首页> 外文期刊>Journal of Computational Chemistry: Organic, Inorganic, Physical, Biological >Packing Optimization for Automated Generation of Complex System's Initial Configurations for Molecular Dynamics and Docking
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Packing Optimization for Automated Generation of Complex System's Initial Configurations for Molecular Dynamics and Docking

机译:自动生成复杂系统的分子动力学和对接的初始配置的包装优化。

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Molecular Dynamics is a powerful methodology for the comprehension at molecular level of many chemical and biochemical systems. The theories and techniques developed for structural and thermodynamic analyses are well established, and many software packages are available. However, designing starting configurations for dynamics can be cumbersome. Easily generated regular lattices can be used when simple liquids or mixtures are studied. However, for complex mixtures, polymer solutions or solid adsorbed liquids (for example) this approach is inefficient, and it turns out to be very hard to obtain an adequate coordinate coordinate file. In this article, the problem of obtaining an adequate initial configuration is treated as a "packing" problem and solved by an optimization procedure. The initial configuration is chosen in such a way that the minimum distance between atoms of different molecules is greater than a fixed tolerance. The optimization uses a well-known algorithm for box-constrained minimization. Applications are given for biomolecule solvation, many-component mixtures, and interfaces. This approach can reduce the work of designing starting configurations from days or weeks to few minutes or hours, in an automated fashion. packing optimization is also shown to be a powerful methodology for space search in docking of small ligands to proteins. This is demonstrated by docking of the thyroid hormone to its nuclear receptor.
机译:分子动力学是一种用于理解许多化学和生化系统分子水平的强大方法。为结构和热力学分析开发的理论和技术已经建立,并且有许多软件包可用。但是,为动力学设计启动配置可能很麻烦。研究简单的液体或混合物时,可以使用易于生成的规则晶格。但是,对于复杂的混合物,聚合物溶液或固体吸附的液体(例如),此方法效率低下,事实证明很难获得足够的坐标坐标文件。在本文中,获得适当的初始配置的问题被视为“打包”问题,并通过优化过程解决。初始构型的选择应使不同分子的原子之间的最小距离大于固定公差。优化使用了众所周知的框约束最小化算法。给出了生物分子溶剂化,多组分混合物和界面的应用。这种方法可以自动方式将设计初始配置的工作从几天或几周减少到几分钟或几小时。在小配体与蛋白质的对接中,堆积优化也被证明是一种有效的空间搜索方法。甲状腺激素与核受体的对接证明了这一点。

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