Olexandr Isayev

This paper introduces a physics-based framework for enzyme engineering that combines machine learning and molecular mechanics to predict catalytic rates and selectivity with high accuracy.

AQuaRef uses machine learning to refine protein structures with quantum accuracy at lower computational cost, improving geometric quality and experimental data fit.

The paper evaluates computational hit-finding methods for targeting the WDR domain of LRRK2, a Parkinson's disease protein, finding that diverse strategies yielded weakly potent compounds.