Differential-evolution protein-structure head-beginning prediction method based on multistage sub-population coevolution strategy

Abstract

The invention discloses a differential-evolution protein-structure head-beginning prediction method based on the multistage subpopulation coevolution strategy. The differential-evolution protein-structure head-beginning prediction method includes the following steps that under a differential-evolution algorithm framework, the conformational space dimensionality is reduced through a Rosetta Score3 coarse-granularity knowledge energy model; an evolution population is divided into a plurality of subpopulations according to the similarity, coevolution is carried out on the subpopulations, and the individual diversity of the population can be improved; the evolutionary process is divided into three stages, different variation crossover strategies are adopted at different stages, and the premature convergence problem can be solved; the conformational space can be effectively sampled in cooperation with the high global searching ability of the differential-evolution algorithm, and the high-accuracy conformation close to the natural state is obtained through searching. Based on the differential-evolution algorithm, the differential-evolution protein-structure head-beginning prediction method based on the multistage subpopulation coevolution strategy is low in conformational space searching dimension and high in convergence speed and prediction accuracy.

Description

technical field [0001] The invention relates to the field of bioinformatics and computer application, in particular to a method for ab initio prediction of differential evolution protein structure based on multi-stage subgroup co-evolution strategy. Background technique [0002] Protein molecules play a vital role in the process of biological and cellular chemical reactions. Their structural models and bioactive states have important implications for our understanding and cure of many diseases. Only when proteins are folded into a specific three-dimensional structure can they produce their unique biological functions. Therefore, to understand the function of a protein, it is necessary to obtain its three-dimensional structure. [0003] The problem of protein structure prediction has attracted much attention since the 1950s, especially the method of ab initio prediction of conformational space optimization is a hot research topic in the fields of bioinformatics and computat...

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Problems solved by technology

[0005] In order to overcome the disadvantages of the existing protein structure prediction methods, such as high conformation space search dimension, slow convergence speed, and low prediction accuracy, the present invention proposes a conformation space search dimension with low conformation space search dimension and fast convergence speed based on the differential evolution algorithm. A fast and high-precision differential evolution protein structure ab initio prediction method based on the multi-stage subgroup co-evolution strategy, under the framework of the differential evolution algorithm, the Rosetta Score3 coarse-grained knowledge energy model is used to reduce the dimension of the conformational space; The similarity is divided into multiple sub-populations, and the co-evolution between sub-populations can increase the diversity of individual populations; the evolution process is divided into three stages, and different mutation crossover strategies are used in different stages to avoid premature convergence problems; The strong global search ability of the evolutionary algorithm can effectively sample the conformation space

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