论文标题
使用贝叶斯优化来加速虚拟筛查，以发现适合于Covid-19的治疗剂
Using Bayesian Optimization to Accelerate Virtual Screening for the Discovery of Therapeutics Appropriate for Repurposing for COVID-19
论文作者
论文摘要
这部小说的武汉冠状病毒被称为SARS-COV-2给非战场环境带来了几乎前所未有的效果，击中了社会，经济和卫生系统。通过高通量虚拟筛选方法具有对SARS-COV-2的所需活动。在这种交流中，我们演示了贝叶斯优化的使用如何为这些计算的优先级提供有价值的服务，从而导致对高性能候选人的加速识别，从而扩大HPC系统实用程序的范围，以进行时间关键筛查。
The novel Wuhan coronavirus known as SARS-CoV-2 has brought almost unprecedented effects for a non-wartime setting, hitting social, economic and health systems hard.~ Being able to bring to bear pharmaceutical interventions to counteract its effects will represent a major turning point in the fight to turn the tides in this ongoing battle.~ Recently, the World's most powerful supercomputer, SUMMIT, was used to identify existing small molecule pharmaceuticals which may have the desired activity against SARS-CoV-2 through a high throughput virtual screening approach. In this communication, we demonstrate how the use of Bayesian optimization can provide a valuable service for the prioritisation of these calculations, leading to the accelerated identification of high-performing candidates, and thus expanding the scope of the utility of HPC systems for time critical screening
