Kryshtafovych, Andriy ORCID: 0000-0001-5066-7178, Montelione, Gaetano T ORCID: 0000-0002-9440-3059, Rigden, Daniel J ORCID: 0000-0002-7565-8937, Mesdaghi, Shahram, Karaca, Ezgi ORCID: 0000-0002-4926-7991 and Moult, John
(2023)
Breaking the conformational ensemble barrier: Ensemble structure modeling challenges in CASP15.
Proteins, 91 (12).
pp. 1903-1911.
Abstract
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.
Item Type: | Article |
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Uncontrolled Keywords: | Proteins, RNA, Protein Conformation, Mutation |
Divisions: | Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Systems, Molecular and Integrative Biology Faculty of Health and Life Sciences > Tech, Infrastructure and Environmental Directorate |
Depositing User: | Symplectic Admin |
Date Deposited: | 15 Mar 2024 16:36 |
Last Modified: | 15 Mar 2024 19:55 |
DOI: | 10.1002/prot.26584 |
Open Access URL: | https://onlinelibrary.wiley.com/doi/10.1002/prot.2... |
Related URLs: | |
URI: | https://livrepository.liverpool.ac.uk/id/eprint/3179499 |