSN1-S-K1068 lactylated polypeptide is connected to an immune carrier in a sulfydryl coupling mode, a polypeptide antigen is obtained, the polypeptide antigen is mixed with a Freund's complete adjuvant and a Freund's incomplete adjuvant respectively, and an immune carrier is obtained; emulsifying to obtain water-in-oil liquid drops; and step 2, carrying out animal immunization by using the water-in-oil liquid drops, and carrying out separation from the immunized animal to obtain the specific anti-ITSN1-S-K1068 lysine lactylated antibody. The antibody provided by the invention can specifically detect the lactic acid modification condition of the human ITSN1-S protein from cell and tissue levels in practical application, is beneficial to discussing the action mechanism of post-translational modification of the ITSN1-S protein in the processes of tumor proliferation, migration and the like, and provides a potential action target for clinical diagnosis and treatment of tumor diseases.

Provided herein are RNA editing oligonucleotides capable of effecting ADAR-mediated deamination of a target adenosine comprised in a target RNA, wherein the oligonucleotide comprises a sequence that is capable of hybridizing with a region in the target RNA comprising said target adenosine, and wherein the oligonucleotide comprises at least one conformationally restricted nucleotide (CRN) positioned at the 5' and / or at the 3' terminus of the oligonucleotide and / or internally. In particular, the target adenosine may be part of a therapeutic target codon in the MECP2 protein-coding RNA. Provided herein are RNA editing oligonucleotides capable of effecting ADAR-mediated deamination of a target adenosine in a target RNA molecule encoding a target protein, wherein the oligonucleotide comprises a sequence that is capable of hybridizing with a region in the target RNA molecule comprising said target adenosine, and wherein the target adenosine is part of a codon encoding a posttranslational modification site in the target protein. In particular, the target adenosine may be part of a ubiquitination site in the frataxin (FXN) protein. Provided herein are RNA editing oligonucleotides capable of effecting ADAR-mediated deamination of a target adenosine in a target RNA molecule encoding a target protein, wherein the oligonucleotide comprises a sequence that is capable of hybridizing with a region in the target RNA molecule comprising said target adenosine, and wherein the target adenosine is part of a start codon in the 5' untranslated region of the target RNA molecule. In particular, the target adenosine may be part of the start codon of an untranslated ORF (uORF) in the human Sodium-dependent phosphate transporter 2 protein (SLC20A2).

The invention provides an application of an HDAH inhibitor in preparation of antibiotics. According to the invention, research finds that escherichia coli has Zn < 2 + >-dependent histone deacetylase-like amide hydrolase-HDAH, and the HDAH can directly influence the enzyme activity of metabolic enzyme through acetylation modification so as to regulate and control the metabolic level of bacteria; and the transcription level of metabolism-related genes can be indirectly regulated by acting on a transcription regulation factor (such as histone-like protein HU), and the metabolism of escherichia coli is synergistically regulated from two levels of post-translational modification and transcription. The invention also finds that the vorinostat (SAHA), the trichosaliocin (TSA) and the like can be combined with the HDAH and inhibit the deacetylation activity of the HDAH, are HDAH inhibitors, and inhibit the growth and migration ability of escherichia coli after being administered to the escherichia coli.

The present invention provides a method and system for predicting species-specific post-translational modification sites of proteins, including: obtaining post-translational modification sites and differential species training samples through data preprocessing; constructing a sequence feature extraction network and setting up a classifier and a domain category discriminator; processing the differential species training samples by a semantic adversarial strategy to obtain a sample pairing group; training the sequence feature extraction network and the classifier with the human post-translational modification samples, and training the domain category discriminator according to the sample pairing group to distinguish the group information of the input sample pairs, and alternately training the sequence feature extraction network and the domain category discriminator so that the sequence feature extraction network, the classifier and the domain category discriminator learn a domain-invariant discriminant feature space; evaluating the performance of the deep neural network. The technical problems of inefficient, expensive, time-consuming, overfitting prediction methods and low prediction accuracy are solved.