Unlocking Scalable Ligand Residence Time Predictions with Koffee Unbinding Kinetics Simulations

A great number of drug discovery programs fail due to poor in vivo efficacy and toxicity liabilities. On- and off-target ligand residence times can act as important drivers of these problems. While modern experimental techniques have made measuring compound kinetics data more routine, there is a lack of accurate, high-throughput simulation techniques to guide compound prioritization by residence time. In this work, we introduce KoffeeUnbinding Kinetics as a solution to the hitherto unanswered problem of scalable ligand-protein residence time scoring by molecular simulation. By bypassing conventional approaches based on molecular dynamics simulations, Koffee Unbinding Kinetics simulates ligand-protein unbinding at the atomistic level in ≈1 GPU minute per complex using inexpensive hardware, a speed-up of at least 3-5 orders of magnitude compared to current state-of-the-art simulation approaches. Koffee Unbinding Kinetics can enhance compound selection to mitigate costly future program failures by adding fast, predictive residence time scoring simulations to early stage computational drug discovery pipelines.