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Navigating the Molecular Maze: A Python-Powered Approach to Virtual Drug Screening
SessionPoster Reception
DescriptionThe COVID-19 pandemic has highlighted the power of using computational methods for virtual drug screening. However, the molecular search space is enormous and the common protein docking methods are still computationally intractable without access to the world’s largest supercomputers. Instead, researchers are using AI methods to provide a powerful new tool to help guide docking campaigns. In such approaches, a lightweight surrogate model is trained and then used to identify promising candidates for screening. We present ParslDock, a Python-based pipeline using the Parsl parallel programming library and the K-Nearest Neighbors machine learning model to screen a huge molecular space of molecules against arbitrary receptors. We achieved a 38X speedup with ParslDock compared to a brute-force docking approach.
Event Type
ACM Student Research Competition: Graduate Poster
ACM Student Research Competition: Undergraduate Poster
Doctoral Showcase
Posters
Research Posters
Scientific Visualization & Data Analytics Showcase
TimeTuesday, 14 November 20235:15pm - 7pm MST
LocationDEF Concourse
TP