Cloud-PERM: Ab Initio Prediction Method for Protein Folding Simulation

doi:10.3969/j.issn.1006-2475.2025.05.010

Abstract

Abstract: A cloud based ab initio prediction method for protein folding simulation calculation algorithm is proposed. Using a non template based ab initio prediction method， the energy function of the protein folding process is constructed by obtaining the optimal relationship between the spatial positions and energies of all atoms in the protein. The protein folding structure is predicted using protein fragment assembly technology. A lattice model is used to place the protein structure chains without overlap in the construction space of the lattice model. The PERM algorithm is used to find the lowest energy protein structure chain placement state， realize protein folding simulation calculation， divide the PERM algorithm based on the MapReduce programming model， and obtain the Cloud-PERM algorithm generated by the MapReduce programming module in Apache’s cloud computing platform Hadoop. Continuously solve the lattice model of protein folding simulation calculation， and obtain the protein folding simulation calculation result with the lowest energy. Through experimental analysis， it was found that the algorithm has a higher similarity in protein structure prediction， can achieve protein folding simulation calculation， and has strong computing power and fast speed. It can obtain the protein folding structure with the lowest energy in the same time with a large number of optimization times.

Key words: , cloud computing, ab initio prediction method, protein folding, simulation calculation, MapReduce, Cloud-PERM algorithm

CLC Number:

TP393.04

XU Shengchao1, ZHOU Jipeng2. Cloud-PERM: Ab Initio Prediction Method for Protein Folding Simulation[J]. Computer and Modernization, 2025, 0(05): 73-78.

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