Abstract 4638: Predictive computational approaches to guide the covalent targeting of cysteine residues in drug discovery

Abstract

Abstract Targeted covalent inhibition is an established approach for increasing the potency and selectivity of potential drug candidates, and has also been used to identify tool compounds for target validation studies. It is evident that binding to reversible recognition elements within the pocket is essential for selective covalent inhibition, but this must also be achieved with the appropriate level of inherent reactivity of the covalent functionality and compatible geometry and reactivity of the target amino acid. We have assessed the ability of several experimental and computational approaches to predict the intrinsic reactivity of a range of cysteine targeting warheads, some of which can be used in prospective compound design. In addition, molecular dynamics (MD) simulations in combination with pKa prediction methods have been used to investigate the accessibility and potential reactivity of target cysteines towards covalent inhibition. As part of this work a number of case studies will be reported including retrospective examples from covalent drug discovery efforts along with prospective use towards novel targets. Finally, a dataset of osimertinib analogues along with other EGFR inhibitors of varying reactivity will be discussed to enable further insight into the impact of reversible and covalent interactions on inhibitor binding. Citation Format: Richard A. Ward, Richard Lonsdale. Predictive computational approaches to guide the covalent targeting of cysteine residues in drug discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4638.