Protein structure ab into prediction method based on firefly algorithm

A protein structure and firefly algorithm technology, which is applied in the de novo field of protein structure prediction based on the firefly algorithm, can solve the problems of high complexity, low prediction accuracy and low sampling efficiency, and achieve the effect of low complexity and high prediction accuracy.

Inactive Publication Date: 2017-02-22
ZHEJIANG UNIV OF TECH
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AI Technical Summary

Problems solved by technology

[0004] In order to overcome the disadvantages of low sampling efficiency, high complexity and low prediction accuracy in the existing protein structure prediction conformation space optimization method, the present invention proposes an ab initio method for protein structure prediction based on the firefly algorithm

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  • Protein structure ab into prediction method based on firefly algorithm

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Embodiment Construction

[0022] The present invention will be further described below in conjunction with the drawings.

[0023] Reference figure 1 , An ab initio method of protein structure prediction based on Firefly algorithm, the method includes the following steps:

[0024] 1) Given input sequence information;

[0025] 2) Parameter initialization: set population size popSize, iteration number generation, light attraction factor γ, position update step factor α;

[0026] 3) Population conformation initialization: According to the given input sequence, randomly generate popSize individuals, do length fragment assembly for each individual in the population, and calculate the fluorescence intensity Io, where length is the sequence length, Io=-E, E Is the protein conformation energy value calculated by RosettaSscore3 energy function;

[0027] 4) Sort the fluorescence brightness calculated in step 3) from large to small, so that the individual with the largest fluorescence brightness is p g ;

[0028] 5) Start...

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Abstract

The invention discloses a protein structure ab into prediction method based on a firefly algorithm. The method includes that under a basic firefly algorithm frame, a coarseness energy model is adopted to effectively lower conformational space dimension, group property of the firefly algorithm is utilized to guarantee diversity of protein conformation, segment assembling technology is adopted to initialize conformational group, a dihedral angle is used to express position of conformation in space according to a coarseness expression model of the protein conformation, energy ranking is adopted to determine a strongest luminous individual, position of the conformation is updated by calculating attraction degree among individuals, and approximately-natural-state conformation with lowest energy is acquired by searching in the conformational space. By applying the method in protein structure prediction, conformation high in predication accuracy and low in complexity can be acquired.

Description

Technical field [0001] The invention relates to the fields of bioinformatics and computer applications, and in particular to an ab initio method of protein structure prediction based on the firefly algorithm. Background technique [0002] Bioinformatics is a research hotspot in the intersection of life science and computer science. Bioinformatics research results have been widely used in gene discovery and prediction, gene data storage management, data retrieval and mining, gene expression data analysis, protein structure prediction, gene and protein homology relationship prediction, sequence analysis and comparison, etc. . The genome defines all the proteins that make up the organism, and the gene defines the amino acid sequence of the proteins. Although proteins are composed of a linear sequence of amino acids, they can only have corresponding activities and corresponding biological functions when they are folded to form a specific spatial structure. Understanding the spatia...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/18G06N3/00
CPCG06N3/006G16B20/00
Inventor 张贵军郝小虎周晓根王柳静李章维
Owner ZHEJIANG UNIV OF TECH
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