文章基本信息

标题：Evolutionary GRSA for Protein Structure Prediction
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作者：Fanny Gabriela Maldonado-Nava ; Juan Frausto-Solís ; Juan Paulo Sánchez-Hernández 等
期刊名称：International Journal of Combinatorial Optimization Problems and Informatics
印刷版ISSN：2007-1558
电子版ISSN：2007-1558
出版年度：2016
卷号：7
期号：3
页码：75-86
语种：English
出版社：International Journal of Combinatorial Optimization Problems and Informatics
其他摘要：Protein folding problem (PFP) is a challenge in some areas, such as molecular biology, computational biology, combinatorial optimi zation , and computer s cience . This is due to the large number of conformational structures that a protein can take from its primary structure to the native structure (NS). The aim of PFP is to find the NS of a protein target sequence. In general, the NS which has the lowest Gib bs energy or an energy close to it. In this paper, a Simulated Annealing like algorithm is presented, using the Golden Ratio search strategy and evolutionary techniques for PFP in small peptides. This method looks for the NS using only the protein's amino acid sequence, and determines the three - dimensional structure with the minimum energy or a close value of it.
其他关键词：Protein Structure Prediction; GRSA; Evolutionary algorithms.