Protein folding prediction in the HP model using ions motion optimization with a greedy algorithm

BioData Mining

Hsueh-Wei Chang¹  Li-Yeh Chuang²  Yu-Shiun Lin³  Cheng-Hong Yang³  Kuo-Chuan Wu³ 

[1] Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University;Department of Chemical Engineering & Institute of Biotechnology and Chemical Engineering, I-Shou University;Department of Electronic Engineering, National Kaohsiung University of Science and Technology;

关键词: Protein folding;    Ion motion optimization;    IMOG;    Hydrophobic-polar (HP) model;    Global search;    Local search;   

DOI  :  10.1186/s13040-018-0176-6

来源: DOAJ

【 摘 要 】

Abstract Background The function of a protein is determined by its native protein structure. Among many protein prediction methods, the Hydrophobic-Polar (HP) model, an ab initio method, simplifies the protein folding prediction process in order to reduce the prediction complexity. Results In this study, the ions motion optimization (IMO) algorithm was combined with the greedy algorithm (namely IMOG) and implemented to the HP model for the protein folding prediction based on the 2D-triangular-lattice model. Prediction results showed that the integration method IMOG provided a better prediction efficiency in a HP model. Compared to others, our proposed method turned out as superior in its prediction ability and resilience for most of the test sequences. The efficiency of the proposed method was verified by the prediction results. The global search capability and the ability to escape from the local best solution of IMO combined with a local search (greedy algorithm) to the new algorithm IMOG greatly improve the search for the best solution with reliable protein folding prediction. Conclusion Overall, the HP model integrated with IMO and a greedy algorithm as IMOG provides an improved way of protein structure prediction of high stability, high efficiency, and outstanding performance.

【 授权许可】

Unknown