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Breaking the conformational ensemble barrier: Ensemble structure modeling challenges in CASP15
  • +3
  • Andriy Kryshtafovych,
  • Gaetano Montelione,
  • Daniel Rigden,
  • Shahram Mesdaghi,
  • Ezgi Karaca,
  • John Moult
Andriy Kryshtafovych
University of California Davis Genome Center
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Gaetano Montelione
Rensselaer Polytechnic Institute Department of Chemistry and Chemical Biology
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Daniel Rigden
University of Liverpool Institute of Systems Molecular and Integrative Biology
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Shahram Mesdaghi
University of Liverpool Institute of Systems Molecular and Integrative Biology
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Ezgi Karaca
─░zmir Biomedicine and Genome Center
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John Moult
Institute for Bioscience and Biotechnology Research

Corresponding Author:[email protected]

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For the first time, the 2022 CASP (Critical Assessment of Structure Prediction) community experiment included a section on computing multiple conformations for protein and RNA structures. There was full or partial success in reproducing the ensembles for four of the nine targets, an encouraging result. For protein structures, enhanced sampling with variations of the AlphaFold2 deep learning method was by far the most effective approach. One substantial conformational change caused by a single mutation across a complex interface was accurately reproduced. In two other assembly modeling cases, methods succeeded in sampling conformations near to the experimental ones even though environmental factors were not included in the calculations. An experimentally derived flexibility ensemble allowed a single accurate RNA structure model to be identified. Difficulties included how to handle sparse or low-resolution experimental data and the current lack of effective methods for modeling RNA/protein complexes. However, these and other obstacles appear addressable.
14 Aug 2023Submitted to PROTEINS: Structure, Function, and Bioinformatics
14 Aug 2023Assigned to Editor
14 Aug 2023Submission Checks Completed
14 Aug 2023Review(s) Completed, Editorial Evaluation Pending
14 Aug 2023Editorial Decision: Accept