Reconstructing and Decomposing Protein Energy Landscapes to Organize Structure Spaces and Reveal Biologically-active States

N. Akhter, Jing Lei, Wanli Qiao, Amarda Shehu
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引用次数: 2

Abstract

The concept of energy landscape has become a useful construction in protein modeling due to its ability to relate structures and structural dynamics to function. While great progress is being made in probing energy landscapes, it remains unclear how to reconstruct the landscape from computed structures. Recently, our laboratories have made headway in this direction via concepts from topological and statistical analysis of spatial data. In this paper, we propose a novel approach to reconstruct the underlying energy landscape populated by computed/sampled energy-evaluated structures of a molecule and decompose it into basins of attraction. We demonstrate that such a construction not only allows deep analysis of the efficacy of a structure computation algorithm and the energy function it employs in the first place, but, more importantly, makes important steps toward addressing the open decoy selection problem in template-free protein structure prediction.
重构与分解蛋白质能量景观,组织结构空间,揭示生物活性状态
能量景观的概念由于其将结构和结构动力学与功能联系起来的能力,已经成为蛋白质建模中一个有用的构造。虽然在探测能量景观方面取得了很大进展,但如何从计算结构中重建景观仍然不清楚。最近,我们的实验室通过空间数据的拓扑和统计分析的概念在这个方向上取得了进展。在本文中,我们提出了一种新的方法来重建由计算/采样的能量评估结构组成的潜在能量景观,并将其分解为吸引力盆地。我们证明,这种构建不仅可以深入分析结构计算算法的有效性及其所使用的能量函数,而且更重要的是,它为解决无模板蛋白质结构预测中的开放诱饵选择问题迈出了重要的一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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