40 results about "ESA Protein" patented technology

Provided is a glycosyltransferase UGTSL2 mutant, which is produced through any one or more selected from the group consisting of mutations based on an amino acid sequence shown in SEQ ID NO: 1. Also provided is a glycosyltransferase mutant, which is the following A1) or A2): A1) a protein produced through an amino acid residue substitution in an amino acid sequence shown in SEQ ID NO: 66, where the protein has an identity of 90% or more with and the same function as the amino acid sequence shown in SEQ ID NO: 66; and A2) a fusion protein produced by linking a tag to an N-terminus and / or a C-terminus of the protein in the A1).

The invention provides a protein language model pre-training and protein mutation method and related products. According to one specific embodiment of the protein language model pre-training method, a sample protein data set is obtained; generating a multi-sequence alignment probability distribution sequence corresponding to the sample protein data according to the amino acid residue probability distribution of multiple sequences in each sample protein data alignment at each site; the sample protein sequence in each sample protein data and the corresponding multi-sequence comparison probability distribution sequence and structure sequence are sequentially connected in series in the forward direction or the reverse direction, and a multi-modal sequence corresponding to the corresponding sample protein data is generated; and finally, performing autoregression pre-training on the protein language model based on the multi-modal sequence corresponding to each sample protein data to obtain a pre-trained protein language model. Namely, the prediction performance of the model is improved by introducing a multi-sequence comparison probability distribution sequence as an independent intermediate reasoning mode and thinking chains in two directions.

A target protein drug binding prediction method based on meta learning and subgraph matching, by constructing protein structure, drug small molecule structure and its binding energy value, the meta learning training task is established according to protein grouping, that is, as the main model of the meta model; the sub model and its loss function for the protein prediction task are obtained after fine tuning of the meta model; then the task self-adaptive self-attention model is established to balance the optimization contribution of the sub model of each protein prediction task to the meta model, the weighted average is used for the loss function of the sub model of each protein prediction task to obtain the meta model loss function; then the meta model loss function is used to calculate the gradient, the meta model parameters are updated and optimized based on the preset learning rate, and after the training is completed, the trained meta model is used for fine tuning of the test set of new protein samples, the prediction sub model of the new protein is obtained, the sub model is used for prediction of the protein test set, and the evaluation result is obtained. The training method combining meta learning and subgraph matching can effectively avoid shortcut learning, enhance the generalization effect, and also solve the problem that the previous prediction model is difficult to predict the newly discovered protein.

According to the method for detecting the conductance of the protein molecules and the application of the method, asymmetric modification is carried out on the tunneling electrode pair and the protein molecules, so that the protein molecules can enter a tunneling area in a fixed posture and form asymmetric single-molecule junctions with the tunneling electrode pair, the activity of the protein molecules can be kept to the maximum extent, and the conductivity of the protein molecules is detected. Therefore, the device capable of stably detecting the conductance of the protein molecules for a long time can be constructed and obtained, and the device can be used for researching the dynamic conformation of the protein, screening small-molecule drugs targeting the protein molecules and analyzing the interaction relationship between the small-molecule drugs and the protein molecules. The tunneling electrode device and the real-time electrical measurement technology are used for achieving protein detection on the single molecule level, the conformation change process of protein such as biological enzyme and the action characteristics of the protein and small molecules are comprehensively described on the high time resolution scale, and the design and optimization efficiency and success rate of existing drugs are expected to be improved.

The application discloses application of a micro cryptosporidium cgd6_660 protein as an oocyst outer wall marker protein, and discloses that the inventors find that the cryptosporidium cgd6_660 protein is an oocyst outer wall protein, and the protein is located on the outer surface of the cryptosporidium oocyst wall. The inventors confirm the feasibility of the protein as a detection antigen. The antibody of the protein recombinant protein (as shown in a sequence table SEQ ID N0.2) can be used for immunological detection of unbroken cryptosporidium oocysts (live cryptosporidium oocysts), and the application further provides a specific polypeptide of the protein.

The present invention provides a method for detecting the electrical conductivity of protein molecules and its application. By asymmetrically modifying a tunneling electrode pair and a protein molecule, the protein molecule can enter the tunneling region in a fixed posture and form an asymmetric single-molecule junction with the tunneling electrode pair, which can maximize the activity of the protein molecule. This constructs a device that can stably detect the electrical conductivity of protein molecules over a long period of time. The device can be used for dynamic conformational studies of the protein itself, screening of small molecule drugs targeting the protein molecule, and analysis of the interaction between small molecule drugs and protein molecules. The present invention utilizes tunneling electrode devices and real-time electrical measurement technology to achieve protein detection at the single-molecule level, comprehensively depicting the conformational change process of proteins such as biological enzymes and their interaction characteristics with small molecules on a high time resolution scale, and is expected to improve the efficiency and success rate of existing drug design and optimization.

The present invention provides a compound having the structure:A-B-----Zwherein A is a biologically active structure of the compound;wherein Z is a protein component of the compound, which protein component comprises one or more polypeptides, wherein at least one of the one or more polypeptides comprises consecutive amino acids which (i) are identical to a stretch of consecutive amino acids present in a chain of an Fc domain of an antibody; (ii) bind to an Fc receptor; and (iii) have at their N-terminus a sequence selected from the group consisting of a cysteine or selenocysteine; wherein the dashed line between B and Z represents a peptidyl linkage; and wherein the solid line between A and B represents a nonpeptidyl linkage, as well as intermediates dimers thereof, and processes of producing the compounds of the invention.

The invention provides a protein scaffold and methods of preparing, screening, engineering and using the protein scaffold.

A protein, such as an antigenic protein, is produced by determining an amino acid sequence of an ancestral version of a given protein in an ancestral sequence reconstruction method based on a plurality of homologous amino acid sequences of the given protein. A domain of the amino acid sequence of the ancestral version of the given protein is replaced with a corresponding domain derived from an amino acid sequence of the given protein or a homologous version thereof. The protein thereby comprises the amino acid sequence obtained by replacing the domain of the amino acid sequence of the ancestral version of the given protein with the corresponding domain derived from the amino acid sequence of the given protein or the homologous version thereof. The protein is suitable as antigen, as vaccine candidate and / or for structural studies.

The present invention relates to a disease-specific biomarker for early prediction and diagnosis of preeclampsia and use thereof, and a composition for prediction or diagnosis of preeclampsia according to an aspect or a method of providing information for prediction or diagnosis thereof, can simply and effectively predict or diagnose the disease by measuring and comparing the mRNA level of a disease-specific protein or a gene encoding the protein changed in a patient.

The present invention addresses the main problem of providing a synthetic culture medium that does not contain animal-derived components. In particular, the present invention addresses the problem of providing a culture medium containing, at a low concentration (at most about 2,000 μM), a peptide that contributes to promoting protein production even when animal-derived components are not contained.　Provided is a protein production promoter comprising, as an active ingredient, a peptide mixture at a total concentration of at most 2,000 μM, wherein the peptide mixture is composed of two peptides selected from the group consisting of Gly-Glu-Lys (GEK), Asp-Gly-Pro (DGP), Ala-Gly-Lys (AGK), Ala-Glu-Lys (AEK), Ala-Gly-Gly (AGG), Ala-Ser-Asn (ASN), Gly-Pro-Pro (GPP), Gly-Gly-Pro (GGP), and Glu-Gly-Lys (EGK), and is a combination with which protein production is further promoted by mixing the selected two peptides.

Methods, compositions, kits, and systems are provided for identifying protein-binding regions in genomic DNA. The method may include contacting genomic DNA with an adenine methyltransferase (A-MTase), wherein the A-MTase methylates adenine residues in a region of the genomic DNA that is not protein-binding; and performing single-molecule long-read sequencing on the contacted genomic DNA to detect locations in the genomic DNA lacking methylated adenine residues, thereby identifying regions in the genomic DNA that are protein-binding. The bound region may be a nucleosome location, and the method can determine the nucleosome location in the genomic DNA. A method is also provided for visualizing chromatin regions that are not protein-binding and spatially serve as substrates for the A-MTase within the cell by visualizing the location of methylated adenine after contacting the cell with the adenine methyltransferase (A-MTase).

Embodiments of the present disclosure provides a method, an electronic device and a storage medium. In the method, a number of residues of a protein structure is obtained, a protein backbone of the protein structure in a first scale is generated, and the protein structure in a second scale is generated based on the number and the protein backbone, where the second scale is larger than the first scale.

Examples are directed to composition, kits, and methods thereof. An example composition comprises a protein and an oligonucleotide linked to the protein via a tetrazine and a trans-cyclooctene (TCO) in a predetermined relationship.

Provided are protein nanostructures that display Neisseria meningitidis factor H binding protein (fHBP). The protein nanostructure may be a two-component icosahedral nanostructure. Further provided are vaccine compositions, methods of manufacturing, and methods of use, e.g., immunizing a subject to generate a protective immune response to Neisseria meningitidis.

An in vitro method for assessing or predicting the response of human patients to treatment of periodontal disease is disclosed. This method is based on insights into identifying biomarker proteins. Therefore, the concentration of a specific combination of proteins is measured in a saliva sample from the patient. One such combination is at least one of interleukin-1-β (IL-1β) and matrix metalloproteinase-8 (MMP-8), and α-1-acid glycoprotein (A1AGP). Based on the measured concentrations, at least one value reflecting the combined concentration of these proteins is determined. This at least one value can indicate the likelihood that the human patient has been or will be successfully treated for periodontitis. This at least one value can be compared to at least one threshold, which in the same manner reflects the combined concentration associated with successful treatment of periodontitis. This comparison allows assessment of whether the test value is an indicator of the patient's periodontal treatment status.

The present disclosure provides a protein language model pre-training method and related products. In one embodiment of the protein language model pre-training method, a sample protein sequence and co-evolution pairs in the sample protein sequence are masked to obtain a sample mask token sequence. Then, the sample mask token sequence is embedded and encoded based on a protein language model to obtain an encoded feature sequence. The encoded feature sequence is decoded based on a preset sequence feature decoder to obtain a decoded protein sequence. The protein language model is optimized based on the difference between the decoded protein sequence and the sample protein sequence and each co-evolution pair. That is, by masking the co-evolution pairs in the protein sequence during pre-training, the understanding and prediction ability of the protein language model for the protein sequence can be optimized, and the accuracy of downstream protein sequence / structure related tasks based on the protein language model can be improved.

Protein complexes targeting CD47, PD-L1, and / or TIGIT are provided, as well as methods for using the same. In one embodiment, the protein complex comprises a CD47-binding domain having all or part of the SIRPα extracellular domain, a PD-L1-binding domain having all or part of the PD-1 extracellular domain, and a TIGIT ligand-binding domain having all or part of the TIGIT extracellular domain.

An in vitro method for assessing or predicting the response of a human patient to periodontal disease treatment is disclosed. The method is based on the insight that biomarker proteins are determined. Thus, in a saliva sample of a patient, the concentration of a specific combination of proteins is measured. One such combination is hemoglobin subunit delta (Hb-delta) and pyruvate kinase (PK). Another combination is at least two of alpha-1-acid glycoprotein (A1AGP), pyruvate kinase (PK), and matrix metallopeptidase-8 (MMP-8), and keratin-4 (K-4). A third combination is alpha-1-acid glycoprotein (A1AGP), pyruvate kinase (PK), and S100 calcium-binding protein A8 (S100A8). Based on the measured concentrations, at least one value is determined that reflects the joint concentration of this proteins. The at least one value can be indicative of the likelihood that the human patient has or will successfully treat periodontitis. The at least one value can be compared to at least one threshold value that reflects the joint concentration in the same way that is associated with successful treatment of periodontitis. This comparison allows to assess whether the test value is an indication of the periodontal treatment status of the patient.

Provided is a chemical recycling method for nylon using an enzyme reaction instead of depolymerization. A mutant, which is a protein that is the following (4), (5), or (6) and in which an amino acid corresponding to at least one selected from among D304, R52, D99, and G111 of the sequence of SEQ ID NO: 1 is mutated, is used. (4) is a protein composed of the amino acid sequence of SEQ ID NO: 1. (5) is a protein composed of a sequence obtained by deleting, substituting, or adding 1-35 amino acids in the amino acid sequence of the protein described in (4), and having 6-aminohexanoic acid oligomer endo-type hydrolase (NylC) activity. (6) is a protein composed of a sequence that shares a sequence identity of at least 90% with the protein described in (4), and having NylC activity.

To provide a novel protein for facilitating the stabilization or structural analysis of a target protein.SOLUTION: Provided is a protein for addition to a target protein that forms a predetermined tertiary structure including a central domain, a first peripheral domain, and a second peripheral domain, the central domain, the first peripheral domain, and the second peripheral domain each including a hydrophobic core formed by a plurality of helices, the hydrophobic core of the central domain being formed by a plurality of helices including at least one helix included in the first peripheral domain and at least one helix included in the second peripheral domain.SELECTED DRAWING: Figure 1A

To provide a method and a kit for analyzing a biological sample obtained from a subject having, suspected to have, or at the risk for a disease associated with a contact activation system.SOLUTION: There is provided a method for analyzing a sample including: (i) preparing a biological sample (for example, serum sample or plasma sample) obtained from a subject (human subject) having, suspected to have, or at the risk for a disease associated with a contact activation system; and measuring the level of a set of biomarkers including at least one type of protein selected from a table 1, in which when the set of biomarkers consists of one type of protein, the protein is not C4, plasma prekallikrein, thrombin, a tissue-type plasminogen activator (tPA), and heat shock protein 90.SELECTED DRAWING: Figure 1

Embodiments of the disclosure provide a solution for a protein language model. A method includes: obtaining a sequence representation of a protein comprising a plurality of amino acid residues, the sequence representation characterizing an amino acid sequence of the protein; determining, by a language model, a predicted discrete structure representation based on the sequence representation, wherein the predicted discrete structure representation comprises a plurality of bit sequences corresponding to the plurality of amino acid residues respectively, a bit sequence of the plurality of bit sequences represents a predicted local structure of a corresponding amino acid residue; and generating a target structure of the protein based on the predicted discrete structure representation.

The present disclosure relates to: a variant of a protein; a polynucleotide encoding the variant of a protein; a microorganism of the genus Corynebacterium, comprising at least one selected from the group consisting of the variant of a protein and the polynucleotide; and a method for producing L-isoleucine by using the microorganism.

[Problem] To provide a conjugate comprising a protein and a nucleic acid moiety, and an immunodetection method using said conjugate. [Solution] A conjugate comprising a protein and a nucleic acid moiety that includes a first nucleic acid bound to the protein and a second nucleic acid containing a sequence complementary to the first nucleic acid is produced. The first nucleic acid and the second nucleic acid form a complementarily bound double-stranded portion, the second nucleic acid includes a single-stranded overhang portion, and the double-stranded portion includes a photo-crosslink using cnvK that crosslinks the first nucleic acid and the second nucleic acid. The conjugate can be used in the detection of a target substance by isothermal amplification and in nucleic acid medicine and gene therapy drugs.

Provided are proteins comprising a variant IgG Fc region, wherein the proteins exhibit significantly reduced binding to human FcγRI when compared with a reference protein comprising the amino acid substitutions L234A / L235A / P329G. Also provided are compositions, methods of treatment and methods to reduce Fc-induced effector functions in a parent protein.

The invention discloses a protein combination marker related to Parkinson's disease, a product and application. The protein combination marker is characterized by comprising KITM, DKK3, PHC1, MP2K3, PERE, VGFR1, IREB2, PPP5, HEPC, H2A2B, IKKA, FBRL, FAK1, EDIL3, NCK1, DRC11, GCYA1, TTC27, CD63 and LHPL2, and the protein combination marker is prepared from the following components: KITM, DKK3, PHC1, MP2K3, PERE, VGFR1, IREB2, PPP5, HEPC, H2A2B, IKKA, FBRL, FAK1, EDIL3, NCK1, DRC11, GCYA1 The invention also discloses a related product and application of the protein combination marker. The invention provides a protein combination marker containing 20 proteins. Whether an object to be detected suffers from Parkinson's disease or not is diagnosed by utilizing the protein marker and a related calculation method. The protein combination marker provided by the invention can realize multi-stage prediction. Proteome-based early, middle and late parting prediction of Parkinson's disease is realized for the first time.

The invention discloses a protein language model targeted polypeptide generation method and system in the technical field of bioinformatics and computer drug design. The protein language model targeted polypeptide generation method comprises the following steps: an input module reads original sequence data as joint input; the embedding module converts the original sequence data into embedded vector data; the encoder module adopts a self-attention mechanism of an ESM3 model to extract a feature embedding vector of a target protein sequence; the decoder module uses a ProGen2 model to generate a new polypeptide sequence through double-layer cross attention mechanism fusion; and the output module generates a new sequence, and outputs and converts the new sequence into a final targeted polypeptide sequence through a corresponding decoding strategy. According to the protein language model targeted polypeptide generation method, the bottleneck of multi-attribute collaborative optimization is broken through, accurate conditional generation of specific target protein is achieved, and the design efficiency and controllability are improved.

The application discloses a multi-point protein directed evolution design method based on a graph neural network, and designs protein directed evolution through a trained protein directed evolution model based on a graph neural network, and comprises the following steps: protein data preparation, representing a protein structure as a protein graph, wherein each node in the graph represents an amino acid, and nodes close to each other are connected by edges; and binding amino acid feature data on the nodes or edges of the graph. The protein directed evolution design method is used for guiding a directed evolution task in protein engineering and designing an effective multi-point protein mutation scheme.

The present invention relates to an allele designated alpha-WOLF 31 which confers resistance to at least one Peronospora effusa race, wherein the protein encoded by said allele is a CC-NBS-LRR protein that comprises in its amino acid sequence: a) the motif "MAEIGYSVC" at its N-terminus; and b) the motif "KWMCLR"; and wherein the protein has an amino acid sequence that in order of increased preference has at least 97% sequence similarity to SEQ ID NO: 11. The allele when present in a spinach plant confers complete resistance to at least Peronospora effusa race Pe:1, Pe:2, Pe:4, Pe:5, Pe:6, Pe:7, Pe:10, Pe:12, Pe:13, Pe:14, Pe:15, Pe:16, Pe:18, Pe:19, and Pe:20.