A Method for Optimizing the Conformation Space of Multimodal Proteins Based on Composite Structural Features

Abstract

The invention discloses a multi-modal protein conformational space optimization method based on composite structure features. The method comprises the following steps that: on the basis of an evolutionary algorithm framework, RosettaScore3 is taken as an optimized objective function, and statistics is carried out to obtain three types of structure features, including the individual distance spectrum, the individual secondary structure spectrum and the individual dihedral angle spectrum of a population individual. Through a multi-modal strategy, algorithm sampling diversity is improved, offspring individuals are selected according to the structure features, the defect that an energy model is inaccurate can be effectively eliminated, and a prediction structure with high accuracy can be obtained through iterative evolution. The method has the advantages of being high in sampling efficiency, low in complexity and high in prediction accuracy.

Description

technical field [0001] The invention relates to the fields of bioinformatics and computer applications, and in particular to a multimodal protein conformation space optimization method based on composite structural features. Background technique [0002] Bioinformatics is a research hotspot in the intersection of life science and computer science. At present, according to the Anfinsen hypothesis, starting directly from the amino acid sequence, based on the potential energy model, using the global optimization method to search for the minimum energy state of the molecular system, so as to predict the natural conformation of the peptide chain with high throughput and low cost, has become the most important bioinformatics. one of the research topics. For low sequence similarity or peptides (small proteins <10 residues), de novo prediction methods are the only option. Ab initio prediction methods must consider the following two factors: (1) protein structure energy function...

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Problems solved by technology

[0004] In order to overcome the disadvantages of low sampling efficiency, high complexity, and low prediction accuracy of existing protein conformation optimization methods, the present invention proposes a composite structure-based method with high sampling efficiency, low complexity, and high prediction accuracy. Featured multimodal protein conformational space optimization method

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