A structural biology community assessment of AlphaFold2 applications.
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ICR Authors
Authors
Akdel, M
Pires, DEV
Pardo, EP
Jänes, J
Zalevsky, AO
Mészáros, B
Bryant, P
Good, LL
Laskowski, RA
Pozzati, G
Shenoy, A
Zhu, W
Kundrotas, P
Serra, VR
Rodrigues, CHM
Dunham, AS
Burke, D
Borkakoti, N
Velankar, S
Frost, A
Basquin, J
Lindorff-Larsen, K
Bateman, A
Kajava, AV
Valencia, A
Ovchinnikov, S
Durairaj, J
Ascher, DB
Thornton, JM
Davey, NE
Stein, A
Elofsson, A
Croll, TI
Beltrao, P
Pires, DEV
Pardo, EP
Jänes, J
Zalevsky, AO
Mészáros, B
Bryant, P
Good, LL
Laskowski, RA
Pozzati, G
Shenoy, A
Zhu, W
Kundrotas, P
Serra, VR
Rodrigues, CHM
Dunham, AS
Burke, D
Borkakoti, N
Velankar, S
Frost, A
Basquin, J
Lindorff-Larsen, K
Bateman, A
Kajava, AV
Valencia, A
Ovchinnikov, S
Durairaj, J
Ascher, DB
Thornton, JM
Davey, NE
Stein, A
Elofsson, A
Croll, TI
Beltrao, P
Document Type
Journal Article
Date
2022-11-01
Date Accepted
2022-09-20
Abstract
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.
Citation
Nature Structural and Molecular Biology, 2022, 29 (11), pp. 1056 - 1067
Source Title
Nature Structural and Molecular Biology
Publisher
Springer Science and Business Media LLC
ISSN
1545-9993
eISSN
1545-9985
1545-9985
1545-9985
Collections
Research Team
Short Linear Motif