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DTSTART;TZID=America/Denver:20231115T164200
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UID:submissions.supercomputing.org_SC23_sess308_spostu111@linklings.com
SUMMARY:Navigating the Molecular Maze:  A Python-Powered Approach to Virtu
 al Drug Screening
DESCRIPTION:John Raicu (University of Chicago)\n\nThe COVID-19 pandemic ha
 s highlighted the power of using computational methods for virtual drug sc
 reening. However, the molecular search space is enormous and the common pr
 otein 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 t
 o identify promising candidates for screening.  We present ParslDock, a Py
 thon-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.\n\nRegistration Cate
 gory: Tech Program Reg Pass\n\nSession Chair: Ana Gainaru (Oak Ridge Natio
 nal Laboratory (ORNL))\n\n
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