ProtGPT2 is a deep unsupervised language model for protein design
Universitat de Girona · University of Bayreuth
Abstract
Protein design aims to build novel proteins customized for specific purposes, thereby holding the potential to tackle many environmental and biomedical problems. 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. Sensitive sequence searches…
Citation impact
- FWCI
- 57.43
- Percentile
- 100%
- References
- 71
Authors
3Topics & keywords
- Computer science
- Protein design
- Computational biology
- Natural language
- Protein structure
- Similarity (geometry)
- Bridging (networking)
- Protein sequencing