Prospective evaluation of structure-based simulations reveal their ability to predict the impact of kinase mutations on inhibitor binding

Sukrit Singh, Vytautas Gapsys, Matteo Aldeghi, David Schaller, Aziz M Rangwala, Jessica B White, Joseph P Bluck, Jenke Scheen, William G Glass, Jiaye Guo, Sikander Hayat, Bert L de Groot, Andrea Volkamer, Clara D Christ, Markus A Seeliger, John D Chodera.
[bioRxiv]

We show that alchemical free energy calculations have the potential to prospectively predict the impact of clinical kinase mutations on targeted kinase inhibitor binding.

Lessons learned during the journey of data: from experiment to model for predicting kinase affinity, selectivity, polypharmacology, and resistance

Raquel López-Ríos de Castro, Jaime Rodríguez-Guerra, David Schaller, Talia B Kimber, Corey Taylor, Jessica B White, Michael Backenköhler, Alexander Payne, Ben Kaminow, Iván Pulido, Sukrit Singh, Paula Linh Kramer, Guillermo Pérez-Hernández, Andrea Volkamer, John D Chodera
[bioRxiv]

This best practices paper describes considerations relevant to the use of experimental datasets in structure-based machine learning, using kinase:small molecule interactions as a model system.