69 results about "Protein Databases" patented technology

A method and system are disclosed for identifying and / or locating complex patterns in an amino acid sequence stored in a computer file or database. According to an aspect of the present invention, techniques are provided to facilitate queries of protein databases. For protein descriptions received in response to the queries, embodiments of the present invention may scan the received protein descriptions to identify and locate Replikin patterns. A Replikin pattern is defined to be a sequence of 7 to about 50 amino acids that include the following three (3) characteristics, each of which may be recognized by an embodiment of the present invention: (1) the sequence has at least one lysine residue located six to ten amino acid residues from a second lysine residue; (2) the sequence has at least one histidine residue; and (3) at least 6% of the amino acids in the sequence are lysine residues.

The term “homology” or “homologous” means an amino acid similarity measured by the program, BLAST (Altschul et al (1997), “Gapped BLAST and PSI-BLAST: a new generation of protein database search programs”, Nucleic Acids Res. 25:33 89–3402), and expressed as —(% identity n / n). In measuring homology between a peptide and a protein of greater size, homology is measured only in the corresponding region; that is, the protein is regarded as only having the same general length as the peptide, allowing for gaps and insertions.

The invention relates to a method for establishing a phylogenetic tree aiming at a target gene of a target organism. The method comprises the following steps of: 1) acquiring data; 2) comparing and analyzing sequences; and 3) establishing the phylogenetic tree, wherein the step 1) is finished by downloading a structure domain of a protein of the target gene, acquiring a sequence which contains the structure domain by searching a biological protein database of which genomes and proteomes are sequenced, and searching a protein sequence of a kindred plant by using the target gene of an organism of which the genomes and the proteomes are sequenced. Because the method of the invention comprises the steps and in particular combines the phylogenetic relationships of species with the database of which the genomes and the proteomes are sequenced, a more accurate phylogenetic tree can be established.

The invention discloses a method for rapidly identifying strain-level pathogenic bacteria in food through double adsorption. The method comprises main steps as follows: a) strain-level pathogenic bacteria in liquid food are adsorbed by MIL-101 magnetic particles, and wall breaking is performed under microwave assistance; after wall breaking, to-be-identified pathogenic bacterium protein is rapidlyenriched through the MIL-101 magnetic particles; b) a mass spectrum graph of the pathogenic bacterium protein is collected through MALDI / TOF MS (matrix-assisted laser desorption ionization / time of flight mass spectrometry); c) a Tagident search tool is used for performing protein database searching on mass spectrum peak, and ribosomal protein is selected; d) a rapid microorganism identification database is sought by use of ribosomal protein obtained through searching, and the attributes of the strain-level pathogenic bacteria are determined. The method has the advantages of simplicity and rapidness. Enrichment of pathogenic bacteria, wall breaking and mycoprotein enrichment are integrated, finally, a ribosomal protein database is used for rapidly identifying the pathogenic bacteria, and the strain level of pathogenic bacteria in the liquid food is rapidly identified.

The present invention relates a method for predicting a protein or polypeptide (B) that interacts with a specific protein or polypeptide (A), wherein the method is characterized by comprising: 1) decomposing the amino acid sequence of protein or polypeptide (A) into a series of oligopeptides having a pre-determined length as sequence information; 2) searching, within a database of protein or polypeptide amino acid sequences, for a protein or polypeptide (C) comprising an amino acid sequence for each member of the series or for a protein or polypeptide (D) comprising an amino acid sequence homologous to an amino acid sequence for each member of the series; 3) carrying out local amino acid sequence alignment between said protein or polypeptide (A) and the detected protein or polypeptide (C) or detected protein or polypeptide (D); and 4) predicting whether the detected protein or polypeptide (C) and / or protein or polypeptide (D) is a protein or polypeptide (B) that interacts with the protein or polypeptide (A) based on the results of the local amino acid sequence alignment and a value calculated from a frequency of amino acids and / or a frequency of said oligopeptides in said amino acid sequence database; and to a recording medium for carrying out the above method, a device comprising the recording medium, and proteins obtained thereby.

A method is provided to create lead compound(s) by discovering a general chemical structure, moieties, formula(s) to explore suitable compositions by computer simulation and / or robotic biological or biochemical experiments at least partially based upon employing said lead compound(s) discover method, which includes steps for inputting at least one chemical formula and at least one byproduct formula, steps for creating a list of dipeptides that might dissociate the byproduct from the input formula by way of catalysis, steps for using these dipeptides to fingerprint a protein from its peptide sequence, and searching a protein database or use experimental methods to search for such proteins. A composition creating means is provide by way of computer simulation and / or robotic biological or biochemical experiments at least partially based upon employing, as lead compound(s), the final chemical structure, moieties, formula(s) generated and communicated the above method.

The invention provides an index acceleration method in scale protein identification, which comprises the following steps of: setting quality intervals for peptide sequences; setting the size of counting windows, and setting the number of the counting windows and the range of each counting window by combining the quality intervals; performing simulated enzyme digestion on protein database, and calculating the quantity of the peptide sequences in each counting window according to the quality of the peptide sequences obtained through the simulated enzyme digestion; obtaining the quantity of the peptide sequences which can be processed once in the memory of a computer according to the capacity of the memory of the computer, and obtaining a quality range section of the peptide sequences which can be processed once in the memory of the computer by combining the quantity of the peptide sequences in each counting window; performing the simulated enzyme digestion on the protein database, saving the obtained peptide sequences in one quality range section in the memory of the computer, and finishing the operations of sequencing, redundancy removal, and dictionary and inverted list establishment on the saved peptide sequences in the memory of the computer; and establishing a dictionary and an inverted list for each quality range section.