Reconciling conformational heterogeneity and Substrate Recognition in Cytochrome P450

The mechanistic basis of substrate-recognition by archtypal metalloenzyme cytochrome P450cam lacks clarity due to reports of contrasting crystallographic poses in its substrate-free form. Here we employ atomic resolution computer simulation to quantitatively dissect the conformational diversities of cytochrome P450cam and reconcile them with its substrate-binding mechanism. By initiating unbiased molecular dynamics simulation trajectories from multiple crystal structures of substrate-free P450cam, we first explore the statistical probabilities of each crystallographic pose of making dynamically transition to the other crystallographic pose and vice versa. Our approach allows us to build a comprehensive conformational ensemble of substrate-free P450cam using an aggregated 54 μs simulation trajectories. A Markov state model constructed using the conformational ensemble identifies multiple key macrostates in a broad and heterogenous free energy landscape and in particular, reveals a dynamic equilibrium between a pair of conformations in which the substrate-recognition sites are closed and open respectively. However, the prediction of a significantly high population of closed conformation, coupled with higher flux and faster rate from open → closed transition than its reverse process, dictates that the net conformational equilibrium would be swayed in favour of closed conformation. The investigation infers that, while a potential substrate of P450cam would in principle sample the diverse array of conformations of substrate-free protein, it would mostly encounter a closed conformation and hence would follow an induced-fit based recognition process. Taken together, this work establishes how a quantitative elucidation of conformational heterogeneity in protein would provide crucial insights in the mechanism of potential substrate-recognition process.