281 results about "Peptide sequence" patented technology

The invention relates to the field of preparation and application of biological peptides, in particular to a swelling hippocampal peptide and application thereof in preparation of uric acid reducing and gout resisting products. The amino acid sequence is shown as SEQ ID NO.1. The uric acid reducing effect of the compound is proved through in-vitro xanthine oxidase (XOD) and adenosine deaminase (ADA) inhibition experiments and cell experiments; on the basis, the uric acid reducing and gout resisting activity of the peptide sequence is further verified by means of a hyperuricemia animal model. The achievement provides a solid theoretical support for high-value development and utilization of the hippocampus japonicus and research and development of uric acid reducing and gout resisting related products.

An engineered polypeptide for use in treating age-related macular degeneration (AMD) comprising FHL-1 engineered variant peptides, compositions including these engineered polypeptides and methods of using them. Further, wherein polypeptides include a linker domain separating the first peptide sequence from the second peptide sequence, a first junction region between the first peptide sequence and the linker domain and a second junction region between the second peptide sequence and the linker domain.

The invention relates to isolated synthetic or recombinant peptides comprising an epitope of human tau 2N4R, wherein the tau peptide sequence comprising the epitope is not phosphorylated. The invention also relates to use of such peptides to generate binding molecules, such as antibodies, specific for the non-phosphorylated tau epitopes and to such peptides and binding molecules, such as antibodies, for use in investigation, diagnosis and treatment of tauopathies, such as Alzheimer's disease.

Disclosed are compositions and methods useful for targeting and internalizing molecules into cells of interest and for penetration by molecules of tissues of interest. The compositions and methods are based on peptide sequences that are selectively internalized by a cell, penetrate tissue, or both. The disclosed internalization and tissue penetration is useful for delivering therapeutic and detectable agents to cells and tissues of interest.

The invention provides a milk protein peptide which takes milk protein as a raw material and has the effects of promoting calcium absorption and improving bone health and application of the milk protein peptide. Specifically, milk protein peptide sequences, including YGGVSL and SQRY, are screened by adopting enzymolysis, sequence identification and molecular docking methods. The milk protein peptide is proved to have high calcium transport promoting capacity in the in-vitro intervention of Caco-2 cells, and the milk protein peptide is proved to have the capacity of promoting osteogenesis and inhibiting bone resorption in the in-vitro intervention of MC3T3-E1 mouse embryo osteoblasts. In animal experiments, by increasing the content of blood calcium and bone calcium, reducing the content of excrement calcium, improving mRNA expression of calcium ion channel protein, calcium binding protein and peptide transporter in intestinal tracts, enhancing the efficiency of calcium entering blood, promoting osteogenesis and inhibiting bone resorption, the milk protein peptide is comprehensively proved to have the capabilities of improving calcium resorption of organisms and improving bone health. The milk protein peptide has both functionality and nutrition, and has a wide application prospect in the aspect of bone health.

The invention relates to the technical field of deep learning, and discloses a multifunctional bioactive peptide function classification method based on evolutionary deep learning. Comprising the following steps: acquiring a data sample set, and dividing the data sample set into a training set and a test set according to a preset proportion; preprocessing the training set and the test set to obtain a preprocessed training set and a preprocessed test set; constructing an initial deep learning model for active peptide function classification, searching parameters of the model by using an evolutionary algorithm, and constructing an optimized deep learning model based on the parameters; training an optimized deep learning model by using the preprocessed training set, and testing the trained optimized deep learning model by using the preprocessed test set to obtain a trained deep learning model; and preprocessing a to-be-classified peptide sequence, and inputting the preprocessed peptide sequence into the trained deep learning model to obtain a classification result. By adopting the method, the classification precision of the active peptide and the migration ability of the model to adapt to different data sets can be improved.

The invention discloses an antibacterial peptide prediction method based on dual-channel sparse attention. The method comprises the following specific steps: extracting initial embedding by using a protein language model; adaptively weighting the channel by using the channel attention enhanced convolutional neural network; capturing short-range interactions between amino acid residues using local sparse attention based on a sliding window; global sparse attention containing a scoring function is used for obtaining long-range interaction between key amino acid residues and the sequence, and local and global information is integrated so as to realize complete characterization of the peptide sequence; and predicting the final feature matrix by using a full connection layer. According to the method, the sequence information of the peptide is comprehensively modeled by using a simple and efficient training process, and a dual-channel sparse attention mechanism is introduced to effectively relieve the problems of representation redundancy and calculation complexity.

The invention discloses sturgeon cartilage active peptide capable of promoting growth and improving bone development as well as a preparation method and application of the sturgeon cartilage active peptide, and belongs to the technical field of active peptide. According to the invention, sturgeon cartilage is taken as a raw material, polypeptide with the highest activity of promoting bone growth and development is selected from different enzymolysis combinations through MC3T3-E1 cell tests, and the positive effect of the polypeptide is verified through zebra fish tests; then, two potential sturgeon cartilage active peptide sequences with the function of promoting bone growth and development are screened out through bioinformatics technologies such as mass spectrum identification, molecular docking and the like, and the amino acid sequences of the sturgeon cartilage active peptide fragments are shown as SEQ ID NO.2 and SEQ ID NO.5. The sturgeon cartilage peptide prepared by the method disclosed by the invention has the activity of promoting bone growth and development, can solve the problem of high-value utilization of sturgeons, can also be applied to functional products as a functional factor, and has a good application prospect.

The invention relates to the technical field of gene engineering, in particular to a transgenic zebrafish system pTo12-efla-tjp1a-P2A-mCherry based on a Tol2 transposition subsystem and a construction method of the transgenic zebrafish system pTo12-efla-tjp1a-P2A-mCherry. The preparation method comprises the following steps: S1, constructing a Tol2 transposon expression vector pTol2-ef1a-tjp1a-P2A-mCherry which contains an ef1a promoter, a tjp1a gene, a P2A peptide sequence and an mCherry reporter gene; s2, carrying out in-vitro transcription to prepare Tol2 transposase mRNA; s3, mixing the expression vector with Tol2 transposase mRNA, and microinjecting the mixture into the single-cell stage embryo of the zebra fish; s4, performing fluorescence screening on the F0 generation embryos surviving after injection to obtain the Founder fish with positive transgenosis; s5, after the F0-generation positive fish is bred to be sexually mature, an F1 generation is obtained through mating, transgenic positive individuals with stable inheritance are screened out after identification, and a transgenic zebrafish strain is established. According to the transgenic zebrafish system pTo12-efla-tjp1a-P2A-mCherry based on the Tol2 transposon system and the construction method of the transgenic zebrafish system pTo12-efla-tjp1a-P2A-mCherry based on the Tol2 transposon system, efficient integration of exogenous genes is achieved by utilizing the Tol2 transposon system, and the transgenic zebrafish line capable of being stably inherited to the F1 generation is successfully obtained.

The invention discloses an antibacterial peptide generating and screening method based on a conditional potential diffusion model, which comprises the following steps: modeling antibacterial peptide sequence distribution in a continuous submerged space, realizing controllable generation of antibacterial peptide sequences through conditional constraints, and improving the efficiency and reliability of an antibacterial peptide discovery process by combining a multi-stage calculation screening and experimental verification strategy; therefore, the problem that in an existing antibacterial peptide design method, due to the factors that the sequence space scale is huge, the generation process is difficult to control, the candidate sequence redundancy is high, and the screening cost is high, the antibacterial peptide discovery efficiency is limited is solved. According to the method, a conditional diffusion generation mechanism is introduced into a continuous submerged space, and a multi-stage screening process formed by calculation screening and experimental verification is combined, so that systematic design and optimization of an antibacterial peptide sequence from data driven generation to performance evaluation are realized.

A peptide sequence mimicking endogenous cofilin-1 incorporates transmembrane amino acid sequences to enhance cellular uptake of the peptide drug. When cofilin peptide drugs are introduced into cancer cells, they affect cancer cell migration and invasion abilities. Furthermore, the peptide sequence can be conjugated with a chelator for cancer diagnosis.

Provided herein are computer-implemented methods of generating a disease map of a population. In some embodiments, the methods include applying a clustering algorithm to a set of weight and bias values of a trained electronic neural network to generate the disease map of the population. In some embodiments, the electronic neural network has been trained on training data that comprises representations of peptide sequence and binding value pair data sets obtained from reference subjects in the population in which a given peptide sequence and binding value pair data set comprises peptide sequence information and peptide binding values of antibodies to peptides that comprises the peptide sequence information. In some embodiments, the antibodies are from a sample obtained from a given reference subject in the population and are indicative of one or more disease states. Related systems, computer readable media, and additional methods are also provided.

The invention relates to the technical field of safe conveying of oil and gas pipelines, in particular to a polypeptide type hydrate kinetic inhibitor screening method based on molecular simulation, which comprises the following steps: selecting target protein related to hydrate growth, and designing a polypeptide sequence; performing polypeptide pre-screening; evaluating the binding affinity and binding mode of the polypeptide and the target protein; performing MD simulation on the screened high-affinity polypeptide; verifying the binding affinity of the polypeptide and the target protein; and collecting all experiment and simulation data for statistical analysis, and optimizing the polypeptide sequence. The structure and function of the target protein are systematically analyzed by using a bioinformatics database and tools, it is ensured that the selected target plays an important role in hydrate formation, and meanwhile, a polypeptide sequence designed based on the target protein structure can effectively improve the binding capacity; and in the pre-screening and docking analysis process of the polypeptide, dynamic parameters are simulated and extracted by molecular dynamics, so that the interaction between the polypeptide and the target protein can be deeply understood.

The present invention relates to the field of vaccines, and in particular to a novel adjuvant polypeptide sequence and a use thereof. The adjuvant polypeptide sequence provided by the present invention comprises amino acid sequences of tetanus toxoid epitopes P2 and P16 and further comprises amino acid sequences of P30 and / or PX. The adjuvant polypeptide sequence aims to expand the coverage population of immune responses by increasing epitope diversity. In addition, the present invention uses an LNP (lipid nanoparticle) delivery system to introduce an mRNA encoding an adjuvant polypeptide and an initial antigen protein into a human body, thereby improving the immunostimulatory ability of the initial antigen. The adjuvant polypeptide sequence provided by the present invention and the initial antigen sequence are preferably fused, thereby simplifying the composition of mRNA in a nucleic acid vaccine and reducing the complexity of vaccine preparation.

The invention relates to the technical field of immune carriers, in particular to immune carrier microspheres loaded with individualized MHC-II binding polypeptide and vaccine preparation and application of the immune carrier microspheres loaded with the individualized MHC-II binding polypeptide. The core microsphere is loaded with individualized MHC-II binding polypeptide, the sequence of the MHC-II binding polypeptide is obtained by predicting and screening based on an HLA genotyping result, and each HLA allele corresponds to at least one high-affinity MHC-II binding polypeptide; and the shell is a glucan or other polymer coating layer. The preparation method has the advantages that the T epitope and the B epitope are separately subjected to immune competitive inhibition inside and outside the microspheres, so that a better immune effect is obtained. The antibody avoids cross reaction side effects; carrier molecule diversity is reduced, and side effects caused by T cell over-activation are avoided; th1 epitopes and Th2 epitopes can be contained in the microspheres, so that antibody immunity and T cell immunity functions are generated; the particle size of the microspheres is controllable, and the immunologic function can be achieved without adjuvants.

The present invention relates to methods of modulating an immune response using enhanced Ii-Key peptides and Ii-Key peptide hybrids comprising an enhanced Ii-Key peptide and one or more epitope peptide sequences.

The application provides a toxicity-enhanced neurotoxin recombinant protein and application thereof, and belongs to the technical field of biological medicine. The recombinant protein comprises a botulinum toxin type A receptor binding domain and at least one GM1 binding peptide inserted into the botulinum toxin type A receptor binding domain, and the recombinin protein can recognize and bind to ganglioside GM1. The short peptide sequence capable of binding to ganglioside GM1 is introduced into the botulinum toxin type A receptor binding domain to obtain the recombinant protein, the binding capacity of the recombinant protein to ganglioside GM1 is enhanced, the target recognition and binding capacity of the recombinant protein to the nerve cell membrane are improved, the overall affinity and endocytosis efficiency of the recombinant protein to the nerve cell are improved, and the neurotoxicity of the botulinum toxin is enhanced. The application not only improves the binding efficiency of BoNT / A in the in-vitro nerve cell model, but also shows a higher toxicity level in the functional verification, and shows a good clinical conversion prospect.

The present application relates to the preparation and application field of biological peptide, and more particularly to a hippocampus abdominalis peptide and its application in preparation of products for reducing uric acid and resisting gout. The amino acid sequence is shown as SEQ ID NO. 1, and the present application confirms the uric acid reducing effect through in vitro xanthine oxidase (XOD) and adenosine deaminase (ADA) inhibition experiments and cell experiments; on this basis, the uric acid reducing and gout resisting activity of the peptide sequence is further verified by means of a high uric acid animal model. This achievement provides a solid theoretical support for high-value development and utilization of hippocampus abdominalis, and research and development of products for reducing uric acid and resisting gout.

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.

The invention provides a compound comprising one, two, three or more non-natural HRC sequence of a viral spike peptide conjugated to a hydrophobic moiety via an optional linker. The hydrophobic moiety can be a membrane integrating ligand, such as a cholesterol, a sphingolipid, a glycolipid, a glycerophospholipid. The non-natural viral spike peptide is preferably a coronavirus spike protein characterized by one or more D-amino acids. The peptides of the invention inhibit viral fusion. The invention includes compositions for the delivery of compounds of the invention, such as pulmonary or nasal delivery. The invention also provides a method of treating or preventing a viral infection, including for example a SARS-CoV-2 (COVID-19) infection, in a subject in need thereof comprising administering an effective amount of a compound of the invention.

This invention relates to the field of biopharmaceutical manufacturing technology, and discloses a BCMA-targeting nanobody, its preparation method, and its application. The nanobody comprises a heavy chain single-domain binding domain, a helical conformation-constrained peptide chain, and an amphiphilic self-assembled polypeptide sequence. The helical conformation-constrained peptide chain forms a steric barrier between the binding domain and the polypeptide sequence through physical length, maintaining the monomeric conformation of the polypeptide sequence in a free state. When the binding domain is anchored at the receptor binding interface, the conformation-constrained peptide chain increases the local effective concentration of the polypeptide sequence within the confined space, inducing intermolecular topological assembly. This invention utilizes a kinetic phase transition mechanism to generate a binding state jump, maintaining the conformational activity of the composition in the circulatory system, reducing off-target toxicity, and prolonging the residence time at the receptor interface.

The application relates to the field of protein deconvolution analysis, in particular to a mass spectrum analysis method and device and an intelligent terminal. The mass spectrum analysis method comprises the following steps: obtaining a target spectrum, wherein the target spectrum is used for reflecting mass spectrum data of a protein peptide segment; determining a spectrum feature of the target spectrum based on a mass-to-charge ratio of the target spectrum; inputting the spectrum feature of the target spectrum into a preset deconvolution model to obtain an analysis category of the target spectrum, wherein the analysis category is used for reflecting a peptide sequence corresponding to the target spectrum. The mass-to-charge ratio of the target spectrum is used to obtain the spectrum feature, and the spectrum feature is input into the deconvolution model, and the analysis category is obtained through the deconvolution model. The application has the characteristics that the peptide sequence of the protein corresponding to the target spectrum can be effectively, accurately and quickly analyzed.

Disclosed herein are formulations, substrates, and arrays. Also disclosed herein are methods for manufacturing and using the formulations, substrates, and arrays. Also disclosed are methods for identifying peptide sequences useful for diagnosis and treatment of disorders, and methods for using the peptide sequences for diagnosis and treatment of disorders, e.g., celiac disorder. In certain embodiments, substrates and arrays comprise a porous layer for synthesis and attachment of polymers or biomolecules.

The present application relates to a kind of water gel support prepared by self-assembled polypeptide and the use of support obtained therefrom, the preparation method includes: 1) self-assembled peptide sequence is linked nerve growth factor analog peptide by covalent bond to obtain bonded functional polypeptide;2) macrophage is separated and cultured, and is induced to be " alternative activation " anti-inflammatory M2 macrophage, obtain culture supernatant and carry out filtration, obtain filtered cell culture supernatant;3) filtered cell culture supernatant is mixed with bonded functional polypeptide, obtain mixed solution and adjust the concentration of the mixed solution, the bonded functional polypeptide self-assembles and forms water gel support.The present application uses M2 macrophage condition culture supernatant to construct regenerative microenvironment, combines polypeptide functional water gel support, realizes better overall interaction, and prepares the water gel support that can supplement and regulate nerve regeneration, the support can promote nerve cell regeneration behavior, provides new selection for tissue engineering biomaterials.

The invention discloses oyster pallium hexapeptide with an effect of promoting osteogenesis as well as a preparation method and application of the oyster pallium hexapeptide. The amino acid sequence of the oyster pallium hexapeptide is Phe-Phe-Glu-Pro-Lys-Phe. Fresh oyster mantle is used as a raw material, pepsin and trypsin are used for hydrolysis and centrifugation to obtain supernate, then ultrafiltration is carried out to obtain filtrate with the molecular weight being 1000 Da or below, finally freeze drying is carried out, the sequence of oyster hydrolytic peptide is obtained through mass spectrum identification, and by means of a molecular docking technology and a database prediction simulation method, the oyster hydrolytic peptide is obtained. Oyster peptide with high osteogenesis promoting capacity is screened from a plurality of peptide sequences. The oyster hexapeptide obtained by the invention has the effects of improving osteoblast proliferation and differentiation capacity and improving dexamethasone-induced zebra fish bone loss, and can be used as a beneficial dietary supplement in related products for delaying bone loss.

A C-terminal fragment of insulin-like growth factor binding protein 2 (IGFBP2) containing 3 cysteine residues has been shown to spontaneously self-assemble into nanotube (NT) structures. These NTs can encapsulate drugs during the assembly process and then deliver their cargo intracellularly following binding to interns and endocytosis. The integrin-dependence of this process is mediated by the presence of a naturally occurring RGD motif within the peptide sequence. A particular advantage of such NTs is that by encapsulating small molecule drugs, tissues are protected from their adverse effects. Here, the use of NTs to deliver small drugs and biologics across the blood-brain barrier (BBB) by penetrating the CNS and delivering their cargo is described.

The invention discloses a blood brain barrier penetrating peptide prediction method based on multi-feature fusion and data enhancement. The method comprises the following steps: S1, constructing multiple groups of balance training sets and independent test sets; s2, combining the features extracted from the polypeptide sequences in the balance training set and the independent test set to generate an original feature matrix; s3, all features in the generated original feature matrix are used, and an optimal training set is selected according to the model performance on the independent test set; s4, calculating feature importance of all features, setting an optimal threshold value, and screening effective feature subsets; s5, using the optimal training set determined in the step S3 and the effective feature subset screened in the step S4, and adopting five-fold cross validation to train and optimize the model; and S6, performing feature extraction and normalization on a to-be-predicted polypeptide sequence, inputting the model optimized in S5, and outputting a prediction category and a prediction probability value. According to the method, efficient and accurate prediction of B3PPs is realized by constructing a balanced data set, integrating multi-dimensional features and optimizing a feature screening and classification model.

The invention belongs to the crossing field of marine biotechnology and bioinformatics, and particularly relates to a method for high-throughput identification of natural functional oligopeptides. At present, bottlenecks still exist in development and application of various functional oligopeptides such as penetrating peptides and antibacterial peptides in non-model species, and the high adaptability of the existing functional oligopeptides in complex and diverse non-model organisms is limited mainly due to differences (amino acid preference and receptor specificity) among species. Therefore, the invention provides a method for high-throughput identification of functional oligopeptides from natural sequences of organisms by means of machine learning. According to the method, based on a biological natural protein sequence, an oligopeptide sequence set meeting a preset length condition is generated through a sliding window strategy system, a deep machine learning model is utilized to perform high-throughput functional prediction on the oligopeptide sequence, and on the basis of performing'interruption-prediction-re-comparison 'on existing functional oligopeptides, the functional oligopeptide sequence set meeting the preset length condition is obtained. The comparison threshold value for accurately identifying the functional oligopeptide can be determined, and the natural functional oligopeptide existing in the protein sequence can be effectively identified based on the threshold value. The functional oligopeptide obtained by the method has strict screening of physicochemical properties of a machine learning model and high-adaptability biological characteristics formed in species evolution. According to the method, the direct application capability of the functional oligopeptide in non-model species is remarkably improved, and an accurate and high-throughput technical means is provided for efficient development and application of the functional oligopeptide in non-model organisms.

A system for binding peptide search for immunotherapy is presented. The system includes employing a deep neural network to predict a peptide presentation given Major Histocompatibility Complex allele sequences and peptide sequences, training a Variational Autoencoder (VAE) to reconstruct peptides by converting the peptide sequences into continuous embedding vectors, running a Monte Carlo Tree Search to generate a first set of positive peptide vaccine candidates, running a Bayesian Optimization search with the trained VAE and a Backpropagation search with the trained VAE to generate a second set of positive peptide vaccine candidates, using a sampling from a Position Weight Matrix (sPWM) to generate a third set of positive peptide vaccine candidates, screening and merging the first, second, and third sets of positive peptide vaccine candidates, and outputting qualified peptides for immunotherapy from the screened and merged sets of positive peptide vaccine candidates to support downstream clinical decision making.