Protein structure prediction method based on distance constraint copy exchange

Abstract

The invention discloses a protein structure prediction method based on distance constraint copy exchange. The protein structure prediction method comprises the following steps: firstly, carrying out random folding and transformation on a query sequence in each temperature layer to generate an initial population; in population update, taking Rosetta Score3 as an optimal object function, and taking each individual in the population as a target individual in each temperature layer on the basis of a structure with lowest free energy when a protein native state structure which is put forward by Anfinsen is adopted; then, randomly selecting two individuals different from the target individual to carry out variation and cross to generate variation individuals, randomly selecting one section from another individual to carry out transformation with the variation individual to generate a test individual; carrying out energy value comparison on the test individual and the target individual, and introducing the knowledge of a distance spectrum for the test individual of which the energy rises; and carrying out copy exchange on the corresponding individual of an adjacent temperature layer. The protein structure prediction method has good conformational space sampling capability and high prediction accuracy.

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 distance-constrained copy exchange. Background technique [0002] Protein molecules play a vital role in the process of biological and cellular chemical reactions. Their structural models and bioactive states have important implications for our understanding and cure of many diseases. Only when proteins are folded into a specific three-dimensional structure can they produce their unique biological functions. Therefore, to understand the function of a protein, it is necessary to obtain its three-dimensional structure. [0003] Protein tertiary structure prediction is an important task in bioinformatics. The biggest challenge facing the protein conformation optimization problem is to search the extremely complex protein energy function surface. The protein energy model takes into account the bonding of molec...

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Problems solved by technology

[0006] In order to overcome the deficiencies of the existing population conformation space optimization methods, such as high conformation space search dimension, slow convergence speed, and low prediction accuracy, the present invention proposes a distance-constrained replica with better conformation space sampling ability and high prediction accuracy. Exchanged Protein Structure Prediction Methods

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