Differential evolution protein structure prediction method based on optimization of distance between residues

Abstract

An inter-residue distance optimization-based differential evolution protein structure prediction method comprises the following steps: under the framework of a differential evolution algorithm, firstly, initializing a population, and constructing an energy function according to distance information; secondly, performing crossover variation on conformations in the population, performing conformation space detection, then performingdistance optimization on the current conformation, and performing selection operation according to energy and updating the population; and finally, outputting the conformation with the lowest energy in the population as a prediction result. According to the differential evolution protein structure prediction method based on residue distance optimization, an energy model based on distance information is constructed, the problem of inaccurate traditional energy is relieved, local detection is enhanced by using a distance optimization method under the framework of an evolutionary algorithm, and the prediction precision and efficiency of the protein structure prediction method are improved. The invention provides a differential evolution protein structure prediction method based on inter-residue distance optimization. The precision and efficiency of protein structure prediction can be effectively improved.

Description

technical field [0001] The invention relates to the fields of bioinformatics and computer applications, in particular to a differential evolution protein structure prediction method based on distance optimization between residues. Background technique [0002] As the main bearer of life activities, proteins have received extensive attention and research in the field of biology. Structure determines function, and understanding the three-dimensional structure of a protein is of great significance for understanding the function of a protein. With the completion of the Human Genome Project, genes are no longer mysterious to humans. The rapid development of sequencing technology has led to a rapid decline in the cost of protein sequencing. However, the speed of protein structure determination is far behind the speed of protein sequence determination. Existing protein structure determinations all use biological wet experiment methods, which are not only costly and time-consuming...

AI Technical Summary

Problems solved by technology

[0006] In order to overcome the inaccuracy of the existing energy function, the insufficient local search ability of the evolutionary algorithm, and the low search efficiency in the later stage, the present invention proposes a protein structure prediction method based on differential evolution based on distance optimization between residues. This method is based on the predicted The energy function is constructed from the distance information between residues, and the distance between protein residues is optimized based on the differential evolution framework, combined with Newton's method

Images