Computational Design of Lysine Targeting Covalent Binders Using Rosetta.

Chemical probes that form a covalent bond with their target protein have been established as a powerful tool for investigating proteins and modulating their activity, but until recently were mostly targeting cysteine residues. Covalent binders that target lysine residues are increasingly reported. Covalent binding to lysine involves challenges such as the increased pK(a) of the side chain and its considerable flexibility. Here, we describe two computational methods to derivatize lysine-binding covalent small-molecules based on known noncovalent binders, approaching the design problem from two opposite directions. In a "ligand-side" approach, we scan different ligand positions to install an electrophile and dock these derivatized ligands into the target protein. In a "protein-side" approach, we install an electrophile on the target lysine and model its conformational space to find suitable installation vectors on the ligand. We applied both of these protocols retrospectively to a data set of electrophilic ligands and to a data set of vitamin B6 covalently bound to a receptor lysine residue. Our ligand-side protocol successfully identified the known covalent binder in 80% and 86% of cases, while the protein-side protocol achieved identification rates of 56% and 82%, respectively. We prospectively validated these protocols by designing and testing a new lysine-targeting MKK7 inhibitor. Mass-spectrometry and crystallography validated the covalent binding to the target lysine. Applying these protocols to a data set of known kinase inhibitors identified high-confidence covalent candidates for more than 200 human kinases, demonstrating the potential impact of our protocols.