An Adaptive Protein Structure Prediction Method Based on a Lower Bound Estimation Strategy

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...

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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

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