A structural biology community assessment of AlphaFold2 applications

Akdel, Mehmet and Pires, Douglas E. V. and Pardo, Eduard Porta and Jänes, Jürgen and Zalevsky, Arthur O. and Mészáros, Bálint and Bryant, Patrick and Good, Lydia L. and Laskowski, Roman A. and Pozzati, Gabriele and Shenoy, Aditi and Zhu, Wensi and Kundrotas, Petras and Serra, Victoria Ruiz and Rodrigues, Carlos H. M. and Dunham, Alistair S. and Burke, David and Borkakoti, Neera and Velankar, Sameer and Frost, Adam and Basquin, Jérôme and Lindorff-Larsen, Kresten and Bateman, Alex and Kajava, Andrey V. and Valencia, Alfonso and Ovchinnikov, Sergey and Durairaj, Janani and Ascher, David B. and Thornton, Janet M. and Davey, Norman E. and Stein, Amelie and Elofsson, Arne and Croll, Tristan I. and Beltrao, Pedro. (2022) A structural biology community assessment of AlphaFold2 applications. Nature Structural and Molecular Biology, 29 (11). pp. 1056-1067.

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Most proteins fold into 3D structures that determine how they function and orchestrate the biological processes of the cell. Recent developments in computational methods for protein structure predictions have reached the accuracy of experimentally determined models. Although this has been independently verified, the implementation of these methods across structural-biology applications remains to be tested. Here, we evaluate the use of AlphaFold2 (AF2) predictions in the study of characteristic structural elements; the impact of missense variants; function and ligand binding site predictions; modeling of interactions; and modeling of experimental structural data. For 11 proteomes, an average of 25% additional residues can be confidently modeled when compared with homology modeling, identifying structural features rarely seen in the Protein Data Bank. AF2-based predictions of protein disorder and complexes surpass dedicated tools, and AF2 models can be used across diverse applications equally well compared with experimentally determined structures, when the confidence metrics are critically considered. In summary, we find that these advances are likely to have a transformative impact in structural biology and broader life-science research.
Faculties and Departments:05 Faculty of Science > Departement Biozentrum > Computational & Systems Biology > Bioinformatics (Schwede)
UniBasel Contributors:Durairaj, Janani
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Nature Publishing Group
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:13 Dec 2022 15:01
Deposited On:13 Dec 2022 15:01

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