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Parallel Flexible Molecular Docking in Computational Chemistry on High Performance Computing Clusters

机译:高性能计算集群计算化学中的平行柔性分子对接

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The main objective in pharmaceutical research is development of novel drugs with improved biological effect in specifically afflicted organisms. A common practice in drug design focuses on systematic organic derivatization of chemical structures exhibiting certain biological activity and subsequent biological in vitro evaluation of the resulted benefits. However, this classical approach can be more or less classified as a chance drug discovery, being very arduous, expensive and time consuming. Nowadays, a lot of enthusiasm is given to rationally oriented drug research techniques like computer-aided drug design, virtual screening, bioinformatics, chemometrics, quantitative structure-activity relationships, etc. In the present article, we deal with designing a high performance computing (HPC) support for flexible molecular docking (FMD) which can be beneficially utilized in structure-based virtual screening (SBVS). The principles of FMD are briefly introduced and a solution combining message passing interface (MPI) with multithreading is proposed. The merits (e.g. availability, scalability, performance) of MPI-HPC enhanced SBVS/FMD are compared with other HPC techniques utilized for novel lead structures discovery in medicinal chemistry.
机译:制药研究的主要目的是开发新型药物,具有特异性受污染的生物体的生物学效应。药物设计的常见做法侧重于化学结构的系统有机衍生化,其具有一定的生物活性和随后的生物体外评估所产生的益处。然而,这种古典方法可以或多或少被归类为机会药物发现,非常艰巨,昂贵且耗时。如今,在本文中,对计算机辅助药物设计,虚拟筛选,生物信息学,化学计量学,定量结构 - 活动关系等,提供了很多热情。在本文中,我们处理设计高性能计算( HPC)支持柔性分子对接(FMD),其可以在基于结构的虚拟筛选(SBV)中有利地利用。提出了简要介绍FMD的原理,并提出了一种组合具有多线程的消息传递接口(MPI)的解决方案。将MPI-HPC增强SBV / FMD的优点(例如可用性,可扩展性,性能,性能)与用于药用化学中的新型铅结构发现的其他HPC技术进行比较。

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