41 results about "Protein design" patented technology

The invention relates to the use of protein design automation (P DA) to generate computationally prescreened secondary libraries of proteins, and to methods and compositions utilizing the libraries.

The present invention relates to apparatus and methods for quantitative protein design and optimization.

The instant invention provides methods and implementing computer software for designing mutant proteins (or “Target Protein or TP”) that will preferentially bind one list of prespecified ligands (Active Ligands or AL) with respect to another list of ligands (The Inactive Ligands or IL).

Methodology for the automated design of proteins is disclosed. Various methods executed by a computer for generating probability matrices, protein sequences, combinatorial libraries of proteins, and optimization of various parameters related to protein design are disclosed. Methodology is applicable to the design and analysis of protein structures and protein sequences.

The present invention discloses methods and compositions comprising a group of novel expression cassettes which provide significantly improved levels of accumulation of Coleopteran inhibitory Cry3B and Cry3B variant amino acid sequences when these are expressed in plants. The preferred embodiments of the invention provide at least up to ten fold higher levels of insect controlling protein relative to the highest levels obtained using prior compositions. In particular, transgenic maize expressing higher levels of a protein designed to exhibit increased toxicity toward Coleopteran pests deliver superior levels of insect protection and are less likely to sponsor development of populations of target insects that are resistant to the insecticidally active protein.

A method for annotating a protein sequence or a subsequence thereof includes the steps of providing an input protein sequence or a subsequence thereof. The subsequence is defined as a central node of a graph or protein network. A subgraph of the graph is calculated including the central node, according to a predefined radius and weights and/or resistances of edges of the subgraph are also calculated. Annotated nodes in the subgraph are identified. Resistance values between the central nodes and each of the annotated nodes in the subgraph are calculated and a list of annotated nodes is outputted. Each of the annotated nodes has a characteristic calculated resistance value to the central node of the input protein sequence.

The invention relates to a method for extracting a protein-micromolecule interaction module. The method specifically comprises: firstly, performing quantitative description on atoms (or amino acids) forming a micromolecular binding pocket on protein according to properties of the atoms (or amino acids); secondly, estimating the distance between the every two pocket atoms (or amino acids), and establishing a distance matrix; thirdly, extracting categories of the pocket atoms (or amino acids) with similar properties by utilizing a clustering algorithm; and finally, performing post-processing to obtain the protein-micromolecule interaction module. The method can be applied to multiple aspects of bioinformatics research, protein design, drug screening, micromolecular chemical synthesis and the like.

The present invention relates to a top-down symmetric deconstruction approach which provides a novel alternative means to successfully identify a useful polypeptide “building block” for subsequent “bottom-up” de novo design of target protein architecture. The present invention also pertains to a novel peptides isolated by top-down symmetric deconstruction which may be useful for design or directed evolution of novel proteins with novel functionalities.

The invention relates to a method for designing proteins on the basis of polarizable force fields and pso (particle swarm optimization). The method includes steps of acquiring a plurality of proteins by the aid of a protein design template; optimizing each protein, in other words, searching certain rotamers in a rotamerlib, and creating a temporary particle by the aid of each found rotamer; computing the fitness of each temporary particle, and updating local optimal particles and neighbor optimal particles according to the fitness of each temporary particle; updating positions and speeds of all non-temporary particles; comparing the positions of all the neighbor optimal particles to acquire the global optimal positions; searching side-chain conformation combined spaces by the aid of particle swarms to acquire the optimized proteins. Each certain rotamer is the closest to sub-vectors of the corresponding particle which continuously moves in a 4n (four-dimensional) space. The method has the advantages that discrete problems are solved by the aid of pso, and the polarizable force fields are used as evaluation foundations by the aid of the high efficiency of pso; modification on the proteins can be predicted theoretically, and the proteins can be screened theoretically.

The invention relates to a protein structure design method and device based on deep learning. The method comprises the following steps: determining a gene sequence or molecular crystal structure information of a targeted protein according to a biomarker; inputting the gene sequence or molecular crystal structure information of the targeted protein into a geometric graph neural network model; generating an amino acid sequence by using the trained geometric graph neural network model; constructing a protein skeleton model according to the generated amino acid sequence and the homologous protein;and optimizing the protein skeleton model according to proteomics and molecular dynamics. According to the method, protein data is bound with corresponding DNA sequences and mRNA sequences, so that the interpretability and effectiveness of the generated amino acid sequences are improved, the screening, repeated adsorption, elution and amplification processes of protein design or verification arereduced, and the calculation amount of the model is reduced through a geometric graph neural network.

The invention relates to detection of a neutralizing antibody of an infectious bovine rhinotracheitis virus, in particular to a blocking ELISA kit for detecting the neutralizing antibody of the infectious bovine rhinotracheitis virus and application of the blocking ELISA kit. The invention provides a monoclonal antibody with neutralizing activity for resisting infectious bovine rhinotracheitis virus. The monoclonal antibody is secreted by hybridoma cells with the preservation number of CGMCC No.21015. The invention further provides a kit for detecting the neutralizing antibody of the infectious bovine rhinotracheitis virus. The kit comprises the monoclonal antibody. Based on the monoclonal antibody and truncated gD protein designed in the invention, a blocking ELISA method for detecting a neutralizing antibody of the infectious bovine rhinotracheitis virus is established, and the blocking ELISA method has the advantages of strong specificity, high sensitivity and good repeatability.

The present invention relates to method for raising biological function of protein. The method includes reasonable conventional protein design to determine the functional region related to the biological function of protein; substituting the gene in the functional region related to the biological function of protein with randomly changed primer segment and constituting mutant gene library in conventional gene engineering method; and the final directional protein evolution to screen out from the mutant gene library the protein with raised biological function. The method of the present invention can obtain protein with raised biological function, and is simple, practical and efficient.

A method for constructing a library of amino-acid sequences having a common structural fold, and a method for designing and selecting an amino-acid sequence having a desired affinity to a molecular surface of interest of a molecular entity, using the library, are provided herein. The methods are based on a stochastic sampling of backbone conformations and amino acid conservation patterns observed in experimentally available protein structures having the common structural fold.

A process for generating a synthetic engineered recombinant protein has been performed by providing an original protein design and the necessary probabilistic priors for random in silico assembly. Once the in silico synthetic protein is assayed using mathematic modeling, the proteins are then reverse translated into DNA. The DNA fragment, modifying the original DNA to obtain a first DNA fragment, wherein the modifying step comprising adding an antigen optimization sequence to the original DNA fragment, purifying the first DNA fragment, performing a DNA self-assembly or a ligation, adding an amplification linker to obtain a second DNA fragment, purifying the second DNA fragment, transferring the second DNA fragment into an expression vector, expressing the second DNA fragment into a synthetic engineered recombinant protein, as well as purifying the synthetic engineered recombinant protein.

The invention relates to methods for stably integrating a desired polynucleotide into a plant genome, comprising transforming plant material with a first vector comprising nucleotide sequences encoding TAL proteins designed to recognize a target sequence; transforming the plant material with a second vector comprising (i) a marker gene that is not operably linked to a promoter (“promoter-free marker cassette”) and which comprises a sequence homologous to the target sequence; and (ii) a desired polynucleotide; and identifying transformed plant material in which the desired polynucleotide is stably integrated.

Provided are methods for de novo design of proteins that are non-immunogenic when administered for therapeutic purposes. The methods involve protein design based on combinations of peptide fragments naturally encountered by the immune system.

The invention relates to a recombinant protein GSE used as a streptococcus suis vaccine. The amino acid sequence of the recombinant protein is SEQ ID NO. 1. Aiming at the problems that the cross protection effect between an inactivated vaccine and a low virulent vaccine of streptococcus suis is poor, and certain biosecurity exists, the recombinant protein designed on the basis of screening of streptococcus suis protective antigen epitopes can be used for preparing the streptococcus suis vaccine. The recombinant protein can be efficiently prepared under the safe condition and has good practicability.