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Protein conformation space sampling method based on multi-modal internal and external crossover

A spatial sampling and protein technology, applied in the field of computer applications and bioinformatics, can solve the problem of inability to balance conformational diversity and convergence speed, improve global search ability and local convergence speed, speed up algorithm convergence, and improve prediction accuracy. Effect

Active Publication Date: 2020-01-17
ZHEJIANG UNIV OF TECH
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AI Technical Summary

Problems solved by technology

[0006] In order to overcome the inability of existing protein structure prediction methods to balance conformational diversity and convergence speed, the present invention proposes an algorithm based on modal in-crossover and modal-outside crossover, and introduces crowding out strategy and greedy search strategy
By cross-using the two strategies, the conflict problem of fast convergence of the algorithm and maintaining diversity can be better solved

Method used

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  • Protein conformation space sampling method based on multi-modal internal and external crossover
  • Protein conformation space sampling method based on multi-modal internal and external crossover
  • Protein conformation space sampling method based on multi-modal internal and external crossover

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Embodiment Construction

[0040] The present invention will be further described below in conjunction with the accompanying drawings.

[0041] refer to figure 1 and figure 2 , a method for sampling protein conformation space based on multimodal inner-outer crossover, comprising the following steps:

[0042] 1) Input the sequence information of the predicted protein and read the sequence length L;

[0043] 2) Setting parameters: population size N, number of iterations G 1 , G 2 , crossover probability P c , the mutation operator F, the number of modes H;

[0044] 3) Initialize the population: Iterate the first and second stages of Rosetta to generate an initial population with N individuals P={P 1 ,P 2 ,...,P N};

[0045] 4) Let g 1 = 1, g 1 ∈{1,2,...,G 1};

[0046] 5) Perform crossover, mutation and selection operations on the population, the process is as follows:

[0047] 5.1) Mutation operation: for the target individual P i , randomly select two from the population that are differen...

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Abstract

A protein conformation space sampling method based on multi-modal internal and external crossover introduces an extrusion strategy and a greedy search strategy, the modal internal crossover and the greedy search strategy are beneficial to convergence of individuals to local extremum, and the model external crossover and the extrusion strategy are beneficial to maintaining of population diversity.After initialization of populations, continuous fragment assembly is performed, population individuals are divided into a plurality of modal sets, when modal internal crossover is executed, the extrusion strategy is executed for sampling conformations, when model external crossover is executed, the greedy search strategy is executed for sampling conformations, and therefore, the conflict problemsof algorithm rapid convergence and diversity keeping can be well solved by using the two strategies in a crossed mode.

Description

technical field [0001] The invention relates to the fields of bioinformatics and computer applications, in particular to a protein conformational space sampling method based on multimodal internal and external crossover. Background technique [0002] Protein structure prediction is an important content of genome function research, and it is an urgent problem to be solved in the field of bioinformatics. Proteins are important units for sustaining life, such as enzyme proteins that catalyze biochemical reactions, carrier proteins that transport oxygen and nutrients, antibody proteins that are responsible for signal recognition or participate in immune reactions, and so on. The function and structure of protein are closely related. Only the amino acid sequence with a certain spatial structure can exert its specific biological function. The research on protein structure prediction tries to decipher the second genetic code and find out the connection between amino acid sequence a...

Claims

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Application Information

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IPC IPC(8): G16B5/20G16B20/20G16B30/10G06K9/62
CPCG16B30/10G16B20/20G16B5/20G06F18/23213
Inventor 张贵军赵凯龙夏瑜豪刘俊彭春祥周晓根
Owner ZHEJIANG UNIV OF TECH