42 results about "Interactions protein" patented technology

The invention provides an isolated nucleic acid encoding NRIP (Nuclear Receptor Interaction Protein) gene that highly expressed in tumorigenic development of human neoplasms in cervical cancer. The invention provides an antibody against the NRIP protein, and methods of diagnosing the NRIP related cancer. The invention also features RNA interferences of the NRIP gene, and the methods of treatment for the NRIP related cancer using the RNA interferences.

The invention relates to a plan protein interaction network constructing method based on deep learning. The method comprises the following steps of 1), acquiring 11 characteristic data of a protein interaction pair; 2), performing screening for obtaining a training set and a testing set; 3), constructing a deep learning classification model; 4), performing batch optimization on the parameter of the deep learning classification model, and obtaining a classification model of an optimal optimization parameter combination; 5), performing interaction relation predicting on all possible two-to-two interaction proteins of the whole genome according the classification model of the optimal optimization parameter combination; and 6), predicting the protein interaction network according to an interaction relation predicting result. Compared with the prior art, the method has advantages of high predicting accuracy, high modeling efficiency, etc.

Protein-protein interaction (PPI) is important for all biological processes; therefore, the research of protein interaction is always a research hot in the fields of cell biology and molecular biology. The co-immunoprecipitation (CoIP) is a classic method which is used to research protein interaction based on the specific action between antibody and antigen and is the commonest and most effective method to find and testify PPI; the traditional CoIP steps based on a resin are complicated and labor consuming and are hard to realize the flux detection. The key point in the invention is that CoIP is implemented on glass aldehyde sheet of the fixed anti-label antibody by utilizing the epitope label of recombinant protein; protein-protein interaction (PPI) is detected by the antibody labeled by fluorescence. The method greatly simplifies the operation steps of the traditional CoIP, greatly improves the flux of sample detection and is a novel technique platform to research PPI simply, conveniently and swiftly and with high flux.

The invention discloses a library versus library yeast two-hybrid massive interaction protein screening method. The method takes a genome-grade cDNA as the bait to screen the genome-grade cDNA library. In the application process of the method, the cDNA library is subjected to a homogenization treatment so as to reduce the masking effect of the high-abundance interaction proteins to the low-abundance interaction proteins, and thus the screening efficiency is improved; and moreover the characteristic of yeast URA3 gene is utilized so as to automatically remove the sequences, which have the self-activating function, in bait cDNA. The invention establish a library versus library yeast two-hybrid massive interaction protein screening method, which has the advantages of high feasibility, low cost, low requirements on experiment conditions, and low workload; and successfully applies the method to a screening of pathogen-host plant interaction proteins.

The invention discloses application of a calcineurin B protein interaction protein kinase gene HsCIPK17 of annual Hordeum spontaneum C. Koch in the Qinghai-Tibet Plateau: the HsCIPK17 is used for constructing Oryza sativa L.; the Oryza sativa L. has heavy metal stress tolerance and also has salt tolerance and abscisic acid stress tolerance; heavy metals are mercury, cadmium and chromium; a nucleotide sequence of the gene HsCIPK17 is that the GenBank accession number is JN655677.

The invention discloses a key protein identification method use principle in a network based on dynamic weighting interaction. A key protein identification method comprises the steps of calculating aprotein activity time point and a protein activity probability, constructing a dynamic PPI network, then calculating a protein interaction weight according to the protein activity probability, and constructing a dynamic weighted PPI network; based on the established dynamic weighted PPI network, according to the topological characteristic and biological attribute of the protein network, calculating an edge clustering coefficient, a gene body similarity and a Pearson correlation coefficient between the interaction protein pairs; afterwards, obtaining an importance score, and performing arrangement according to the score value from largest to lowest, and outputting k proteins which correspond with the scores as a final result. The method according to the invention improves key protein identification efficiency and expands application range and practicability of the technique in a bioinformation field.

The invention relates to the technical field of genetic biology, in particular to a method screening MKL-1 protein interaction proteins via yeast two-hybrid screening. A recombinant yeast capable of expressing bait protein MKL-1 is prepared, cDNA library is transformed to the recombinant yeast, the two nutrient defects, His and Ade, and chromogenic reaction are used alone or in combination, and positive clones having different interactive intensities to the protein MKL-1 are acquired by further screening. By means of gradually increasing the selective pressure, it is convenient to quickly screen out proteins having different interactive degrees to the protein MKL-1, subsequent validation experiments are facilitated, and the method is significant to further elaboration of the functionality and regulatory effect of MKl-1 in the genesis and development of leukemia.

The invention discloses a protein identification method based on a protein interaction network and proteomics. The method is based on the phenomenon that the existence probabilities between interaction proteins are influenced mutually. Protein interaction network information is fused with shotgun method proteomics data, a new protein identification graph model is defined, the probability of peptide mapped to the proteins is adjusted by means of the existence probability of the proteins in the graph model and the support degree of neighbor protein nodes obtained in the graph model, and therefore the existence probability of the proteins is adjusted. Most proteins can be identified through the method. Compared with other identification methods, the protein identification method based on the protein interaction network and the proteomics has high accuracy. Valuable reference information is provided for experiments for inference and identification of proteins of biologists through proteomics data and further study.

The invention provides a target PPIs drug property prediction method based on a protein interaction network. The method at least comprises the following steps: S1, detecting the interaction relationship of interaction protein structural domains in the PPI network; S2, detecting a drug small molecule binding pocket on the surface of interaction protein in the PPI network; S3, obtaining a GO function similarity score of the interactive protein in the PPI network; S4, screening out PPIs meeting the following conditions at the same time to serve as drug therapy targets: protein interaction relationship pairs have structural domain interaction; in the protein interaction relationship pair, at least one protein surface has a small molecule drug binding pocket; at least two of the GO function categories of the interaction proteins of the protein interaction relationship pair have significant similarity, and the GO function categories comprise GO BP, GO MF and GO CC. According to the method, three strict mutually independent standards are adopted to comprehensively explore and discover the target PPI, false positive interaction is systematically eliminated, more reliable PPIs are selectedas drug targets, and the calculation result better conforms to objective reality.

The invention discloses a known molecule and protein interaction detection system based on covalent linkage and an identification or verification method thereof. The detection system comprises: a) a streptavidin-oligopeptide tetramer; b) a PafA enzyme; and c) biotin-modified known molecules. Known molecules are labeled with biotin, after the known molecules interact with proteins, interaction proteins of the known molecules are efficiently captured through the streptavidin-oligopeptide tetramer under mild conditions, and then under catalysis of PafA enzyme, oligopeptide and the known molecules are in covalent linkage with the interaction proteins, therefore, non-covalent binding between the interacting known molecules and the protein is converted into covalent linkage between the streptavidin and the protein, and analysis, separation and identification are carried out. The method can realize capture of weak interaction and instantaneous interaction on the basis of keeping the natural structure of known molecules, and can be used for verification and discovery of known molecules and interaction proteins.

The invention provides a luciferase fluorescence-complementary system as well as a preparation method and application thereof. The luciferase fluorescence-complementary system comprises Rab1, SidM/DrrA, a luciferase C-terminal, a luciferase N-terminal, linker peptides and a reducer TCEP; the C terminal of the Rab1 is connected with the luciferase N-terminal by a linker peptide; and the SidM/DrrA is connected with a luciferase C-terminal fragment by a linker peptide. By introducing specific interaction protein pairs, designing appropriate flexible peptides and binding sites as well as optimizing type and concentration of a reducer in a buffer solution, the luciferase fluorescence-complementary system finally has significantly increased fluorescence complementary efficiency; and the fluorescence complementary efficiency can be increased to up to 30 times. Moreover, the preparation method of the luciferase fluorescence-complementary system provided by the invention is simple and highly efficient, so that, the preparation method is convenient to operate, easy to promote, wide in application prospects and high in market values.

The present invention provides a kit for diagnosing the cardiomyopathy comprising an antibody or oligonucleotide for measuring an expression level of nuclear receptor interaction protein (NRIP). The present invention also provides a method of predicting a risk of cardiomyopathy for a subject. The present invention further provides a method of screening an agent for treating cardiomyopathy.

The present invention provides a method for evaluating physiological state of motor neurons in a subject. The method comprises detecting an expression level of a nuclear receptor interaction protein (NRIP) in a biological sample from the subject; and comparing the expression level of the NRIP to a control value for NRIP; wherein detecting a decrease of the expression level of the NRIP in the biological sample from the subject as compared to the control value for NRIP indicates an abnormal function of the motor neurons of the subject

The invention discloses a construction method of yeast two-hybird bait vectors for screening ASICs interaction proteins, belonging to the technical field of biology. According to the construction method, subunit extracellular loop genes ASIC1a and ASIC2a in acid-sensitive ion channels (ASICs) are respectively cloned to a yeast two-hybird bait vector pGBKT7 by virtue of a gene engineering technique so as to successfully construct two yeast two-hybird bait vectors pGBKT7-ASIC1a and pGBKT7-ASIC2a, the expression and identification of the constructed vectors are realized, and the recombinant bait vectors are proved to be applicable to a yeast two-hybird system, so that an important experimental foundation is laid for screening the ASICs interaction proteins by virtue of the yeast two-hybird system and further researching and establishing an ASICs regulation and control machine, and a new direction is opened up for the treatment of inflammatory pain.

The invention belongs to the technical field of biology, and relates to a method for identifying and analyzing specific locus interaction proteins on the basis of a CRISPR/cas9 and peroxidase APEX2 system. The method comprises the following steps: plasmid transformation; biotin labeling of specific locus binding protein complex; enrichment of biotin-labeled protein complex by utilizing streptomycin magnetic beads; and assay and analysis of enriched proteins. An experimental analysis result shows that the method is applicable to the research and analysis of protein at any given chromosomal location, and meanwhile, the idea that the method combines the CRISPR gene editing system with APEX2 to carry out specific locus protein analysis is also applicable to the combination of other genome editing methods (such as TALEN) and the APEX2. The method has the advantages of simplicity in operation, high sensitivity, high specificity, good repeatability and adaption to the requirement of the research of local chromatin interaction at any given chromosomal location.

The present invention discloses a protein interaction network construction method. The method comprises the following steps: acquiring a protein set that is interested in; constructing a first-level interaction protein database of a target protein, and drawing a first-level protein interaction network of the target protein according to the first-level interaction protein database; and constructing a second-level interaction protein database of the target protein, and in conjunction with the first-level protein interaction network of the target protein, drawing an interaction protein database of the target protein. Compared with the prior art, according to the method disclosed by the present invention the candidate database used when constructing the protein interaction network is comprehensive and extensive, and the idea of integrated use and expanded application of an existing database is novel; the protein interaction database can comprehensively and extensively store existing protein interaction relationships, the source is reliable, and the query is convenient; and a reliable basis is provided for experimental verification of unknown protein functions.

The invention discloses an experimental method for improving the corn amylose content by knocking out an SIP1 gene, and belongs to the field of genetic engineering.The method mainly comprises the following steps: constructing a CRISPR/Cas9-SIP1 gene knockout vector; and transforming target corn by agrobacterium to obtain a corn plant with the SIP1 gene knockout. According to the genetic engineering method, the content of amylose in corn kernels is improved by interfering the starch branching action of SIP1 in the participation of the main gene ZmSBEII. The realization of the method has important practical guiding significance for developing a new high-amylose corn variety by utilizing ZmSBEII interaction protein.

The present invention directs to a transgenic NRIP knockout mouse, the genome of which is manipulated to comprise a disruption of a nuclear receptor interaction protein (NRIP) gene, wherein the NRIP gene is disrupted by deletion of exon 2, the mouse exhibits a phenotype comprising abnormal muscular function. The present invention also directs to a method for making a transgenic NRIP knockout mouse whose genome comprises a homozygous disruption of the NRIP gene, the mouse exhibits abnormal muscular function.

The invention discloses a protein interaction prediction method based on a sampling strategy of non-interaction protein pairs fused with biological semantics. Protein pairs in different molecular functions, biological processes and cell components are sampled and combined based on GO term semantic similarity to obtain an NIPs subset. With a negative set sampling strategy, a non-protein interactiondata set with higher quality and low selection deviation is obtained, so that a protein interaction prediction model with better robustness and better prediction performance is obtained through training.

The invention discloses a research method for analyzing a Klotho interaction protein in non-small cell lung cancer which comprises the three steps, a screening of Klotho interaction protein, a verification of Rab8 and Klotho gene binds to one another, and the mechanism analysis of Rab8 and Klotho interaction. The present invention firstly finds that the presence of Rab8 and Klotho in non-small cell lung cancer cells binds to one another, and a co-location exist in the subcellular, Rab8 binds to Klotho through a protein synthesis pathway and promotes a transport thereof to the membrane surfacein the form of vesicles, so that the level of the surface of the membrane is increased.

The invention relates to yeast transformant for screening a protein with interaction with G protein beta-gamma dimer and a screening method of the yeast transformant. Yeast transformant has encoding genes of a beta-subunit and a gamma-subunit of mulberry, a mulberry cDNA (Complementary Deoxyribonucleic Acid) library is converted into the yeast transformant capable of simultaneously expressing thebeta-subunit and the gamma-subunit, two types of nutrition defect screening of His and Met are carried out to obtain positive cloning with interaction with beta-gamma dimer, and finally the protein with interaction with the G protein beta-gamma dimer of the mulberry can be successfully screened. By adopting the method, a protein dimer interaction protein can be efficiently screened, and the methodcan be successfully applied to screening on a mulberry G protein beta-gamma dimer interaction protein.

Various aspects and embodiments of the present disclosure relate to the purification antibodies by hydrophobic interaction chromatography under no-salt conditions.