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首页> 外文期刊>Bulletin of the American Physical Society >APS -APS March Meeting 2017 - Event - ChemHTPS - A virtual high-throughput screening program suite for the chemical and materials sciences
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APS -APS March Meeting 2017 - Event - ChemHTPS - A virtual high-throughput screening program suite for the chemical and materials sciences

机译:APS -APS 2017年3月会议-活动-ChemHTPS-用于化学和材料科学的虚拟高通量筛选程序套件

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The discovery of new compounds, materials, and chemical reactions with exceptional properties is the key for the grand challenges in innovation, energy and sustainability. This process can be dramatically accelerated by means of the virtual high-throughput screening (HTPS) of large-scale candidate libraries. The resulting data can further be used to study the underlying structure-property relationships and thus facilitate rational design capability. This approach has been extensively used for many years in the drug discovery community. However, the lack of openly available virtual HTPS tools is limiting the use of these techniques in various other applications such as photovoltaics, optoelectronics, and catalysis. Thus, we developed ChemHTPS, a general-purpose, comprehensive and user-friendly suite, that will allow users to efficiently perform large in silico modeling studies and high-throughput analyses in these applications. ChemHTPS also includes a massively parallel molecular library generator which offers a multitude of options to customize and restrict the scope of the enumerated chemical space and thus tailor it for the demands of specific applications. To streamline the non-combinatorial exploration of chemical space, we incorporate genetic algorithms into the framework. In addition to implementing smarter algorithms, we also focus on the ease of use, workflow, and code integration to make this technology more accessible to the community.
机译:发现具有优异性能的新化合物,材料和化学反应是创新,能源和可持续性方面的巨大挑战的关键。通过大规模候选库的虚拟高通量筛选(HTPS),可以大大加快此过程。得到的数据可以进一步用于研究潜在的结构-属性关系,从而促进合理的设计能力。这种方法已经在药物发现社区中广泛使用了很多年。但是,缺乏公开可用的虚拟HTPS工具限制了这些技术在光伏,光电和催化等各种其他应用中的使用。因此,我们开发了ChemHTPS,这是一种通用,全面且用户友好的套件,它将使用户能够在这些应用程序中高效地执行大型计算机模拟研究和高通量分析。 ChemHTPS还包括一个大规模并行的分子库生成器,该生成器提供了多种选项来自定义和限制所列举的化学空间的范围,从而根据特定应用的需要对其进行定制。为了简化化学空间的非组合探索,我们将遗传算法纳入框架。除了实现更智能的算法外,我们还关注易用性,工作流程和代码集成,以使社区更容易使用此技术。

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