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Dynamic fragment length based population protein structure prediction method

A technology of protein structure and prediction method, applied in the field of population protein structure prediction based on dynamic fragment length, can solve the problems of low prediction accuracy and search efficiency, and achieve the effect of maintaining diversity, speeding up search speed and improving search efficiency.

Active Publication Date: 2019-01-04
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0006] In order to overcome the shortcomings of low prediction accuracy and search efficiency of existing protein structure prediction methods, the present invention proposes a group protein structure prediction method based on dynamic fragment length with high prediction accuracy and search efficiency

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  • Dynamic fragment length based population protein structure prediction method
  • Dynamic fragment length based population protein structure prediction method
  • Dynamic fragment length based population protein structure prediction method

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Embodiment Construction

[0031] The present invention will be further described below in conjunction with the accompanying drawings.

[0032] refer to Figure 1 ~ Figure 3 , a population protein structure prediction method based on dynamic fragment length, comprising the following steps:

[0033] 1) Input the sequence information of the protein to be tested, and obtain the fragment library from the ROBETTA server (http: / / www.robetta.org / );

[0034] 2) Parameter setting: set the population size NP, the crossover probability CR, the temperature factor KT, and the maximum number of iterations G max , fragment length set l={l 1 , l 2 ,...,l M}, the selection probability p of each segment length m , m=1,2,...,M, and initialize the number of iterations g=0, where M is the scale of the fragment length set;

[0035] 3) Randomly select fragments from the fragment library corresponding to each residue to assemble to generate the initial conformation population P initial ={C 1 ,C 2 ,...,C NP}, where C ...

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Abstract

The invention discloses a dynamic fragment length based population protein structure prediction method. For each target conformation, half of conformation individuals can be randomly selected from a current population to establish a subpopulation, ordering can be performed on the population according to energy values, and a conformation can be randomly selected from top ranked conformations to guide variation; and during a variation process, multiple fragment lengths can be designed, selected probability can be calculated according to the previous success rate of each fragment length, and a fragment length can be selected to perform fragment exchange based on selection probability according to the way of roulette so that variation process can be realized. Thus, the dynamic fragment lengthbased population protein structure prediction method with high prediction precision and searching efficiency is provided.

Description

technical field [0001] The invention relates to the fields of biological informatics, intelligent optimization and computer application, and in particular to a group protein structure prediction method based on dynamic fragment length. Background technique [0002] In 1965, Nirenberg and Khorana discovered the triplet genetic code (that is, the first genetic code). DNA is translated into a protein amino acid sequence (that is, the primary structure of the protein) with a codon of three nucleotides; Only by forming a specific three-dimensional structure (that is, the tertiary structure of the protein) can its specific biological function be produced. Relative to the first genetic code, the correspondence between the primary structure of a protein sequence and its tertiary structure (ie, the second genetic code or folding code) remains an unsolved mystery. In order to solve the "problem of the century" of protein folding, more and more researchers with different disciplinary ...

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Application Information

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IPC IPC(8): G16B20/00
Inventor 周晓根张贵军彭春祥胡俊刘俊
Owner ZHEJIANG UNIV OF TECH
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