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首页> 外文期刊>Journal of computational biology: A journal of computational molecular cell biology >Using Motion Planning to Map Protein Folding Landscapes and Analyze Folding Kinetics of Known Native Structures
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Using Motion Planning to Map Protein Folding Landscapes and Analyze Folding Kinetics of Known Native Structures

机译:使用运动计划来绘制蛋白质折叠态势并分析已知天然结构的折叠动力学

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We investigate a novel approach for studying the kinetics of protein folding. Our framework has evolved from robotics motion planning techniques called probabilistic roadmap methods (PRMS) that have been applied in many diverse fields with great success. In our previous work, we presented our PRM-based technique and obtained encouraging results studying protein folding pathways for several small proteins. In this paper, we describe how our motion planning framework can be used to study protein folding kinetics. In particular, we present a refined version of our PRM-based framework and describe how it can be used to produce potential energy landscapes, free energy landscapes, and many folding pathways all from a single roadmap which is computed in a few hours on a desktop PC. Results are presented for 14 proteins. Our ability to produce large sets of unrelated folding pathways may potentially provide crucial insight into some aspects of folding kinetics, such as proteins that exhibit both two-state and three-state kinetics that are not captured by other theoretical techniques.
机译:我们研究一种新颖的方法来研究蛋白质折叠的动力学。我们的框架是从被称为概率路线图方法(PRMS)的机器人运动计划技术发展而来的,该技术已在许多不同领域中得到了成功应用。在我们之前的工作中,我们介绍了基于PRM的技术,并且在研究几种小蛋白质的蛋白质折叠途径时获得了令人鼓舞的结果。在本文中,我们描述了如何将运动计划框架用于研究蛋白质折叠动力学。特别是,我们提出了基于PRM的框架的精炼版本,并描述了如何将其用于生成潜在的能源格局,自由能源格局以及许多折叠路径,这些都可以从一个单一的路线图得出,而该路线图是在桌面上几个小时内计算得出的电脑给出了14种蛋白质的结果。我们产生大量无关折叠途径的能力可能会为折叠动力学的某些方面提供至关重要的见解,例如同时具有两种状态和三态动力学的蛋白质无法被其他理论方法捕获。

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