Monte Carlo Pathway Search (MCPS) for Exploring Permeation Pathways in High-Dimensional Conformational Space

Abstract

Antibiotic resistance of Gram-negative bacteria is largely attributed to the low permeability of their outer membrane (OM). Antibiotics crossing the OM typically do so through OM porins; therefore, understanding mechanisms facilitating this permeation would aid in antibiotic development. Molecular dynamics (MD) simulations provide key structural information on relevant molecular processes; however, simulating OM porin permeation is challenging, because antibiotic permeation occurs on timescales not feasibly attained with equilibrium MD due to hindrance by a constriction region (CR) within these porins. The CR also hinders antibiotic reorientation meaning translation and rotation are slow degrees of freedom requiring extensive simulation or expensive enhanced sampling techniques to satisfactorily sample. To overcome these challenges, we developed MCPS to efficiently sample high-dimensional permeation pathways through OM porins from the extracellular to periplasmic side. First, a multidimensional energy landscape is created by placing the antibiotic in all possible poses within translational and rotational space and evaluating antibiotic-protein interaction energy for each pose. Then, Monte Carlo (MC) moves are used to walk through this landscape to determine favorable trajectories connecting extracellular and periplasmic spaces. Since rotation and translation are slow degrees of freedom, limited changes in antibiotic orientation and position are allowed in each MC move. After obtaining multiple trajectories to comprehensively sample the possible pathways, most likely permeation pathways are identified using Dijkstra's algorithm. MCPS was used to study permeation of ampicillin through OmpF, an abundant E. Coli porin. We found ampicillin adopts a similar orientation as in the ampicillin-bound OmpF crystal structure at the CR entrance before diverging into two pathways with differing orientations and protein interactions. This application demonstrates MCPS effectiveness to obtain descriptive structural information for antibiotic permeation using few computational resources, indicating its potential for screening multiple antibiotics.