Predicting protein electrostatics with protein language models nature.com

Researchers at the University of Maryland School of Pharmacy developed KaML-ESMs, sequence-based models using ESM protein language models to predict amino-acid pKa values. The models achieved about 0.5-unit error across six residue types in natural proteins, but performed worse on 89 buried engineered mutations; the team also applied the predictions to the human proteome to identify potential functional sites and catalytic mechanisms.