A Quantum Evolutionary Algorithm Based Protein Conformation Space Optimization Method

A technology of quantum evolutionary algorithm and optimization method, which is used in the analysis of two-dimensional or three-dimensional molecular structure, bioinformatics, instruments, etc., can solve the problems of low sampling efficiency and low prediction accuracy, and achieve high sampling efficiency and prediction accuracy. Effect
CN106778057BActive Publication Date: 2019-01-29ZHEJIANG UNIV OF TECH

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
ZHEJIANG UNIV OF TECH
Publication Date
2019-01-29

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Abstract

Provided is a protein conformation space optimization method based on quantum evolutionary algorithm. The protein conformation space optimization method comprises the following steps: based on a framework of quantum evolutionary algorithm, with Rosetta Score3 as the optimum objective function, based on an amino acid sequence coarse-grained expression model, converting an energy calculation model into a dihedral angle optimization space energy model; encoding a dihedral angle individual expression of the amino acid sequence by means of real phase encoding; improving prediction precision by implementing the operation of quantum mutation through fragment assembly; by adopting quantum rotation gate, quantum updating individual population to achieve the purpose of partial adjusting the angle; through iterative evolutionary process, the algorithm will produce protein conformation with lower energy and reasonable structure. The protein conformation space optimization method has the advantage of quick acquisition of conformation of high prediction precision in the application of protein structure prediction.
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Description

technical field

[0001] The invention relates to the fields of bioinformatics and computer applications, in particular to a method for optimizing protein conformation space based on quantum evolutionary algorithms. 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, de novo prediction methods are the only option. Ab initio prediction methods must consider the following two factors: (1) protein structure energy function; (2) conformational space search method. T...

Claims

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