New insights into the substrate specificity of cholesterol oxidases for more aware application.

Cholesterol oxidases (ChOxes) are enzymes that catalyze the oxidation of cholesterol to cholest-4-en-3-one. These enzymes find wide applications across various diagnostic and industrial settings. In addition, as a pathogenic factor of several bacteria, they have significant clinical implications. The current classification system for ChOxes is based on the type of bond connecting FAD to the apoenzyme, which does not adequately illustrate the enzymatic and structural characteristics of these proteins. In this study, we have adopted an integrative approach, combining evolutionary analysis, classic enzymatic techniques and computational approaches, to elucidate the distinct features of four various ChOxes from Rhodococcus sp. (RCO), Cromobacterium sp. (CCO), Pseudomonas aeruginosa (PCO) and Burkhoderia cepacia (BCO). Comparative and evolutionary analysis of substrate-binding domain (SBD) and FAD-binding domain (FBD) helped to reveal the origin of ChOxes. We discovered that all forms of ChOxes had a common ancestor and that the structural differences evolved later during divergence. Further examination of amino acid variations revealed SBD as a more variable compared to FBD independently of FAD coupling mechanism. Revealed differences in amino acid positions turned out to be critical in determining common for ChOxes properties and those that account for the individual differences in substrate specificity. A novel look with the help of chemical descriptors on found distinct features were sufficient to attempt an alternative classification system aimed at application approach. While univocal characteristics necessary to establish such a system remain elusive, we were able to demonstrate the substrate and protein features that explain the differences in substrate profile. [Display omitted] • Current classification of cholesterol oxidases is useless for enzymatic description. • All forms of ChOxes had a common ancestor with further divergence. • Chemical descriptors turned out to be a suitable for alternative classification. • Folding-based approach can better guide the selection of enzymes for practice. [ABSTRACT FROM AUTHOR]