In this project, we aim to combine structure-enabled machine learning and alchemical free energy calculations to develop a predictive quantitative model to rapidly assess kinase inhibitor affinity and selectivity, design ligands with desired selectivity profiles and assess the impact of clinical point mutations on inhibitor binding.
kinoml package provides a modern Python library to help build flexible pipelines for machine learning in the context of structural bioinformatics. More information on how to use install it and use it for your research can be found on the official documentation.
Software and resources
- John D. Chodera · MSKCC
- The Einstein Foundation & Stiftung Charité · BIH Einstein Visiting Fellowship