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Protein complex prediction with AlphaFold-Multimer

View ORCID ProfileRichard Evans, View ORCID ProfileMichael O’Neill, View ORCID ProfileAlexander Pritzel, Natasha Antropova, View ORCID ProfileAndrew Senior, View ORCID ProfileTim Green, Augustin Žídek, View ORCID ProfileRuss Bates, View ORCID ProfileSam Blackwell, View ORCID ProfileJason Yim, View ORCID ProfileOlaf Ronneberger, View ORCID ProfileSebastian Bodenstein, Michal Zielinski, Alex Bridgland, View ORCID ProfileAnna Potapenko, View ORCID ProfileAndrew Cowie, View ORCID ProfileKathryn Tunyasuvunakool, View ORCID ProfileRishub Jain, View ORCID ProfileEllen Clancy, View ORCID ProfilePushmeet Kohli, View ORCID ProfileJohn Jumper, View ORCID ProfileDemis Hassabis
doi: https://doi.org/10.1101/2021.10.04.463034
Richard Evans
1DeepMind, London, UK
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Michael O’Neill
1DeepMind, London, UK
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Alexander Pritzel
1DeepMind, London, UK
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Natasha Antropova
1DeepMind, London, UK
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Andrew Senior
1DeepMind, London, UK
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Tim Green
1DeepMind, London, UK
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Augustin Žídek
1DeepMind, London, UK
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Russ Bates
1DeepMind, London, UK
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Sam Blackwell
1DeepMind, London, UK
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Jason Yim
1DeepMind, London, UK
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Olaf Ronneberger
1DeepMind, London, UK
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Sebastian Bodenstein
1DeepMind, London, UK
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Michal Zielinski
1DeepMind, London, UK
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Alex Bridgland
1DeepMind, London, UK
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Anna Potapenko
1DeepMind, London, UK
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Andrew Cowie
1DeepMind, London, UK
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Kathryn Tunyasuvunakool
1DeepMind, London, UK
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Rishub Jain
1DeepMind, London, UK
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Ellen Clancy
1DeepMind, London, UK
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Pushmeet Kohli
1DeepMind, London, UK
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John Jumper
1DeepMind, London, UK
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  • For correspondence: jumper@deepmind.com dhcontact@deepmind.com
Demis Hassabis
1DeepMind, London, UK
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  • For correspondence: jumper@deepmind.com dhcontact@deepmind.com
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Abstract

While the vast majority of well-structured single protein chains can now be predicted to high accuracy due to the recent AlphaFold [1] model, the prediction of multi-chain protein complexes remains a challenge in many cases. In this work, we demonstrate that an AlphaFold model trained specifically for multimeric inputs of known stoichiometry, which we call AlphaFold-Multimer, significantly increases accuracy of predicted multimeric interfaces over input-adapted single-chain AlphaFold while maintaining high intra-chain accuracy. On a benchmark dataset of 17 heterodimer proteins without templates (introduced in [2]) we achieve at least medium accuracy (DockQ [3] ≥ 0.49) on 14 targets and high accuracy (DockQ ≥ 0.8) on 6 targets, compared to 9 targets of at least medium accuracy and 4 of high accuracy for the previous state of the art system (an AlphaFold-based system from [2]). We also predict structures for a large dataset of 4,433 recent protein complexes, from which we score all non-redundant interfaces with low template identity. For heteromeric interfaces we successfully predict the interface (DockQ ≥ 0.23) in 67% of cases, and produce high accuracy predictions (DockQ ≥ 0.8) in 23% of cases, an improvement of +25 and +11 percentage points over the flexible linker modification of AlphaFold [4] respectively. For homomeric interfaces we successfully predict the interface in 69% of cases, and produce high accuracy predictions in 34% of cases, an improvement of +5 percentage points in both instances.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted October 04, 2021.
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Protein complex prediction with AlphaFold-Multimer
Richard Evans, Michael O’Neill, Alexander Pritzel, Natasha Antropova, Andrew Senior, Tim Green, Augustin Žídek, Russ Bates, Sam Blackwell, Jason Yim, Olaf Ronneberger, Sebastian Bodenstein, Michal Zielinski, Alex Bridgland, Anna Potapenko, Andrew Cowie, Kathryn Tunyasuvunakool, Rishub Jain, Ellen Clancy, Pushmeet Kohli, John Jumper, Demis Hassabis
bioRxiv 2021.10.04.463034; doi: https://doi.org/10.1101/2021.10.04.463034
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Protein complex prediction with AlphaFold-Multimer
Richard Evans, Michael O’Neill, Alexander Pritzel, Natasha Antropova, Andrew Senior, Tim Green, Augustin Žídek, Russ Bates, Sam Blackwell, Jason Yim, Olaf Ronneberger, Sebastian Bodenstein, Michal Zielinski, Alex Bridgland, Anna Potapenko, Andrew Cowie, Kathryn Tunyasuvunakool, Rishub Jain, Ellen Clancy, Pushmeet Kohli, John Jumper, Demis Hassabis
bioRxiv 2021.10.04.463034; doi: https://doi.org/10.1101/2021.10.04.463034

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