Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

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

Active Publication Date: 2019-01-29
ZHEJIANG UNIV OF TECH
View PDF7 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the shortcomings of low sampling efficiency and low prediction accuracy of existing protein conformation optimization methods, the present invention proposes a protein conformation space optimization method based on quantum evolutionary algorithm with high sampling efficiency and prediction accuracy

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A Quantum Evolutionary Algorithm Based Protein Conformation Space Optimization Method
  • A Quantum Evolutionary Algorithm Based Protein Conformation Space Optimization Method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0034] The present invention will be further described below in conjunction with the accompanying drawings.

[0035] refer to figure 1 , a protein conformational space optimization method based on a quantum evolutionary algorithm, comprising the following steps:

[0036] 1) Given an input sequence:

[0037] 2) Setting parameters: population size pop_size, iteration number generation;

[0038] 3) Population initialization: According to the given input sequence, pop_size population individuals p are generated to form the initial population, expressed as: Need to satisfy|α i | 2 +|β i | 2 =1, let α i = sinζ i , β i =cosζ i , where ζ∈[-120°,120°] represents the dihedral angle of amino acids in the input sequence ψ, when i is odd When i is even, ζ i = ψ j , i, j are serial number index values, n is the sequence length; 4) Perform initial quantum observation on each individual in the initial population:

[0039] 4.1) Let i=1, i∈{1,2,3,...,2n};

[0040] 4.2) Genera...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

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.

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

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G16B15/20
CPCG16B15/00
Inventor 张贵军郝小虎周晓根王柳静李章维
Owner ZHEJIANG UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com