AN EVOLUTIONARY CONSERVATION-BASED METHOD FOR REFINING AND RERANKING PROTEIN COMPLEX STRUCTURES

Author:

AKBAL-DELIBAS BAHAR1,HASHMI IRINA2,SHEHU AMARDA2,HASPEL NURIT1

Affiliation:

1. Computer Science Department, University of Massachusetts Boston, 100 Morrissey Boulevard, Boston, MA 02125, USA

2. Department of Computer Science, George Mason University, 4400 University Drive, Fairfax, VA 22030, USA

Abstract

Detection of protein complexes and their structures is crucial for understanding their role in the basic biology of organisms. Computational docking methods can provide researchers with a good starting point for the analysis of protein complexes. However, these methods are often not accurate and their results need to be further refined to improve interface packing. In this paper, we introduce a refinement method that incorporates evolutionary information into a novel scoring function by employing Evolutionary Trace (ET)-based scores. Our method also takes Van der Waals interactions into account to avoid atomic clashes in refined structures. We tested our method on docked candidates of eight protein complexes and the results suggest that the proposed scoring function helps bias the search toward complexes with native interactions. We show a strong correlation between evolutionary-conserved residues and correct interface packing. Our refinement method is able to produce structures with better lRMSD (least RMSD) with respect to the known complexes and lower energies than initial docked structures. It also helps to filter out false-positive complexes generated by docking methods, by detecting little or no conserved residues on false interfaces. We believe this method is a step toward better ranking and prediction of protein complexes.

Publisher

World Scientific Pub Co Pte Lt

Subject

Computer Science Applications,Molecular Biology,Biochemistry

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Ranking Protein-Protein Binding Using Evolutionary Information and Machine Learning;Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics;2017-08-20

2. Machine Learning Approaches for Predicting Protein Complex Similarity;Journal of Computational Biology;2017-01

3. Methods for Detecting Critical Residues in Proteins;Methods in Molecular Biology;2016-10-06

4. Accurate refinement of docked protein complexes using evolutionary information and deep learning;Journal of Bioinformatics and Computational Biology;2016-06

5. Accurate Prediction of Docked Protein Structure Similarity;Journal of Computational Biology;2015-09

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3