IIDAI Seminar Series
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Speaker: Dr. Connor W. Coley, Associate Professor, MIT
Title: Tailoring generative AI to molecular design for early stage drug discovery
Abstract: Generative molecular design seeks to propose novel molecular structures that may surpass what is available in enumerated virtual libraries. While enumerated libraries are large, the enormity of chemical spaces means that there are ample opportunities for "creativity" in molecular design. In this talk, I will describe two recent projects that advance our ability to design molecular structures. First, I will introduce a 3D molecular generative model that facilitates interaction-aware chemical design by learning the joint distribution over 3D molecular structures and their shapes, electrostatics, and pharmacophores. Empirically, this model can sample chemically diverse molecules with highly enriched interaction-similarity to target structures, design small-molecule mimics of complex natural products, diversify bioactive hits while enriching docking scores despite having no knowledge of the protein, and merge fragments from experimental fragment screens into bioisosteric ligands. Second, I will describe a generative framework that mitigates lack of synthesizable as a major failure mode of molecular design. Our model ensures that every generated molecule has a viable synthetic pathway, enabling the design of analogs and optimization of molecular properties while maintaining synthetic feasibility. By providing effective and controllable navigation within synthesizable chemical space, we can provide actionable suggestions of new small organic molecules across a range of fields, including drug development and materials science.
Bio: https://coley.mit.edu/people
Connor W. Coley is the Class of 1957 Career Development Professor and an Associate Professor without tenure at MIT in the Department of Chemical Engineering and the Department of Electrical Engineering and Computer Science. He received his B.S. and Ph.D. in Chemical Engineering from Caltech and MIT, respectively, and did his postdoctoral training at the Broad Institute. His research group at MIT works at the interface of chemistry and data science to develop models that understand how moleculesbehave, interact, and react and use that knowledge to engineer new ones, with an emphasis on therapeutic discovery. Connor is a recipient of C&EN’s “Talented Twelve” award, Forbes Magazine’s “30 Under 30” for Healthcare, Technology Review’s 35 Innovators Under 35, the NSF CAREER award, the ACS COMP OpenEye Outstanding Junior Faculty Award, the Bayer Early Excellence in Science Award, the 3M NTFA, and was named a Schmidt AI2050 Early Career Fellow, a 2023 Samsung AI Researcher of the Year, and a Scialog Fellow (Automating Chemical Laboratories). Connor has been recognized for his teaching and mentorship by MIT’s inaugural Common Ground Award for Excellence in Teaching, the 2024 Outstanding UROP Mentor Award, and the 2024 James W. Swan Outstanding Faculty Award for Graduate Teaching in Chemical Engineering.
Date and Time: March 6, 2025, 11am-noon ET / 10-11am CT
Location: IBM Thomas J. Watson Research Center
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