Markov-State Transition Path Analysis of ElectrostaticChanneling

摘要

Electrostatic channeling is a naturally occurring approach to control the flux of charged intermediates in catalytic cascades. Computational techniques have enabled quantitative understanding of such mechanisms, augmenting experimental approaches by modeling molecular interactions in atomic detail. In this work, we report the first utilization of a Markov-state model (MSM) to describe the surface diffusion of a reaction intermediate, glucose 6-phosphate, on an artificially modified cascade where hexokinase and glucose-6-phosphate dehydrogenase are covalently conjugated by a cationic oligopeptide bridge. Conformation space networks are used to represent intermediate transport on enzyme surfaces, along with committor probabilities that assess the desorption probability of the intermediate on each segment of the channeling pathway. For the region between the peptide bridge and downstream active site, the ionic strength dependence of desorption probability by MSM agreed well with that by transition state theory. A kinetic Monte Carlo model integrates parameters from different computationalmethods to evaluate the contribution of desorption during each step.The approach is validated by calculation of kinetic lag time, whichagrees well with experimental results. These results further demonstratethe applicability of molecular simulations and advanced sampling techniquesto the design of chemical networks.