Specific and non-specific protein association in solution: computation of solvent effects and prediction of first-encounter modes for efficient configurational bias Monte Carlo simulations.
Specific and non-specific protein association in solution: computation of solvent effects and prediction of first-encounter modes for efficient configurational bias Monte Carlo simulations.
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DOI：
10.1021/jp4050594
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发表时间：
2013-10-17
期刊：
影响因子：
--
通讯作者：
Hassan SA
中科院分区：
文献类型：
--
作者：
Cardone A;Pant H;Hassan SA
弱和超弱蛋白质-蛋白质缔合在分子识别中起作用，并能驱动自发自组装和聚集。这种相互作用很难通过实验检测，并且对力场和采样技术是一个挑战。提出了一种识别水溶液中低群体蛋白质-蛋白质结合模式的方法。该方法的目的是确定优先的第一次遇到的复杂的最终复杂（ES）在平衡的演变。使用连续介质模型来表示溶剂的影响，该模型解释了水排斥的短期和长期影响以及蛋白质/液体界面处的液体结构力。这些效应控制着蛋白质的行为，并基于结合焓数据和模拟进行优化。描述了一种构造偏置函数的算法，用于一组相互作用的蛋白质的自适应构型偏置Monte Carlo。该函数允许混合蛋白质空间分布中的大的和局部的变化，从而增强相关微观状态的采样。该方法适用于三个二元系统。概括多蛋白复合物进行了讨论。
Weak and ultra-weak protein-protein association play a role in molecular recognition, and can drive spontaneous self-assembly and aggregation. Such interactions are difficult to detect experimentally, and are a challenge to the force field and sampling technique. A method is proposed to identify low-population protein-protein binding modes in aqueous solution. The method is designed to identify preferential first-encounter complexes from which the final complex(es) at equilibrium evolves. A continuum model is used to represent the effects of the solvent, which accounts for short- and long-range effects of water exclusion and for liquid-structure forces at protein/liquid interfaces. These effects control the behavior of proteins in close proximity and are optimized based on binding enthalpy data and simulations. An algorithm is described to construct a biasing function for self-adaptive configurational-bias Monte Carlo of a set of interacting proteins. The function allows mixing large and local changes in the spatial distribution of proteins, thereby enhancing sampling of relevant microstates. The method is applied to three binary systems. Generalization to multiprotein complexes is discussed.
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影响因子：
2.8
作者：
Bruge, F;Fornili, SL;Palma, MU
通讯作者：
Palma, MU
影响因子：
4.4
作者：
Falcioni, M;Deem, MW
通讯作者：
Deem, MW
影响因子：
3
作者：
FLORIS, F;TOMASI, J
通讯作者：
TOMASI, J
DOI：
10.1073/pnas.80.12.3696
发表时间：
1983-01-01
期刊：
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA-BIOLOGICAL SCIENCES
影响因子：
--
作者：
GO, N;NOGUTI, T;NISHIKAWA, T
通讯作者：
NISHIKAWA, T
影响因子：
--
作者：
BENNAIM, A
通讯作者：
BENNAIM, A