Centroid mutation strategy-based differential evolution protein structure prediction method

Abstract

The invention discloses a centroid mutation strategy-based differential evolution protein structure prediction method. The method comprises the steps of firstly, performing ascending sort according to an energy value of each conformation and calculating an average energy error value of each conformation and the conformation with the lowest energy; secondly, selecting part of the conformations with the relatively low energy to calculate a centroid conformation; and finally, judging a search state of an algorithm according to the average energy error value so as to design different centroid mutation strategies for generating test conformations, namely, if the average energy error value is greater than a set threshold, designing a DE / rand-to-centroid / 1 strategy to perform mutation, replacing corresponding segments in the randomly selected conformation by extracting partial segments in the centroid conformation to generate the test conformation, or otherwise, designing a DE / centroid / 2 strategy to perform mutation, replacing the corresponding segments in the centroid conformation by extracting the segments in the randomly selected conformation to generate the test conformation. Therefore, the search efficiency and prediction precision of the algorithm are improved.

Description

technical field [0001] The present invention relates to the fields of biological informatics, intelligent optimization and computer application, in particular to a differential evolution protein structure prediction method based on centroid mutation strategy. Background technique [0002] In 1953, J.Watson and F.Crick published the DNA molecular double helix structure model in the British "Nature", marking the birth of molecular biology in a true sense; five years later, F.Crick proposed the "Center of Molecular Biology". The idea of ​​"law" reveals the general law of life genetic information transmission. As a key part of this law, the deciphering of the triple genetic code from DNA to protein amino acid sequence (referred to as "the first code") has been completed as early as 1965; however, the folding code from amino acid sequence to spatial structure (referred to as The "Second Code") has not yet been cracked. With the completion of the sequencing of the human genome i...

AI Technical Summary

Problems solved by technology

For optimization problems such as protein conformation, the absorption state is not necessarily the global optimal solution, which affects the prediction accuracy

[0005] Therefore, the existing population-based protein structure prediction methods are deficient in search efficiency and prediction accuracy, and need to be improved.

Images