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Determination of protein-protein binding affinity values is key to understanding various underlying biological phenomena, such as how missense variations change protein-protein binding. Most existing non-rigorous (fast) and rigorous (slow) methods that rely on all-atom representation of the proteins force the user to choose between speed and accuracy. In an attempt to achieve balance between speed and accuracy, we have combined rigorous umbrella sampling molecular dynamics simulation with a coarse-grained protein model. We predicted the effect of missense variations on binding affinity by selecting three protein-protein systems and comparing results to empirical relative binding affinity values and to non-rigorous modeling approaches. We obtained significant improvement both in our ability to discern stabilizing from destabilizing missense variations and in the correlation between predicted and experimental values compared to non-rigorous approaches. Overall our results suggest that using a rigorous affinity calculation method with coarse-grained protein models could offer fast and reliable predictions of protein-protein binding free energies.

Fast Calculation of Protein–Protein Binding Free Energies Using Umbrella Sampling with a Coarse-Grained Model