A structural biology community assessment of AlphaFold2 applications

Research output: Contribution to journal › Journal article › Research › peer-review

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

In: Nature Structural & Molecular Biology, Vol. 29, No. 11, 2022.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Akdel, M, Pires, DE, Porta Pardo, E, Jänes, J, Zalevsky, AO, Meszaros, 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, A, Valencia, A, Ovchinnikov, S, Durairaj, J, Ascher, DB, Thornton, JM, Davey, NE, Stein, A, Elofsson, A, Croll, T & Beltrao, P 2022, 'A structural biology community assessment of AlphaFold2 applications', Nature Structural & Molecular Biology, vol. 29, no. 11. https://doi.org/10.1038/s41594-022-00849-w

APA

Akdel, M., Pires, D. E., Porta Pardo, E., Jänes, J., Zalevsky, A. O., Meszaros, B., Bryant, P., Good, L. L., Laskowski, R. A., Pozzati, G., Shenoy, A., Zhu, W., Kundrotas, P., Serra, V. R., Rodrigues, C. H. M., Dunham, A. S., Burke, D., Borkakoti, N., Velankar, S., ... Beltrao, P. (2022). A structural biology community assessment of AlphaFold2 applications. Nature Structural & Molecular Biology, 29(11). https://doi.org/10.1038/s41594-022-00849-w

Vancouver

Akdel M, Pires DE, Porta Pardo E, Jänes J, Zalevsky AO, Meszaros B et al. A structural biology community assessment of AlphaFold2 applications. Nature Structural & Molecular Biology. 2022;29(11). https://doi.org/10.1038/s41594-022-00849-w

Author

Akdel, Mehmet ; Pires, Douglas E. ; Porta Pardo, Eduard ; Jänes, Jürgen ; Zalevsky, Arthur O. ; Meszaros, Balint ; Bryant, Patrick ; Good, Lydia L. ; Laskowski, Roman A. ; Pozzati, Gabriele ; Shenoy, Aditi ; Zhu, Wensi ; Kundrotas, Petras ; Serra, Victoria Ruiz ; Rodrigues, Carlos H. M. ; Dunham, Alistair S. ; Burke, David ; Borkakoti, Neera ; Velankar, Sameer ; Frost, Adam ; Basquin, Jérôme ; Lindorff-Larsen, Kresten ; Bateman, Alex ; Kajava, Andrey ; Valencia, Alfonso ; Ovchinnikov, Sergey ; Durairaj, Janani ; Ascher, David B. ; Thornton, Janet M. ; Davey, Norman E. ; Stein, Amelie ; Elofsson, Arne ; Croll, Tristan ; Beltrao, Pedro. / A structural biology community assessment of AlphaFold2 applications. In: Nature Structural & Molecular Biology. 2022 ; Vol. 29, No. 11.

Bibtex

@article{c22cd76166b14095b1efc324b957cd62,
title = "A structural biology community assessment of AlphaFold2 applications",
abstract = "Here, the authors evaluate the performance of AlphaFold2 and its predicted structures on common structural biological applications, including missense variants, function and ligand binding site prediction, modeling of interactions and modeling of experimental structural data.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.",
keywords = "PROTEIN STABILITY, MUTATIONS, PREDICTION, FEATURES, SERVER, IDENTIFICATION, SEQUENCE, DOCKING, SPACE, TOOL",
author = "Mehmet Akdel and Pires, {Douglas E.} and {Porta Pardo}, Eduard and J{\"u}rgen J{\"a}nes and Zalevsky, {Arthur O.} and Balint Meszaros and Patrick Bryant and Good, {Lydia L.} and Laskowski, {Roman A.} and Gabriele Pozzati and Aditi Shenoy and Wensi Zhu and Petras Kundrotas and Serra, {Victoria Ruiz} and Rodrigues, {Carlos H. M.} and Dunham, {Alistair S.} and David Burke and Neera Borkakoti and Sameer Velankar and Adam Frost and J{\'e}r{\^o}me Basquin and Kresten Lindorff-Larsen and Alex Bateman and Andrey Kajava and Alfonso Valencia and Sergey Ovchinnikov and Janani Durairaj and Ascher, {David B.} and Thornton, {Janet M.} and Davey, {Norman E.} and Amelie Stein and Arne Elofsson and Tristan Croll and Pedro Beltrao",
year = "2022",
doi = "10.1038/s41594-022-00849-w",
language = "English",
volume = "29",
journal = "Nature Structural and Molecular Biology",
issn = "1545-9993",
publisher = "nature publishing group",
number = "11",

}

RIS

TY - JOUR

T1 - A structural biology community assessment of AlphaFold2 applications

AU - Akdel, Mehmet

AU - Pires, Douglas E.

AU - Porta Pardo, Eduard

AU - Jänes, Jürgen

AU - Zalevsky, Arthur O.

AU - Meszaros, Balint

AU - Bryant, Patrick

AU - Good, Lydia L.

AU - Laskowski, Roman A.

AU - Pozzati, Gabriele

AU - Shenoy, Aditi

AU - Zhu, Wensi

AU - Kundrotas, Petras

AU - Serra, Victoria Ruiz

AU - Rodrigues, Carlos H. M.

AU - Dunham, Alistair S.

AU - Burke, David

AU - Borkakoti, Neera

AU - Velankar, Sameer

AU - Frost, Adam

AU - Basquin, Jérôme

AU - Lindorff-Larsen, Kresten

AU - Bateman, Alex

AU - Kajava, Andrey

AU - Valencia, Alfonso

AU - Ovchinnikov, Sergey

AU - Durairaj, Janani

AU - Ascher, David B.

AU - Thornton, Janet M.

AU - Davey, Norman E.

AU - Stein, Amelie

AU - Elofsson, Arne

AU - Croll, Tristan

AU - Beltrao, Pedro

PY - 2022

Y1 - 2022

N2 - Here, the authors evaluate the performance of AlphaFold2 and its predicted structures on common structural biological applications, including missense variants, function and ligand binding site prediction, modeling of interactions and modeling of experimental structural data.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.

AB - Here, the authors evaluate the performance of AlphaFold2 and its predicted structures on common structural biological applications, including missense variants, function and ligand binding site prediction, modeling of interactions and modeling of experimental structural data.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.

KW - PROTEIN STABILITY

KW - MUTATIONS

KW - PREDICTION

KW - FEATURES

KW - SERVER

KW - IDENTIFICATION

KW - SEQUENCE

KW - DOCKING

KW - SPACE

KW - TOOL

U2 - 10.1038/s41594-022-00849-w

DO - 10.1038/s41594-022-00849-w

M3 - Journal article

C2 - 36344848

VL - 29

JO - Nature Structural and Molecular Biology

JF - Nature Structural and Molecular Biology

SN - 1545-9993

IS - 11

ER -

ID: 329743063