Abstract convex lower-bound estimation based protein structure prediction method

Abstract

Disclosed is an abstract convex lower-bound estimation based protein structure prediction method. The method includes: firstly, aiming for high-dimensional conformational spatial sampling problems for proteins, adopting a series of transform methods to transform an ECEPP / 3 force field model into an increasing radial convex function in unit simple constraint conditions; secondly, based on an abstract convex theory, proving and analyzing to give out a supporting hyperplane set of the increasing radial convex function; thirdly, constructing a lower-bound underestimate supporting plane on the basis of population minimization conformation subdifferential knowledge under a differential evolution population algorithm framework; fourthly, by the aid of a quick underestimate supporting plane extreme point enumeration method, gradually decreasing a conformational sampling space to improve sampling efficiency; fifthly, utilizing the lower-bound underestimate supporting plane for quickly and cheaply estimating an energy value of an original potential model to effectively decrease evaluation times of a potential model objective function; finally, verifying effectiveness of the method by methionine-enkephalin (TYR1-GLY2-GLY3-PHE4-MET5) conformational spatial optimization examples. The abstract convex lower-bound estimation based protein structure prediction method is high in reliability, low in complexity and high in computation efficiency.

Description

technical field [0001] The invention relates to the fields of bioinformatics and computer applications, in particular to a protein structure prediction method based on abstract convex lower bound estimation. Background technique [0002] Bioinformatics is a research hotspot in the intersection of life science and computer science. Bioinformatics research results have been widely used in gene discovery and prediction, gene data storage and management, data retrieval and mining, gene expression data analysis, protein structure prediction, gene and protein homology relationship prediction, sequence analysis and comparison, etc. The prediction of protein three-dimensional structure is an important branch in the field of bioinformatics. The famous Anfinsen experiment shows that the primary structure of a protein determines its three-dimensional structure, that is, the sequence of amino acid residues in the peptide chain determines its spatial structure. From a thermodynamic poi...

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Problems solved by technology

[0005] In order to overcome the shortcomings of existing methods that are highly complex and easy to fall into local extreme points and difficult to obtain the global optimal stable conformation, the present invention not only reduces the complexity of the force field model, but also combines the abstract convex theory to propose a method based on abstract convex Protein Structure Prediction Method Based on Lower Bound Estimation

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