Modelling covalent modification of cysteine residues in proteins

Abstract

Cysteine is a unique amino acid because of the chemical reactivity of its thiol (–SH) side chain. For that reason, cysteine serves several essential roles in biochemistry, and its reactivity is critical for the catalytic activity of several biological enzymes. This significance of cysteine residues has been exploited in designing covalent-modifier drugs, particularly kinase inhibitors, which have proven to be successful cancer chemotherapeutic agents in recent years. The reactivity of cysteine thiol group is complex, but a measure of its acidity or pKₐ is a strong determinant of its reactivity towards druggable targets—and can help guide the selection of appropriate druggable targets for covalent modification. Relatively few experimental pKₐ’s of cysteine residues in proteins have been reported, and methods for the computation of cysteine pKₐ’s have received little attention. This thesis presents studies undertaken to investigate the reactivity and covalent modification of cysteine residues in proteins. The introductory chapter lays the groundwork that becomes the basis for subsequent chapters in the thesis. This chapter provides a general introduction to covalent modification and the techniques used to investigate the biophysical properties of residue-specific nucleophilic targets for covalent modification. The first two chapters following the introduction are focused on predictive pKa assessments and validation studies on different computational methods in accurately calculating experimental cysteine pKₐ’s. In the latter chapters, advanced computational and multiscale methods are adopted to investigate the reactivity of druggable cysteines in protein kinases commonly implicated in diverse clinical indications, as well as model all the steps in the covalent modification mechanism of a kinase target. The thesis concludes by providing a concise summary of the research findings and future directions stemming from the work. The fundamental studies presented herein expand our current knowledge of modelling the covalent inhibition of druggable cysteines in enzyme targets and could go a long way to inform drug design and discovery.