Spatial search method for multi-modal protein conformations

Abstract

The invention provides a spatial search method for multi-modal protein conformations. According to the spatial search method, the thoughts of a spatial locality principle and an assembly process are integrated based on a crowding differential evolution algorithm, and the protein conformations obtained through experiments are processed by adopting an energy minimization process. Due to the spatial locality principle, the convergence rate of the algorithm is increased, and the problems of local convergence and modal diversity in multi-modal optimization are effectively solved; in the assembly process, different crossover strategies are randomly selected, so that better segments in the conformations are prevented from being damaged by the algorithm, and the diversity of the multi-modal protein conformations is improved; and due to the energy minimization process, the complexity of space solution of the protein conformations is reduced, and the search space of feasible zones of the protein conformations is effectively shortened. According to the spatial search method, enkephalin is taken as an example, not only is the well-known most global stable structure of the enkephalin obtained, but also a series of high-quality local stable structure are obtained, so that the problem of multi-gene and multi-target paths of diseases which cannot be solved by the traditional single-target-directed single-modal research method is solved, and the requirements of computer-aided drug design on multi-modal protein structures at the present stage are met.

Description

technical field [0001] The design of the present invention relates to the technical field of protein conformation space search, in particular to a multimodal protein conformation space search method based on crowding out differential evolution algorithm, which belongs to the comprehensive intersection technology of biological information technology, modern intelligent optimization method and computer virtual reality technology. Background technique [0002] On April 14, 2003, Dr. Collins F, chief scientist of the Human Genome Research Project of the United States, announced in Washington that the human genome sequence map was successfully drawn, and all the goals of the Human Genome Project (HGP) were fully realized, which marked the human genome project. Successful completion and the post-genome era (Post Genome Era, PGE) has come. In today's field of molecular biology, the research on the spatial structure and function of protein molecules is undoubtedly the most challengi...

AI Technical Summary

Problems solved by technology

[0007] Although some achievements have been made in multimodal protein conformation space search at this stage, protein conformation space search is still an important task in order to accurately, stably and effectively search the stable conformation of proteins while ensuring good modal distribution. Difficult task

The reason is that a reasonable multimodal protein conformation space search method must meet the following three conditions: first, there must be a reasonable potential function that can abstract the protein structure into a mathematical model; second, the protein energy model is a high-dimensional The non-convex function of the non-convex function, it is necessary to ensure that the algorithm finds the global optimum of the potential energy function in the effective calculation time; third, in the process of protein molecular design, the global stable conformation predicted by the algorithm may not meet the actual needs, so a new The algorithm not only obtains the global stable conformation of the protein faster, but also finds a series of high-quality local optimal conformations as much as possible

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