Towards predicting the effects of protein mutations on binding kinetics

Giulia D’Arrigo, Rebecca C. Wade

Binding kinetics are major determinants of in vivo protein function and are affected by mutations leading to phenomena such as drug resistance, antibody maturation or altered enzyme substrate specificity. However, the prediction of association and dissociation rates poses many challenges for computational methods, in particular due to the gap – often of many orders of magnitude – between the times accessible to conventional molecular dynamics simulations and the protein binding kinetics. I will discuss insights from recent applications of molecular docking and molecular dynamics simulations to engineer altered enzyme substrate preference (1) and to investigate how drug resistance mutations affect drug binding and transport by a malaria drug transporter (2). I will then describe the development and validation of the τ-Random Acceleration Molecular Dynamics (τRAMD) approach (3,4) for computational screening of protein mutants for their effects on the dissociation rates of protein-protein and protein-peptide complexes.

References:

(1) Rahman MT et al. An engineered variant of MECR reductase reveals indispensability of long-chain acyl-ACPs for mitochondrial respiration. Nature Commun. 2023, 14, 619.
(2) Gomez GM, et al. PfCRT mutations conferring piperaquine resistance in falciparum malaria shape the kinetics of quinoline drug binding and transport. PLoS Pathog. 2023, 19(6):e1011436.
(3) Kokh DB, et al. Estimation of drug-target residence times by τ-random acceleration molecular dynamics simulations. J. Chem. Theory Comput. 2018, 14: 3859–3869.
(4) Kokh DB, et al. A workflow for exploring ligand dissociation from a macromolecule: Efficient random acceleration molecular dynamics simulation and interaction fingerprint analysis of ligand trajectories. J. Chem. Phys. 2020, 153: 125102.