期刊
JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY
卷 10, 期 3, 页码 -出版社
IMPERIAL COLLEGE PRESS
DOI: 10.1142/S021972001242005X
关键词
Protein conformational space; near-native conformations; structural profile
类别
资金
- NSF CCF [1016995]
- NSF IIS CAREER Award [1144106]
- Division of Computing and Communication Foundations
- Direct For Computer & Info Scie & Enginr [1016995] Funding Source: National Science Foundation
The roughness of the protein energy surface poses a significant challenge to search algorithms that seek to obtain a structural characterization of the native state. Recent research seeks to bias search toward near-native conformations through one-dimensional structural profiles of the protein native state. Here we investigate the er effectiveness of such profiles in a structure prediction setting for proteins of various sizes and folds. We pursue two directions. We first investigate the contribution of structural profiles in comparison to or in conjunction with physics-based energy functions in providing an effective energy bias. We conduct this investigation in the context of Metropolis Monte Carlo with fragment-based assembly. Second, we explore the effectiveness of structural profiles in providing projection coordinates through which to organize the conformational space. We do so in the context of a robotics-inspired search framework proposed in our lab that employs projections of the conformational space to guide search. Our findings indicate that structural profiles are most effective in obtaining physically realistic near-native conformations when employed in conjunction with physics-based energy functions. Our findings also show that these profiles are very effective when employed instead as projection coordinates to guide probabilistic search toward undersampled regions of the conformational space.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据