Payal Chatterjee, Wesley M. Botello-Smith, Han Zhang, Li Qian, Abdelaziz Alsamarah, David Kent, Jerome J. Lacroix, Michel Baudry, and Yun Luo
J. Am. Chem. Soc., 2017
doi: 10.1021/jacs.7b08938
Reversible covalent inhibitors have many clinical advantages over noncovalent or covalent drugs. However, apart from selecting a warhead, substantial efforts in design and synthesis are needed to optimize noncovalent interactions to improve target-selective binding. Computational prediction of binding affinity for reversible covalent inhibitors presents a unique challenge since the binding process consists of multiple steps, which are not necessarily independent of each other. In this study, we lay out the relation between relative binding free energy and the overall reversible covalent binding affinity using a two-state binding model. To prove the concept, we employed free energy perturbation (FEP) coupled with λ-exchange molecular dynamics method to calculate the binding free energy of a series of α-ketoamide analogs relative to a common warhead scaffold, in both noncovalent and covalent bond states, and for two highly homologous proteases, calpain-1 and calpain-2. We conclude that covalent binding affinity alone, in general, can be used to predict reversible covalent binding selectivity. However, exceptions may exist. Therefore, we also discuss the conditions under which the noncovalent binding step is no longer negligible and propose a novel approach that combines the relative FEP calculations with a single QM/MM calculation of warhead to predict the binding affinity and binding kinetics for a large number of reversible covalent inhibitors. Our FEP calculations also revealed that covalent and noncovalent states of an inhibitor do not necessarily exhibit the same selectivity. Thus, investigating both binding states, as well as the kinetics will provide extremely useful information for optimizing reversible covalent inhibitors.
A blog highlighting recent publications in the area of covalent modification of proteins, particularly relating to covalent-modifier drugs. @CovalentMod on Twitter, @covalentmod@mstdn.science on Mastodon, and @covalentmod.bsky.social on BlueSky
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