Computational redox biology: Methods and applications

Abstract

Cysteine (Cys) is the most important amino acid in redox biology: it is the premier residue used by proteins to maintain redox homeostasis, sense redox changes in the environment, and counteract oxidative stress. Cys is often used as a catalytic redox-active residue and plays a key role in protein structure stabilization via disulfides and metal binding. Cys is much different from other common amino acids in proteins: its unique chemical and physical properties provide high affinity for metal ions, support formation of covalent bonds with other Cys, and confer response to changes in the environment. These features are largely responsible for the broad variety of its biological functions. Thus, a better understanding of basic properties of Cys is essential for understanding the fundamental roles Cys plays in redox biology, as well as for prediction and classification of functional Cys residues in proteins. In this chapter, we provide an overview of theoretical and computational tools that have been developed in the area of thiol regulation and redox biology. In particular, we introduce and discuss methods to investigate basic properties of Cys, such as exposure and pKa, and a variety of algorithms for functional prediction of different types of Cys in proteins.