Computational identification of functionally important residues in Cytochrome P450 RufO

Aromatic nitration is an important chemical transformation widely used in the production of pharmaceuticals, dyes, agrochemicals, and energetic materials. However, conventional chemical nitration methods typically require harsh reaction conditions and often lack regioselectivity. In contrast, certain cytochrome P450 enzymes can catalyse selective aromatic nitration under mild biological conditions. RufO is a nitrating cytochrome P450 enzyme involved in the biosynthesis of the antibiotic rufomycin, where it catalyses nitration of a tyrosine residue within a precursor peptide. Despite its unique catalytic activity, the structural determinants governing substrate recognition and active-site organization in RufO remain poorly understood. In this study, we used computational structural analysis to identify residues that contribute to the functional architecture of RufO. We identified residues F69, T85, and M172 as important contributors to the local structural framework surrounding the catalytic pocket. Mutational analysis suggests that these residues primarily influence hydrogen-bonding networks, hydrophobic packing, and steric organisation rather than directly participating in catalysis. These findings also provide a foundation for future experimental studies aimed at understanding and engineering nitrating cytochrome P450 enzymes for selective nitroaromatic synthesis.