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ProGen: Language Modeling for Protein Generation

Ali Madani, Bryan McCann, Nikhil Naik, Nitish Shirish Keskar, Namrata Anand, Raphael R. Eguchi, View ORCID ProfilePo-Ssu Huang, Richard Socher
doi: https://doi.org/10.1101/2020.03.07.982272
Ali Madani
1Salesforce Research, Palo Alto, CA, USA
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  • For correspondence: amadani@salesforce.com
Bryan McCann
1Salesforce Research, Palo Alto, CA, USA
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Nikhil Naik
1Salesforce Research, Palo Alto, CA, USA
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Nitish Shirish Keskar
1Salesforce Research, Palo Alto, CA, USA
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Namrata Anand
2Department of Bioengineering, Stanford University, Stanford, CA, USA
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Raphael R. Eguchi
2Department of Bioengineering, Stanford University, Stanford, CA, USA
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Po-Ssu Huang
2Department of Bioengineering, Stanford University, Stanford, CA, USA
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  • ORCID record for Po-Ssu Huang
Richard Socher
1Salesforce Research, Palo Alto, CA, USA
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Abstract

Generative modeling for protein engineering is key to solving fundamental problems in synthetic biology, medicine, and material science. We pose protein engineering as an unsupervised sequence generation problem in order to leverage the exponentially growing set of proteins that lack costly, structural annotations. We train a 1.2B-parameter language model, ProGen, on ∼280M protein sequences conditioned on taxonomic and keyword tags such as molecular function and cellular component. This provides ProGen with an unprecedented range of evolutionary sequence diversity and allows it to generate with fine-grained control as demonstrated by metrics based on primary sequence similarity, secondary structure accuracy, and conformational energy.

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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 08, 2020.
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ProGen: Language Modeling for Protein Generation
Ali Madani, Bryan McCann, Nikhil Naik, Nitish Shirish Keskar, Namrata Anand, Raphael R. Eguchi, Po-Ssu Huang, Richard Socher
bioRxiv 2020.03.07.982272; doi: https://doi.org/10.1101/2020.03.07.982272
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ProGen: Language Modeling for Protein Generation
Ali Madani, Bryan McCann, Nikhil Naik, Nitish Shirish Keskar, Namrata Anand, Raphael R. Eguchi, Po-Ssu Huang, Richard Socher
bioRxiv 2020.03.07.982272; doi: https://doi.org/10.1101/2020.03.07.982272

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