ProtGPT2 is a deep unsupervised language model for protein design

🤖 Plain-English Summary

Protein design aims to build novel proteins customized for specific purposes, thereby holding the potential to tackle many environmental and biomedical problems. AlphaFold prediction of ProtGPT2-sequences yields well-folded non-idealized structures with embodiments and large loops and reveals topologies not captured in current structure databases.

🔑 Key Findings

• Recent progress in Transformer-based architectures has enabled the implementation of language models capable of generating text with human-like capabilities.
• Here, motivated by this success, we describe ProtGPT2, a language model trained on the protein space that generates de novo protein sequences following the principles of natural ones.
• The generated proteins display natural amino acid propensities, while disorder predictions indicate that 88% of ProtGPT2-generated proteins are globular, in line with natural sequences.

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