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Dear colleagues,

We’ll be hosting a special guest lecture by Prof. John Moult from UMD.

Abstract:
Computing the three-dimensional structure of a protein molecule from its amino acid
sequence is a long-standing grand challenge problem. Results from the recent Critical
Assessment of Structure Prediction (CASP14) experiment show that new deep-learning
methods have now provided a dramatic solution, with many computed structures
comparable, likely sometimes better, representations of in vivo protein structures to
those obtained with state-of-the-art experimental techniques of crystallography and
cryo-electron microscopy. These models have already demonstrated an ability to solve
problematic crystal structures, and the results suggest the methods will be successfully
applied to other areas of structural biology and more generally. This is the first solution
of a serious scientific problem by AI, and it will not be the last.
In this talk I’ll describe how the protein modeling field arrived at this point, what sort of
methods were used, characteristics of the computed structures, and some potential
further applications.

Bio:
John Moult is a Fellow at the Institute for Bioscience and Biotechnology Research and
Professor in the Department of Cell Biology and Molecular Genetics at the University of
Maryland. He is co-founder and Chair of CASP (Critical Assessment of Protein structure
Prediction), an organization that conducts large-scale experiments in protein structure
modeling, and joint founder of CAGI, a sister organization for advancing genome
interpretation. He is an ex-crystallographer turned computational biologist. His research
interests include the relationship between genetic variation and human disease, disease
mechanisms, protein structure, and different ways of doing science. (BSc Physics, University of London 1965, D.Phil Molecular Biophysics, University of Oxford 1970)

Join Zoom Meeting
https://umd.zoom.us/j/97941931766

Meeting ID: 979 4193 1766
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