Structure-aware generation of molecules in protein pockets

Add to your list(s) Download to your calendar using vCal

• Pavol Drotar
• Tuesday 08 June 2021, 13:15-14:15
• Zoom.

If you have a question about this talk, please contact Mateja Jamnik.

Join us on Zoom

Searching the vast chemical space for potential drugs is intractable even for computational screening approaches, though deep generative methods have shown promise in proposing novel molecules from scratch (de-novo design). However, most models fail to incorporate 3D protein structures that are salient in designing drugs that bind to protein targets. I present a novel supervised approach that combines insights from graph-generative and 3D models and constructs drugs inside protein pockets, atom-by-atom, guided by structural information from crystallographic drug datasets. I find that the model improves binding affinities on average by 8% and druglikeness scores by 10% over the non-guided baseline, and proposes some molecules that exceed the binding scores of known ligands.

This talk is part of the Artificial Intelligence Research Group Talks (Computer Laboratory) series.

This talk is included in these lists:

• All Talks (aka the CURE list)
• Artificial Intelligence Research Group Talks (Computer Laboratory)
• Cambridge Centre for Data-Driven Discovery (C2D3)
• Cambridge Forum of Science and Humanities
• Cambridge Language Sciences
• Cambridge talks
• Chris Davis' list
• Department of Computer Science and Technology talks and seminars
• Guy Emerson's list
• Hanchen DaDaDash
• Interested Talks
• School of Technology
• Speech Seminars
• Trust & Technology Initiative - interesting events
• Zoom
• bld31
• ndk22's list
• ob366-ai4er
• rp587
• yk373's list

Note that ex-directory lists are not shown.