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Unified rational protein engineering with sequence-only deep representation learning

Ethan C. Alley, Grigory Khimulya, View ORCID ProfileSurojit Biswas, Mohammed AlQuraishi, George M. Church
doi: https://doi.org/10.1101/589333
Ethan C. Alley
Wyss Institute for Biologically Inspired Engineering, Harvard University
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Grigory Khimulya
Cambridge, MA 02138, USA
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Surojit Biswas
Wyss Institute for Biologically Inspired Engineering, Harvard University
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Mohammed AlQuraishi
Department of Systems Biology, Harvard Medical School
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George M. Church
Wyss Institute for Biologically Inspired Engineering, Harvard UniversityDepartment of Genetics, Harvard Medical School
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  • For correspondence: gchurch@genetics.med.harvard.edu
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Abstract

Rational protein engineering requires a holistic understanding of protein function. Here, we apply deep learning to unlabelled amino acid sequences to distill the fundamental features of a protein into a statistical representation that is semantically rich and structurally, evolutionarily, and biophysically grounded. We show that the simplest models built on top of this unified representation (UniRep) are broadly applicable and generalize to unseen regions of sequence space. Our data-driven approach reaches near state-of-the-art or superior performance predicting stability of natural and de novo designed proteins as well as quantitative function of molecularly diverse mutants. UniRep further enables two orders of magnitude cost savings in a protein engineering task. We conclude UniRep is a versatile protein summary that can be applied across protein engineering informatics.

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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 March 26, 2019.
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Unified rational protein engineering with sequence-only deep representation learning
Ethan C. Alley, Grigory Khimulya, Surojit Biswas, Mohammed AlQuraishi, George M. Church
bioRxiv 589333; doi: https://doi.org/10.1101/589333
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Unified rational protein engineering with sequence-only deep representation learning
Ethan C. Alley, Grigory Khimulya, Surojit Biswas, Mohammed AlQuraishi, George M. Church
bioRxiv 589333; doi: https://doi.org/10.1101/589333

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