High-Throughput Virtual Laboratory For Drug Discovery Using Massive Datasets

INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS(2021)

引用 22|浏览28
暂无评分
摘要
Time-to-solution for structure-based screening of massive chemical databases for COVID-19 drug discovery has been decreased by an order of magnitude, and a virtual laboratory has been deployed at scale on up to 27,612 GPUs on the Summit supercomputer, allowing an average molecular docking of 19,028 compounds per second. Over one billion compounds were docked to two SARS-CoV-2 protein structures with full optimization of ligand position and 20 poses per docking, each in under 24 hours. GPU acceleration and high-throughput optimizations of the docking program produced 350x mean speedup over the CPU version (50x speedup per node). GPU acceleration of both feature calculation for machine-learning based scoring and distributed database queries reduced processing of the 2.4 TB output by orders of magnitude. The resulting 50x speedup for the full pipeline reduces an initial 43 day runtime to 21 hours per protein for providing high-scoring compounds to experimental collaborators for validation assays.
更多
查看译文
关键词
High-throughput virtual screening, drug discovery, GPU acceleration, high-performance database query
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要