TL;DR
It is shown that model size, training dataset and stochastic elements can bias the predicted p(sequence) away from real fitness, which clarifies the scaling behavior of protein models on fitness prediction and provides practical guidelines for their application and future development.
A parameter sweep is implemented to explicitly couple empirical nucleotide mutational supply from PLM-assessed amino acid substitution pseudo-probabilities across evolutionary forecasting tasks and finds that base PLMs implicitly learn generic nucleotide-level mutational constraints, an effect strongly amplified by vir...
Multiple sequence alignment (MSA) Pairformer is presented, a protein language model that builds on AlphaFold2/3's bidirectional refinement between sequence and pairwise residue representations to accurately model the evolution of protein-protein interactions, despite training exclusively on individual chains.
It is found that many GigaRef singletons belong to a cluster under alternative parameter settings, suggesting that genomic and metagenomic datasets may require dataset-specific clustering configurations, and it is shown that singletons share mutual information with clustered sequences, making them learnable by PLMs and...
MAXWELL (Matrix-wise Landscape Learning), a novel post-training method that calibrates the probabilistic outputs learned by protein language models during pretraining to generate mutational landscapes that quantify the effects of individual amino acid substitutions on protein stability, is introduced.
It is determined that portions of protein sequence space, despite being unobserved in nature, contains many functional proteins that cannot be predicted accurately in silico, providing experimental support for the hypothesis that natural protein sequences explored by evolution represent a miniscule fraction of all poss...
This work developed a scoring-approach for AI-agents to autonomously assess AlphaGenome prediction confidence and accurately differentiate between AlphaGenome’s robust sequence-level recognition across species and its current limitations when interpreting un-fine-mapped regulatory variants.
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