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Neural Potts Model

Tom Sercu, Robert Verkuil, Joshua Meier, Brandon Amos, Zeming Lin, Caroline Chen, Jason Liu, Yann LeCun, Alexander Rives
doi: https://doi.org/10.1101/2021.04.08.439084
Tom Sercu
1Facebook AI Research
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Robert Verkuil
1Facebook AI Research
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Joshua Meier
1Facebook AI Research
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Brandon Amos
1Facebook AI Research
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Zeming Lin
2New York University
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Caroline Chen
3Facebook AI
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Jason Liu
1Facebook AI Research
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Yann LeCun
5FAIR, NYU
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Alexander Rives
5FAIR, NYU
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  • For correspondence: arives@cs.nyu.edu
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Abstract

We propose the Neural Potts Model objective as an amortized optimization problem. The objective enables training a single model with shared parameters to explicitly model energy landscapes across multiple protein families. Given a protein sequence as input, the model is trained to predict a pairwise coupling matrix for a Potts model energy function describing the local evolutionary landscape of the sequence. Couplings can be predicted for novel sequences. A controlled ablation experiment assessing unsupervised contact prediction on sets of related protein families finds a gain from amortization for low-depth multiple sequence alignments; the result is then confirmed on a database with broad coverage of protein sequences.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • tsercubda{at}fb.com,rverkuilbda{at}fb.com,jmeierbda{at}fb.com

  • zl2799{at}nyu.edu

  • carolinechen{at}fb.com

  • jasonliu{at}fb.com

  • yann,arives{at}cs.nyu.edu

  • ↵† Work performed while at Facebook AI Research

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted April 11, 2021.
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Neural Potts Model
Tom Sercu, Robert Verkuil, Joshua Meier, Brandon Amos, Zeming Lin, Caroline Chen, Jason Liu, Yann LeCun, Alexander Rives
bioRxiv 2021.04.08.439084; doi: https://doi.org/10.1101/2021.04.08.439084
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Neural Potts Model
Tom Sercu, Robert Verkuil, Joshua Meier, Brandon Amos, Zeming Lin, Caroline Chen, Jason Liu, Yann LeCun, Alexander Rives
bioRxiv 2021.04.08.439084; doi: https://doi.org/10.1101/2021.04.08.439084

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