虚拟筛选
云计算
可扩展性
计算机科学
工作流程
相似性(几何)
资源(消歧)
虚拟机
缩放比例
药物发现
分布式计算
数据科学
数据库
人工智能
操作系统
生物信息学
计算机网络
图像(数学)
生物
几何学
数学
作者
Christoph Grebner,Erik Malmerberg,Andrew Shewmaker,José Batista,Anthony Nicholls,Jens Sadowski
标识
DOI:10.1021/acs.jcim.9b00779
摘要
Virtual screening is a standard tool in Computer-Assisted Drug Design (CADD). Early in a project, it is typical to use ligand-based similarity search methods to find suitable hit molecules. However, the number of compounds which can be screened and the time required are usually limited by computational resources. We describe here a high-throughput virtual screening project using 3D similarity (FastROCS) and automated evaluation workflows on Orion, a cloud computing platform. Cloud resources make this approach fully scalable and flexible, allowing the generation and search of billions of virtual molecules, and give access to an explicit 3D virtual chemistry space not available before. We discuss the impact of the size of the search space with respect to finding novel chemical hits and the size of the required hit list, as well as computational and economical aspects of resource scaling.
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