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首页> 外文期刊>Journal of chemical information and modeling >DICE: A Monte Carlo Code for Molecular Simulation Including the Configurational Bias Monte Carlo Method
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DICE: A Monte Carlo Code for Molecular Simulation Including the Configurational Bias Monte Carlo Method

机译:骰子:用于分子模拟的蒙特卡罗代码,包括配置偏置蒙特卡罗方法

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Solute-solvent systems are an important topic of study, as the effects of the solvent on the solute can drastically change its properties. Theoretical studies of these systems are done with ab initio methods, molecular simulations, or a combination of both. The simulations of molecular systems are usually performed with either molecular dynamics (MD) or Monte Carlo (MC) methods. Classical MD has evolved much in the last decades, both in algorithms and implementations, having several stable and efficient codes developed and available. Similarly, MC methods have also evolved, focusing mainly in creating and improving methods and implementations in available codes. In this paper, we provide some enhancements to a configurational bias Monte Carlo (CBMC) methodology to simulate flexible molecules using the molecular fragments concept. In our implementation the acceptance criterion of the CBMC method was simplified and a generalization was proposed to allow the simulation of molecules with any kind of fragments. We also introduce the new version of DICE, an MC code for molecular simulation (available at https://portal.if.usp.br/dice) . This code was mainly developed to simulate solute-solvent systems in liquid and gas phases and in interfaces (gas-liquid and solid-liquid) that has been mostly used to generate configurations for a sequential quantum mechanics/molecular mechanics method (S-QM/MM). This new version introduces several improvements over the previous ones, with the ability of simulating flexible molecules with CBMC as one of them. Simulations of well-known molecules, such as n-octane and 1,2-dichloroethane in vacuum and in solution, are presented to validate the new implementations compared with MD simulations, experimental data, and other theoretical results. The efficiency of the conformational sampling was analyzed using the acceptance rates of different alkanes: n-octane, neopentane, and 4-ethylheptane. Furthermore, a very complex molecule, boron subphtalocyanine, was simulated in vacuum and in aqueous solution showing the versatility of the new implementation. We show that the CBMC is a very good method to perform conformation sampling of complex moderately sized molecules (up to 150 atoms) in solution following the Boltzmann thermodynamic equilibrium distribution.
机译:溶质 - 溶剂系统是研究的重要课题,因为溶剂对溶质对溶质的影响会大大改变其性质。这些系统的理论研究是用AB Initio方法,分子模拟或两者组合进行的。通常用分子动力学(MD)或蒙特卡罗(MC)方法进行分子系统的模拟。在算法和实现中,古典MD在过去几十年中发展得很大,具有开发和可用的几个稳定和有效的代码。同样,MC方法也在演变,主要关注在可用代码中创造和改进方法和实现。在本文中,我们为使用分子碎片概念模拟柔性分子的配置偏差蒙特卡罗(CBMC)方法提供了一些增强。在我们的实施中,简化了CBMC方法的验收标准,提出了概括以允许用任何种类的片段模拟分子。我们还介绍了新版本的骰子,一个用于分子模拟的MC代码(在https://portal.if.usp.br/dice上提供)。该代码主要开发,以模拟液体和气相中的溶质 - 溶剂系统,以及主要用于产生连续量子力学/分子机械方法的配置(S-QM /毫米)。这个新版本介绍了以前的几种改进,具有模拟CBMC作为其中一个的柔性分子的能力。鉴于与MD模拟,实验数据和其他理论结果相比,提出了在真空和溶液中的众所周知分子(如N-辛烷和1,2-二氯乙烷)的模拟,以验证新的实施。使用不同烷烃的验收速率分析构象取样的效率:正辛烷,新戊烷和4-乙基庚烷。此外,在真空和水溶液中模拟了一个非常复杂的分子硼亚苯酞菁,显示出新的实施方式的多功能性。我们表明,CBMC是在Boltzmann热力学平衡分布之后在溶液中进行溶液中复合体积大小分子(最多150个原子)的构象采样的非常好的方法。

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