Lower bound estimation strategy adaptive protein structure prediction method

A protein structure and prediction method technology, applied in the field of lower bound estimation strategy adaptive protein structure prediction, can solve the problems of poor population diversity, low prediction accuracy, and low sampling efficiency.

Active Publication Date: 2019-02-15
ZHEJIANG UNIV OF TECH
View PDF4 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] In order to overcome the shortcomings of the existing protein structure prediction methods, such as low sampling efficiency, poor population diversity, and low prediction accuracy, the present invention introduces a strategy adaptive method to guide conformational space optimization under the framework of the basic differential evolution algorithm, and proposes a sampling An adaptive method for protein structure prediction with lower bound estimation strategy with high efficiency and high 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
  • Lower bound estimation strategy adaptive protein structure prediction method
  • Lower bound estimation strategy adaptive protein structure prediction method
  • Lower bound estimation strategy adaptive protein structure prediction method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0044] The present invention will be further described below in conjunction with the accompanying drawings.

[0045] refer to Figure 1 ~ Figure 3 , a lower bound estimation strategy adaptive protein structure prediction method, the prediction method comprises the following steps:

[0046] 1) The sequence information of the given target protein;

[0047] 2) Obtain fragment library files from the ROBETTA server (http: / / www.robetta.org / ) according to the target protein sequence, including 3-fragment library files and 9-fragment library files;

[0048] 3) Setting parameters: population size NP, maximum iteration algebra G of the algorithm, crossover factor CR, temperature factor β, learning period LP, probability of the first mutation strategy being selected The probability that the second mutation strategy is chosen The probability that the third mutation strategy is chosen The probability that the fourth mutation strategy is selected g represents the current generation...

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

The invention relates to a lower bound estimation strategy adaptive protein structure prediction method. Under the evolutionary algorithm framework, firstly, a population is initialized, according tothe method of roulette, different strategies are chosen to mutate and cross the conformation; secondly, according to a lower bound estimation function, a Rosetta energy function score3 and the Monte Carlo probability acceptance criterion, the conformation is selected to guide the conformation update process, and the strategy selection probability is dynamically updated according to the historicalinformation of conformation update. The method is advantaged in that not only can a problem of inaccuracy of the energy function be alleviated, but also the conformation with lower energy and the morereasonable structure can be obtained by using historical information-guided algorithm sampling, sampling efficiency is improved, and the method further has properties of relatively high sampling efficiency and prediction precision.

Description

technical field [0001] The invention relates to the fields of bioinformatics and computer applications, in particular to a lower bound estimation strategy adaptive protein structure prediction method. Background technique [0002] The rapid development of computer hardware and software technology provides a solid basic platform for the development of ab initio prediction methods. In a review article published in the journal Science in 2012, Professor Dill, an academician of the American Academy of Sciences, reviewed the progress made in the field of de novo prediction in the past 50 years, and pointed out that in the process of seeking answers to this question, supercomputers, new The development of materials and drug discovery that aids in understanding the fundamental processes of life. Ab initio prediction methods are still facing many difficulties and challenges. [0003] Ab initio prediction methods are directly based on protein physics or knowledge-energy models, and...

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 Applications(China)
IPC IPC(8): G16B15/30G16B30/10G06N3/00
CPCG06N3/006
Inventor 张贵军彭春祥刘俊周晓根王柳静胡俊
Owner ZHEJIANG UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products