Multi-strategy colony protein structure prediction method based on local abstract convexity supporting plane

Abstract

The invention discloses a multi-strategy colony protein structure prediction method based on a local abstract convexity supporting plane. The method comprises the steps of firstly generating three different new conformation individuals according to randomly chosen conformation individuals, a current target conformation individual and a conformation individual with a minimum energy value; then calculating the distance of each conformation individual in a current colony to each new conformation individual, and conducting ascending sort according to the distance; next, calculating an abstract convexity supporting plane of a partial conformation individual which is closest to each new conformation individual, and thus calculating an energy estimated value of each new conformation individual; finally, comparing the energy estimated value of each new conformation individual and thus choosing a new conformation individual with minimum energy estimated value to conduct energy function evaluation. The provided multi-strategy colony protein structure prediction method based on the local abstract convexity supporting plane is high in prediction accuracy and high in search efficiency.

Description

technical field [0001] The invention relates to the fields of biological informatics, intelligent optimization and computer application, and in particular to a multi-strategy group protein structure prediction method based on a local abstract convex support surface. Background technique [0002] Biological cells contain many proteins that are folded by long chains formed by more than 20 amino acids. The problem of protein structure prediction is a research hotspot in the field of computational biology today. , Interaction modeling between proteins, and the design of drug target proteins have very important guiding significance. At present, the most commonly used protein structure determination methods include X-crystal diffraction and nuclear magnetic resonance, but the above two protein structure determination methods have certain defects and cannot meet the needs of all protein structure predictions. For example, for some proteins that are not easy to crystallize, X-cryst...

AI Technical Summary

Problems solved by technology

However, for the above-mentioned swarm algorithm, the selection of new conformation generation strategy is very important. An inappropriate strategy will lead to low search efficiency and slow convergence speed of the algorithm, and even fall into local optimum, resulting in premature convergence, which will affect the prediction accuracy.

[0005] Therefore, existing conformational space optimization methods have shortcomings in search efficiency and prediction accuracy, and need to be improved

Images