Residue interaction network comparison algorithm SI-MAGNA introducing sequence information

A technology for introducing sequences and sequence information, applied in the field of residue interaction network alignment algorithm SI-MAGNA, which can solve problems such as unseen algorithms and unseen residue interaction network alignment algorithms, and achieves improved accuracy and reasonableness. The effect of stability, high EC, high edge correctness

Active Publication Date: 2018-02-09
JIANGNAN UNIV
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  • Abstract
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Problems solved by technology

However, there is no algorithm for residue interaction network alignment in the literature and patents, let alone an algorithm that introduces protein sequence information into residue interaction network alignment

Method used

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  • Residue interaction network comparison algorithm SI-MAGNA introducing sequence information
  • Residue interaction network comparison algorithm SI-MAGNA introducing sequence information
  • Residue interaction network comparison algorithm SI-MAGNA introducing sequence information

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Embodiment Construction

[0037] (1) In this paper, three groups of residue interaction network pairs are selected as the input of the algorithm, namely: (a) ADP-ribose pyrophosphatase from Thermus thermophilus (PDB number: 1V8I) and the structure from Mycobacterium tuberculosis Hydrolase (PDB number: 1MP2); (b) Type Ⅲ antifreeze protein isoform (PDB number: 9AME) from high-latitude temperate sea fish and sialic acid synthase (PDB number: 1WVO) from humans; ( c) Wild mesophilic lipase from Bacillus subtilis (PDB number: 1I6W) and its two thermophilic mutants (PDB number: 3D2B and 3QMM). The three-dimensional structure information and sequence information of different protein pairs were obtained from the RCSB PDB database (http: / / www.rcsb.org / pdb / home / home.do), and the BLAST algorithm was used for sequence alignment; and the residue-residue Based on the interaction of residues, the interaction network of residues is constructed, and then the network comparison is carried out.

[0038] (2) Use the SI-MA...

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Abstract

The invention discloses a residue interaction network comparison algorithm SI-MAGNA introducing sequence information, and belongs to the technical field of computer application. According to the method, based on a MAGNA comparison algorithm framework completely depending on network topology information, a sequence information similarity score of protein is introduced in an optimization function ofthe framework and an SI-MAGNA algorithm is proposed. The fitness values of population members are calculated; two parent comparisons are optimized through a cross function to generate a child comparison with a higher fitness value; iterative loop is performed; when a stop condition is met, the loop exits; and a comparison result is output. By utilizing the accuracy of the algorithm SI-MAGNA in residue interaction network comparison, a conserved region on a protein structure can be discovered, so that a similar structure realizing a similar function and a unique structure generating differenceare found, and an effective means is provided for researching relationships between a protein space structure and protein properties and functions from a system perspective.

Description

technical field [0001] The invention is a residue interaction network comparison algorithm SI-MAGNA which introduces sequence information, and belongs to the field of computer application technology. Specifically, based on the MAGNA network comparison method, a residue interaction network comparison algorithm SI-MAGNA that introduces protein sequence information is proposed to discover the conserved regions on the structure of two proteins, so as to find similar structures that achieve similar functions and generate differences. This method can be applied in many fields such as molecular design, molecular screening, drug design, etc. Background technique [0002] With the development of experimental measurement technology, a large amount of molecular interaction data, also known as biological network data, has been generated, such as: protein-protein interaction network, metabolic network, residue interaction network, gene expression network, etc. This makes biological netw...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/00
CPCG06N3/002G06N3/006
Inventor 丁彦蕊陶斯涵
Owner JIANGNAN UNIV
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