title: A data-driven approach to modeling the tripartite structure of multidrug resistance efflux pumps.
abstract: Many bacterial pathogens are becoming increasingly resistant to antibiotic treatments, and a detailed understanding of the molecular basis of antibiotic resistance is critical for the development of next-generation approaches for combating bacterial infections. Studies focusing on pathogens have revealed the profile of resistance in these organisms to be due primarily to the presence of multidrug resistance efflux pumps: tripartite protein complexes which span the periplasm bridging the inner and outer membranes of Gram-negative bacteria. An atomic-level resolution tripartite structure remains imperative to advancing our understanding of the molecular mechanisms of pump function using both theoretical and experimental approaches. We develop a fast and consistent method for constructing tripartite structures which leverages existing data-driven models and provide molecular modeling approaches for constructing tripartite structures of multidrug resistance efflux pumps. Our modeling studies reveal that conformational changes in the inner membrane component responsible for drug translocation have limited impact on the conformations of the other pump components, and that two distinct models derived from conflicting experimental data are both consistent with all currently available measurements. Additionally, we investigate putative drug translocation pathways via geometric simulations based on the available crystal structures of the inner membrane pump component, AcrB, bound to two drugs which occupy distinct binding sites: doxorubicin and linezolid. These simulations suggest that smaller drugs may enter the pump through a channel from the cytoplasmic leaflet of the inner membrane, while both smaller and larger drug molecules may enter through a vestibule accessible from the periplasm.
authors: Theoretical Biology and Biophysics Group (T-6), Los Alamos National Laboratory, Los Alamos, New Mexico, 87545; Department of Computer Science, Middle Tennessee State University, Murfreesboro, Tennessee, 37132.
authors: Joshua L
authors: JL
authors: Phillips
authors: S
authors: S
authors: Gnanakaran
mesh_terms: D000596:Amino Acids / Q000737:chemistry; D001426:Bacterial Proteins / Q000737:chemistry; D001692:Biological Transport; D016957:Burkholderia pseudomallei / Q000737:chemistry; D003198:Computer Simulation; D018432:Drug Resistance, Multiple; D026901:Membrane Transport Proteins / Q000737:chemistry*; D008958:Models, Molecular; D017711:Nonlinear Dynamics; D004364:Pharmaceutical Preparations / Q000737:chemistry / Q000378:metabolism; D025341:Principal Component Analysis; D017433:Protein Structure, Secondary; D040681:Structural Homology, Protein
chemical_list: D000596:Amino Acids; D001426:Bacterial Proteins; D026901:Membrane Transport Proteins; D004364:Pharmaceutical Preparations
keywords: AmrAB-OprA; Burkholderia pseudomallei; FRODAN; MexAB-OprM; drug resistance; drug translocation; efflux pump; geometrical simulations; membrane transporter; tripartite structures