[phenixbb] 2022 ACA session on AI predicted Models in Structural Biology/Crystallography

[Aaron Brewster]

Hi all, we'd like to call your attention to the upcoming session at the
2022 ACA on the use of AI predicted Models in Structural
Biology/Crystallography.  We'd like to invite abstract submissions to this
session from people, including early-career scientists, who have done
difficult or interesting work using these AI predicted structural models,
such as from AlphaFold2 and RoseTTAFold.  We are very excited to hear what
people are using these tools for and how the future might unfold in this
new world of AI-aided structural analysis and design.  Remember that the
deadline to submit an abstract for talks is April 15, 2022@ 11:59 PM ET.

The full abstract for the session is below.  Thanks,
-Aaron Brewster and John Moult

Prediction of 3D protein structure by AlphaFold2 and RoseTTAFold has
achieved revolutionary accuracy using new AI methods. These programs can
accurately predict the 3D structure of many proteins from 1D amino acid
sequences, opening up a vast array of exciting new experiments and
challenges for researchers.  In this session we will explore current
applications of these structures in molecular replacement, cryo-EM fitting
and refinement, structure-based drug design, and tomography.  We will
explore what kinds of new and difficult methods have been enabled and what
remains difficult.  Other topics may include how error estimates on AI
protein models can be incorporated into these methods, progress in modeling
of protein complexes, implications of AI structures on protein design, the
generation and use of structure ensembles, and new data analysis best
practices that need to be developed as the use of computer-generated
structures becomes more common.

Sponsored by the BioMAC and Best Practices for Data Analysis and Archiving
SIGs
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