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Article

Evolutionary profiles for protein fitness prediction.

Bioinformatics (Oxford, England) - 3 Aug 2026

Jiao Xiaoran, Lin Shengdong, Fan Jigang, Liang Zhanming, Mao Weian, Chen Hao, Shen Chunhua

Abstract excerpt

MOTIVATION: Predicting the fitness impact of mutations is central to protein engineering but constrained by limited assays relative to the size of sequence space. Protein language models (pLMs) trained with masked language modeling (MLM) exhibit strong zero-shot fitness prediction; we provide an interpretive lens by regarding natural evolution as implicit reward maximization and MLM as inverse reinforcement...

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PMID: 42475522
DOI: 10.1093/bioinformatics/btag525
PMCID: PMC13430659

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