Pérez-Sánchez Horacio, Rezaei Vahid, Mezhuyev Vitaliy, Man Duhu, Peña-García Jorge, den-Haan Helena, Gesing Sandra
Bioinformatics and High Performance Computing Research Group (BIO-HPC), Computer Engineering Department, Universidad Catolica San Antonio de Murcia (UCAM), Murcia, Spain.
Department of Statistics, Faculty of Mathematics and Computer Sciences, Allameh Tabataba'i University, Tehran, Iran.
Springerplus. 2016 Aug 9;5(1):1300. doi: 10.1186/s40064-016-2914-x. eCollection 2016.
Methods for in silico screening of large databases of molecules increasingly complement and replace experimental techniques to discover novel compounds to combat diseases. As these techniques become more complex and computationally costly we are faced with an increasing problem to provide the research community of life sciences with a convenient tool for high-throughput virtual screening on distributed computing resources.
To this end, we recently integrated the biophysics-based drug-screening program FlexScreen into a service, applicable for large-scale parallel screening and reusable in the context of scientific workflows.
Our implementation is based on Pipeline Pilot and Simple Object Access Protocol and provides an easy-to-use graphical user interface to construct complex workflows, which can be executed on distributed computing resources, thus accelerating the throughput by several orders of magnitude.
对大量分子数据库进行计算机模拟筛选的方法越来越多地补充并取代实验技术,以发现对抗疾病的新型化合物。随着这些技术变得更加复杂且计算成本高昂,我们面临着一个日益严峻的问题,即要为生命科学研究群体提供一种便捷工具,以便在分布式计算资源上进行高通量虚拟筛选。
为此,我们最近将基于生物物理学的药物筛选程序FlexScreen集成到一项服务中,该服务适用于大规模并行筛选,并可在科学工作流程中重复使用。
我们的实现基于管道先导(Pipeline Pilot)和简单对象访问协议(Simple Object Access Protocol),并提供易于使用的图形用户界面来构建复杂的工作流程,这些工作流程可在分布式计算资源上执行,从而将通量提高几个数量级。