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A Phased Protein Structure Prediction Method Based on Population Entropy

A protein structure and prediction method technology, applied in the field of staged protein structure prediction based on population entropy, can solve the problems of low search efficiency and prediction accuracy, and achieve the effect of improving exploration performance

Active Publication Date: 2021-08-03
ZHEJIANG UNIV OF TECH
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AI Technical Summary

Problems solved by technology

[0007] In order to overcome the disadvantages of low search efficiency and prediction accuracy in existing conformation space optimization methods, the present invention provides a staged protein structure prediction method based on population entropy with high search efficiency and prediction accuracy

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  • A Phased Protein Structure Prediction Method Based on Population Entropy
  • A Phased Protein Structure Prediction Method Based on Population Entropy

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Embodiment Construction

[0072] The present invention will be further described below in conjunction with the accompanying drawings.

[0073] refer to figure 1 and figure 2 , a phased protein structure prediction method based on population entropy, including the following steps:

[0074] 1) Input the sequence information of the predicted protein;

[0075] 2) Setting parameters: population size NP, maximum number of iterations G 1 , G 2 , the crossover probability CR, the number of clusters K;

[0076] 3) Population initialization: Iterate the first and second stages of the Rosetta protocol to generate a population with NP individuals P={P 1 ,P 2 ,...,P NP};

[0077] 4) Exploration phase, the process is as follows:

[0078] 4.1) Let g 1 = 1, where g 1 ∈{1,2,...,G 1};

[0079] 4.2) Let n 1 = 1, where n 1 ∈{1,2,...,NP};

[0080] 4.3) order Indicates the nth in the population P 1 individual;

[0081] 4.4) Variation operation, the process is as follows:

[0082] 4.4.1) Randomly sele...

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Abstract

A staged protein structure prediction method based on population entropy, under the framework of differential evolution algorithm, uses the transition between individual states in the population to select different mutation strategies to achieve a balance between global detection and local enhancement. In the exploration stage, the crowding-out strategy is used to ensure the diversity of the population in evolution; in the enhancement stage, the Markov model is constructed according to the transition between individual states in the population, and the entropy of the population is calculated according to the Markov type, and then according to The calculated entropy information guides the selection of mutation strategies in the next generation population, so as to achieve a balance between global detection and local enhancement, avoid falling into local optimum while continuously searching for better conformations, and improve the exploration performance of conformation space. The invention provides a staged protein structure prediction method based on population entropy with high search efficiency and prediction accuracy.

Description

technical field [0001] The invention relates to the fields of bioinformatics and computer applications, in particular to a method for predicting protein structures in stages based on population entropy. Background technique [0002] Protein is the main bearer of life activities. There are many types of proteins in the human body, and each protein has a specific function. A protein is a substance with a certain spatial structure formed by folding a polypeptide composed of amino acids in a "dehydration condensation" manner. The specific spatial structure of proteins determines their specific functions. Diseases such as familial hypercholesterolemia and cataracts are caused by changes in the spatial structure of proteins, resulting in the loss of their functions. If the spatial structure of the protein can be determined, it will help people understand its specific function more comprehensively and design new drugs to fight diseases. [0003] The methods for determining the th...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G16B15/00G16B40/00
Inventor 张贵军刘俊王柳静彭春祥周晓根郝小虎
Owner ZHEJIANG UNIV OF TECH