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

机译:高性能计算集群上计算化学中的并行柔性分子对接

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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:药物研究的主要目标是开发在特定患病生物体中具有改善的生物效应的新型药物。药物设计中的常见做法集中于对具有特定生物学活性的化学结构进行系统的有机衍生化,以及随后对所得益处进行生物学体外评估。然而,这种经典方法或多或少可以归类为偶然性药物发现,这是非常艰巨,昂贵和费时的。如今,人们对基于理性的药物研究技术表现出极大的热情,例如计算机辅助药物设计,虚拟筛选,生物信息学,化学计量学,定量构效关系等。在本文中,我们致力于设计高性能计算( HPC)支持灵活的分子对接(FMD),可以在基于结构的虚拟筛选(SBVS)中有效地利用它。简要介绍了FMD的原理,并提出了一种将消息传递接口(MPI)与多线程相结合的解决方案。将MPI-HPC增强的SBVS / FMD的优点(例如可用性,可伸缩性,性能)与用于药物化学中新型铅结构发现的其他HPC技术进行了比较。

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