2022 ACA session on AI predicted Models in Structural Biology/Crystallography
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
participants (1)
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Aaron Brewster