Stochastic roadmap simulation: An efficient representation and algorithm for analyzing molecular motion
Stochastic roadmap simulation: An efficient representation and algorithm for analyzing molecular motion
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DOI：
10.1089/10665270360688011
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发表时间：
2003-01-01
影响因子：
1.7
通讯作者：
Varma, C
中科院分区：
文献类型：
--
作者：
Apaydin, MS;Brutlag, DL;Varma, C
经典的分子运动模拟技术，如蒙特卡罗（MC）模拟，一次生成一个运动路径，并花费大部分时间在分子构象空间上定义的能量景观的局部最小值。它们的高计算成本使它们不能用于计算系综性质（需要分析许多途径的性质）。本文介绍了随机路线图模拟（SRS）作为一种新的计算方法，探索分子运动的动力学，同时检查多个途径。这些途径被复杂地编码在一个图中，该图是通过随机采样分子构象空间而构建的。这种计算不显式地跟踪任何特定的路径，避免了局部极小值问题。图中的每条边表示分子的潜在转变，并且与指示该转变的可能性的概率相关联。通过将图视为马尔可夫链，可以在整个分子能量景观上有效地计算系综性质。此外，SRS收敛到相同的分布MC模拟。SRS被应用于两个生物学问题：计算折叠的概率，一个重要的序参数，衡量“动力学距离”的蛋白质的构象从其天然状态;和估计预期的时间逃离配体-蛋白质结合位点。与MC模拟蛋白质折叠的比较表明，SRS可以产生更准确的结果，同时减少了几个数量级的计算时间。配体-蛋白质结合的计算研究也表明SRS作为一种有前途的方法来研究配体-蛋白质相互作用。
Classic molecular motion simulation techniques, such as Monte Carlo (MC) simulation, generate motion pathways one at a time and spend most of their time in the local minima of the energy landscape defined over a molecular conformation space. Their high computational cost prevents them from being used to compute ensemble properties (properties requiring the analysis of many pathways). This paper introduces stochastic roadmap simulation (SRS) as a new computational approach for exploring the kinetics of molecular motion by simultaneously examining multiple pathways. These pathways are compactly encoded in a graph, which is constructed by sampling a molecular conformation space at random. This computation, which does not trace any particular pathway explicitly, circumvents the local-minima problem. Each edge in the graph represents a potential transition of the molecule and is associated with a probability indicating the likelihood of this transition. By viewing the graph as a Markov chain, ensemble properties can be efficiently computed over the entire molecular energy landscape. Furthermore, SRS converges to the same distribution as MC simulation. SRS is applied to two biological problems: computing the probability of folding, an important order parameter that measures the "kinetic distance" of a protein's conformation from its native state; and estimating the expected time to escape from a ligand-protein binding site. Comparison with MC simulations on protein folding shows that SRS produces arguably more accurate results, while reducing computation time by several orders of magnitude. Computational studies on ligand-protein binding also demonstrate SRS as a promising approach to study ligand-protein interactions.