计算机科学 ›› 2015, Vol. 42 ›› Issue (3): 237-240.doi: 10.11896/j.issn.1002-137X.2015.03.049

• 人工智能 • 上一篇    下一篇

一种基于片段组装的蛋白质构象空间优化算法

郝小虎,张贵军,周晓根,程正华,张启鹏   

  1. 浙江工业大学信息工程学院 杭州310023,浙江工业大学信息工程学院 杭州310023,浙江工业大学信息工程学院 杭州310023,浙江工业大学信息工程学院 杭州310023,浙江工业大学经贸管理学院 杭州310023
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受国家自然科学基金(61075062,61379020),浙江省自然科学基金(LY13F030008),浙江省科技厅公益项目(2014C33088),浙江省重中之重学科开放基金(20120811),杭州市产学研合作项目(20131631E31)资助

Protein Conformational Space Optimization Algorithm Based on Fragment-assembly

HAO Xiao-hu, ZHANG Gui-jun, ZHOU Xiao-gen, CHENG Zheng-hua and ZHANG Qi-peng   

  • Online:2018-11-14 Published:2018-11-14

摘要: 针对蛋白质构象空间优化问题,提出一种基于片段组装的构象空间优化算法。算法利用基于Rosetta粗粒度的知识能量模型有效地提高了收敛速度;同时,借助片段组装技术可以有效弥补因能量函数不精确而导致的预测精度不足的缺陷;此外,差分进化算法的引入使得算法具有较好的全局搜索能力。5种测试蛋白的实验结果表明,所提算法具有较好的搜索性能和预测精度。

关键词: 蛋白质结构预测,片段组装,差分进化算法,Rosetta粗粒度能量模型

Abstract: An optimization algorithm based on fragment-assembly was proposed for the optimization problems of protein conformational space.The algorithm employs Rosetta energy model based on the knowledge and coarse-grained to improve the convergence rate.Simultaneously,fragment-assembly techniques are able to compensate the defect of prediction accuracies caused by the inaccuracy of energy functions.The introduction of differential evolution algorithm successfully improves the global searching capability of the algorithm as well.The experiments on five test proteins verify the superior searching performance and prediction accuracy of the proposed algorithm.

Key words: Protein structure prediction,Fragment-assembly,Differential evolution algorithm,Rosetta knowledge-based coarse-grained energy model

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