Protein conformation prediction acceleration method based on virtual network mapping and cloud parallel computing

Abstract

The invention discloses a protein conformation prediction acceleration method based on virtual network mapping and cloud parallel computing. The method comprises the following steps: converting a protein conformation prediction problem into a virtual network mapping problem; constructing a protein conformation prediction heuristic algorithm based on the mathematical model, and finally predicting the protein conformation by adopting cloud parallel computing. A protein folding direction coding string obtained by using a protein conformation prediction heuristic algorithm is used as a part of aninitial population, sub-population division is carried out on the population, and each sub-population independently completes a calculation process of a genetic algorithm on protein conformation on arespective processor. The protein conformations with the minimum free energy are exchanged among the sub-populations, genetic manipulation is further carried out, and the manipulation is stopped untila specified multiplication algebra is reached. According to the method, a mathematical model for predicting the protein conformation is established, and the protein conformation can be accurately andefficiently predicted by utilizing a heuristic and parallel genetic algorithm and combining a cloud parallel computing acceleration prediction protein structure.

Description

technical field [0001] The invention relates to interdisciplinary technology of communication, computer and bioengineering, in particular to a protein conformation prediction acceleration method based on virtual network mapping and cloud parallel computing. Background technique [0002] Protein is the basis of life activities. The problem of protein conformation prediction is mainly to determine its folding path and protein structure in the natural state according to the amino acid sequence. The protein structure in the natural state is the most stable protein structure. The normal function of protein is inseparable from its structure. The study of protein structure is conducive to further understanding of protein function. The study of protein conformation prediction can not only explore the basic process of life, but also promote the development of medicine, agriculture and biology. The development of technology and other application fields. For example, in the field of m...

AI Technical Summary

Problems solved by technology

The problem of predicting protein structure using theoretical modeling has been proved to be NP-difficult, and its calculation is huge, and the virtual network mapping heuristic algorithm can more quickly solve the (approximate) optimal solution of the protein conformation prediction model (with global minimum free energy protein structure), so far, there is no effective heuristic algorithm for the above

[0006] In addition, the process of predicting protein conformation through mathematical modeling and heuristic algorithms is serial, and the actual efficiency is not high. When predicting long amino acid sequences, there are still problems such as time-consuming and high computing costs.

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