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Keyword: protein scaffolds ×Clear all

3 claims from 1 paper

1. Biochemistry, Genetics and Molecular Biology › Protein Structure and Dynamics

   The Dayhoff Atlas: scaling sequence diversity for improved protein generation

   Yang, Alamdari, Lee et al. · bioRxiv (Cold Spring Harbor Laboratory) · 2025

   The authors present the Dayhoff Atlas of protein sequence data and language models, and report that training on metagenomic and synthetic sequences increased expression rates of generated proteins.

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   1. UncheckedThe Dayhoff Atlas introduces GigaRef, an open set of 3.34B natural protein sequences in 1.70B clusters, and BackboneRef, 46M synthetic sequences.“The Atlas introduces GigaRef, the largest open dataset of natural proteins, spanning 3.34B genomic and metagenomic sequences across 1.70B clusters, and BackboneRef, which distills structural information from 240,811 synthetic backbones into 46M synthetic sequences.”
   2. UncheckedDayhoff protein language models, trained on the new GigaRef and BackboneRef datasets, can predict mutation effects, scaffold motifs and generate proteins within families.“Leveraging these datasets, we trained the Dayhoff protein language models, which can predict mutation effects, scaffold structural motifs, and generate novel proteins within families.”
   3. UncheckedAdding metagenomic and structure-based synthetic sequences to training data raised the expression rates of proteins generated by the Dayhoff language models.“Training on metagenomic and structure-based synthetic sequences increased the expression rates of generated proteins, demonstrating the value of data diversity and scale.”