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DTSTART;TZID=America/New_York:20221026T120000
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SUMMARY:ASSET Seminar: How to Design Molecules that Dock Well but Can't Exist\, Jacob Gardner\, Ph.D.
DESCRIPTION:ABSTRACT:BIO \nMachine learning has become an indispensable aid to researchers developing the next generation of novel therapeutics. In this talk\, I will discuss how some of the most important problems  in virtual screening for new potential drug molecules can be cast as black-box optimization problems\, where the goal is to find molecules maximizing some desired property — for example\, the binding affinity to a known drug target. By leveraging recent work on representation learning for molecules and high dimensional black-box optimization\, we are able to achieve up to a 20x performance improvement over state of the art on several of the most widely used benchmarks for molecule design. I will then show how this powerful new approach reveals flaws in tools commonly used for computational molecule design. Even the most widely used docking simulators can be fooled by a sufficiently powerful optimizer producing molecules that could not plausibly exist in nature — a challenge reminiscent of adversarial image generation in computer vision. These findings can be mitigated to a degree through the use of constrained optimization\, but also motivate adapting lessons from robust machine learning to the docking simulators themselves.
URL:https://seasevents.nmsdev7.com/event/asset-seminar-tba-jake-gardner-university-of-pennsylvania/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
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