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

Multi-modal protein structure prediction method based on crowding-out strategy

A technology of protein structure and prediction method, which is applied in the field of multimodal protein structure prediction based on the extrusion strategy, which can solve the problem of insufficient search of multi-extremal solutions of energy models.

Active Publication Date: 2019-02-19
ZHEJIANG UNIV OF TECH
View PDF3 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Therefore, the current protein structure prediction methods are insufficient in searching for multi-extreme solutions of energy models and need to be improved

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
  • Multi-modal protein structure prediction method based on crowding-out strategy
  • Multi-modal protein structure prediction method based on crowding-out strategy
  • Multi-modal protein structure prediction method based on crowding-out strategy

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0039] The present invention will be further described below in conjunction with the accompanying drawings.

[0040] refer to Figure 1 ~ Figure 3 , a multimodal protein structure prediction method based on the crowding out strategy, including the following steps:

[0041] 1) Given the input sequence information and the protein force field model, namely the energy function Rosetta Score3;

[0042] 2) Initialization: Iterate the first and second stages of the Rosetta protocol to generate a population P with NP conformations g , denoted as in For the i-th conformation of the g-th generation population, set the maximum number of iterations G max And initialize the number of iterations g=0;

[0043] 3) Generate population P through crossover and mutation operations of differential evolution algorithm g The test conformation population U g , denoted as in is the i-th test conformation of the g-th generation population. Set i=1, the process is as follows:

[0044] 3.1...

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

A multi-modal protein structure prediction method based on a crowding-out strategy comprises the following steps of 1) giving input sequence information and a protein force field model; 2) initializing; 3) carrying out mutation and crossover operation; 4) generating an archiving set; 5) calculating a cluster center and a cluster radius; 6) carrying out crowding-out operation; 7) carrying out clustering operation; and 8) determining whether to satisfy a termination condition, if the condition is satisfied, terminating and outputting all optimal solutions. By using the multi-modal protein structure prediction method based on the crowding-out strategy, under the framework of a differential evolution algorithm, the crowding-out strategy is used to adaptively form multiple modals in an evolution process, all the local optimum solutions of the model can be discovered, and the local optimum solutions can be stored as many as possible in the process so that the prediction precision of the protein structure prediction method can be increased. By using the multi-modal protein structure prediction method based on the crowding-out strategy, the prediction precision is high.

Description

technical field [0001] The invention relates to the fields of bioinformatics, intelligent optimization and computer application, and in particular to a multimodal protein structure prediction method based on crowding out strategy. Background technique [0002] In the 125 scientific issues published by Science in 2005, "the problem of whether protein folding can be predicted" was raised, indicating that the determination of the structure of biological macromolecules represented by proteins is not only a basic theoretical problem that has not yet been resolved by the central dogma of molecular biology, but also It is an application problem that needs to be solved urgently in the fields of medicine, pharmacy and materials science that are related to the vital interests of human beings. For example, the structural variation of Prion Protein (PrP) will cause mad cow disease, and protein misfolding will lead to diseases such as Alzheimer's disease and Parkinson's disease. Therefo...

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): G16B15/20G16B40/20
Inventor 张贵军王柳静刘俊周晓根谢腾宇郝小虎
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