A 3D protein structure prediction method based on Monte Carlo local dithering and fragment assembly

Abstract

The invention discloses a method for predicting a protein three-dimensional structure based on Monte Carlo local shaking and fragment assembly. The method comprises the following steps that firstly, according to the difficult problem that search space of protein high-dimensional conformation space is complex, the effectiveness of fragment replacement is judged under a Rosetta force field model through the Monte Carlo statistical method according to a protein database configuration fragment bank; under a differential evolution group algorithm framework, the complexity of the search space is reduced through fragment assembly, meanwhile, false fragment assembly is removed through the Monte Carlo statistical method, and the conformation search space is gradually reduced through the diversity of an evolutionary algorithm, and therefore the searching efficiency is improved; meanwhile, a module with coarseness is adopted, a side chain is ignored, and cost of a search is effectively reduced. The method for predicting the protein three-dimensional structure based on Monte Carlo local shaking and fragment assembly can effectively obtain optimal local stable conformation and is high in predicting efficiency and good in convergence correctness.

Description

technical field [0001] The invention relates to the technical field of protein three-dimensional structure prediction in bioinformatics, in particular to a protein three-dimensional structure prediction method, which belongs to the application of modern intelligent optimization methods to protein three-dimensional structure prediction. Background technique [0002] Bioinformatics reveals the biological mysteries of large and complex biological data through the comprehensive use of biology, computer science and information technology. It is a hot spot of current research. Bioinformatics research results have been widely used in sequence alignment, protein alignment, gene recognition analysis, molecular evolution, sequence contig assembly, genetic code, drug design, biological systems, protein structure prediction, etc. Among them, protein structure prediction is an important branch in the field of bioinformatics. Anfinsen, the famous Nobel laureate in chemistry, showed that...

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Problems solved by technology

[0007] In order to overcome the shortcomings of using a single modern evolutionary algorithm to predict the three-dimensional structure of proteins in the prior art, it is easy to fall into the minimum value, it is difficult to obtain the global optimal stable concept, the prediction efficiency is low, and the shortcomings of wrong convergence

The present invention combines the Monte Carlo statistical simulation method with the existing known knowledge base, and proposes a protein three-dimensional structure prediction method based on Monte Carlo local shaking and fragment assembly, which effectively obtains the local optimal stable concept, and has high prediction efficiency , the convergence accuracy is better, making up for the existing search space is too complex and the above defects

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