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基于软棘轮准则的温度加速分子动力学通过低分辨率信息实现增强采样。

Temperature Accelerated Molecular Dynamics with Soft-Ratcheting Criterion Orients Enhanced Sampling by Low-Resolution Information.

作者信息

Cortes-Ciriano Isidro, Bouvier Guillaume, Nilges Michael, Maragliano Luca, Malliavin Thérèse E

机构信息

Unité de Bioinformatique Structurale, CNRS UMR 3528, Structural Biology and Chemistry Department, Institut Pasteur , 25-28, rue Dr. Roux, 75 724 Paris, France.

Department of Neuroscience and Brain Technologies, Istituto Italiano di Tecnologia , Genoa, Italy.

出版信息

J Chem Theory Comput. 2015 Jul 14;11(7):3446-54. doi: 10.1021/acs.jctc.5b00153. Epub 2015 Jun 3.

Abstract

Many proteins exhibit an equilibrium between multiple conformations, some of them being characterized only by low-resolution information. Visiting all conformations is a demanding task for computational techniques performing enhanced but unfocused exploration of collective variable (CV) space. Otherwise, pulling a structure toward a target condition biases the exploration in a way difficult to assess. To address this problem, we introduce here the soft-ratcheting temperature-accelerated molecular dynamics (sr-TAMD), where the exploration of CV space by TAMD is coupled to a soft-ratcheting algorithm that filters the evolving CV values according to a predefined criterion. Any low resolution or even qualitative information can be used to orient the exploration. We validate this technique by exploring the conformational space of the inactive state of the catalytic domain of the adenyl cyclase AC from Bordetella pertussis. The domain AC gets activated by association with calmodulin (CaM), and the available crystal structure shows that in the complex the protein has an elongated shape. High-resolution data are not available for the inactive, CaM-free protein state, but hydrodynamic measurements have shown that the inactive AC displays a more globular conformation. Here, using as CVs several geometric centers, we use sr-TAMD to enhance CV space sampling while filtering for CV values that correspond to centers moving close to each other, and we thus rapidly visit regions of conformational space that correspond to globular structures. The set of conformations sampled using sr-TAMD provides the most extensive description of the inactive state of AC up to now, consistent with available experimental information.

摘要

许多蛋白质在多种构象之间呈现平衡,其中一些构象仅由低分辨率信息表征。对于在集体变量(CV)空间中进行增强但无聚焦探索的计算技术而言,遍历所有构象是一项艰巨的任务。否则,将结构拉向目标条件会以难以评估的方式使探索产生偏差。为了解决这个问题,我们在此引入软棘轮温度加速分子动力学(sr-TAMD),其中TAMD对CV空间的探索与一种软棘轮算法相结合,该算法根据预定义标准对不断演变的CV值进行过滤。任何低分辨率甚至定性信息都可用于引导探索。我们通过探索百日咳博德特氏菌腺苷酸环化酶AC催化结构域的非活性状态的构象空间来验证这项技术。AC结构域通过与钙调蛋白(CaM)结合而被激活,现有的晶体结构表明,在复合物中该蛋白质呈细长形状。对于无CaM的非活性蛋白质状态,尚无高分辨率数据,但流体动力学测量表明,非活性AC呈现出更球状的构象。在此,我们将几个几何中心用作CV,使用sr-TAMD来增强CV空间采样,同时过滤对应于中心彼此靠近移动的CV值,从而快速访问对应于球状结构的构象空间区域。使用sr-TAMD采样的构象集提供了迄今为止对AC非活性状态最广泛的描述,与现有实验信息一致。

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