XSEDE Support: Revolutionizing the Next-Generation Therapeutic Drug Discovery

Bhanu Rekepalli, Y. Peterson
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Abstract

Drug discovery is a critical but complex and costly endeavor. The rate of approval of new therapeutics by the FDA has been in decline while costs are rising. Increasingly, pharmaceutical companies desire to translate pharmaceutical discovery from academic research in order to decrease risk. Although many researchers have identified very compelling targets, most researchers do not have access to drug discovery resources due to the high cost and complex infrastructure needed to launch a discovery campaign. Long-term objective of this research is to integrate drug interaction simulation software to identify new bioactive molecules and speed drug development with minimum cost and time. This technology is a highly feasible way to rapidly close the therapeutic gap and potentially dramatically improve public health. Initially research was conducted using typical clusters and it took 3 months to perform one run with one conformation of the protein using 1.5 million small molecules. But researchers are interested in working with many proteins with multiple conformations per protein related to entire disease related pathways. At this rate this computational research by itself would take 6 to 7 years of computation on institutional clusters. This resulted in PI applying for the XSEDE allocation with Extended Collaborative Support Services (ECSS) support, which resulted in generation of optimized and scaled the drug interaction workflow on XSEDE supercomputers that reduced computation time for single run from months to 40 minutes using 8000 cores. The results were generated for 5 proteins with 5 conformations with 1.5 million compounds in an afternoon (wall clock time)on Kraken supercomputer which would have taken 5 years of computation on typical cluster. This presentation will discuss about the process from project inception to generating results for publications and proposals for various funding agencies. PI quotes "I thought the computation might not be finished in my life span, this collaboration takes my research to new heights".
XSEDE支持:革新下一代治疗药物发现
药物发现是一项关键但复杂且昂贵的工作。FDA对新疗法的批准率一直在下降,而成本却在上升。越来越多的制药公司希望从学术研究转化药物发现,以降低风险。尽管许多研究人员已经确定了非常引人注目的目标,但由于开展发现活动所需的高成本和复杂的基础设施,大多数研究人员无法获得药物发现资源。本研究的长期目标是整合药物相互作用模拟软件,以最小的成本和时间识别新的生物活性分子,加快药物开发。这项技术是一种非常可行的方法,可以迅速缩小治疗差距,并有可能极大地改善公众健康。最初的研究是使用典型的簇进行的,用了3个月的时间,用150万个小分子对蛋白质的一种构象进行了一次测试。但研究人员感兴趣的是研究与整个疾病相关途径相关的许多蛋白质,每个蛋白质具有多种构象。按照这个速度,这项计算研究本身就需要在机构集群上进行6到7年的计算。这导致PI申请具有扩展协作支持服务(ECSS)支持的XSEDE分配,从而在XSEDE超级计算机上生成优化和扩展的药物相互作用工作流,将单次运行的计算时间从几个月减少到使用8000个核心的40分钟。结果是在Kraken超级计算机上一个下午(时钟时间)产生的5种蛋白质,5种构象,150万种化合物,这在典型的集群上需要5年的计算时间。本报告将讨论从项目开始到为各种资助机构的出版物和提案产生结果的过程。PI引用道:“我以为在我有生之年可能不会完成计算,这次合作将我的研究推向了新的高度。”
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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