Accelerating protein engineering: an integrated framework combines protein language models and epistatic landscape modeling

Abstract

In a recent study published in Science , Tran et al. introduced MULTI-evolve (model guided, universal, targeted installation of multimutants), a machine learning-guided directed evolution (MLDE) framework that rapidly designs hyperactive multimutant proteins. 1 By integrating protein language models (PLMs), epistasis-aware modeling, and a high-efficiency multisite mutagenesis platform, the authors address the major combinatorial challenge that has long bottlenecked protein engineering and therapeutic development.