Molecular determinants of avoidance and inhibition of Pseudomonas aeruginosa MexB efflux pump

: Transporters of the resistance-nodulation-cell division (RND) superfamily of proteins are the dominant multidrug efflux power of Gram-negative bacteria. The major RND efflux pump of Pseudomonas aeruginosa is MexAB-OprM, in which the inner membrane transporter MexB is responsible for the recognition and binding of compounds. The high importance of this pump in clinical antibiotic resistance made it a subject of intense investigations and a promising target for the discovery of efflux pump inhibitors. This study is focused on a series of peptidomimetic compounds developed as effective inhibitors of MexAB-OprM. We performed multi-copy molecular dynamics simulations, machine-learning (ML) analyses, and site-directed mutagenesis of MexB to investigate interactions of MexB with representatives of efflux avoiders, substrates, and inhibitors. The analysis of both direct and water-mediated protein-ligand interactions revealed characteristic patterns for each class, highlighting significant differences between them. We found that efflux avoiders poorly interact with the access binding site of MexB, and inhibition engages amino acid residues that are not directly involved in binding and transport of substrates. In agreement, machine-learning models selected different residues predictive of MexB substrates and inhibitors. The differences in interactions were further validated by site-directed mutagenesis. We conclude that the substrate translocation and inhibition pathways of MexB split at the interface (between the main putative binding sites) and at the deep binding pocket and that interactions outside of the hydrophobic patch contribute to the inhibition of MexB. This molecular-level information could help in the rational design of new inhibitors and antibiotics less susceptible to the efflux mechanism. IMPORTANCE Multidrug transporters recognize and expel from cells a broad range of ligands including their own inhibitors. The difference between the substrate translocation and inhibition routes remains unclear. In this study, machine learning and computational and experimental approaches were used to understand dynamics of MexB interactions with its ligands. Our results show that some ligands engage a certain combination of polar and charged residues in MexB binding sites to be effectively expelled into the exit funnel, whereas others engage aromatic and hydrophobic residues that slow down or hinder the next step in the transporter cycle. These findings suggest that all MexB ligands fit into this substrate-inhibitor spectrum depending on their physico-chemical structures and properties

First-generation structure-activity relationship studies of 2,3,4,9-tetrahydro-1H-carbazol-1-amines as CpxA phosphatase inhibitors

Genetic activation of the bacterial two-component signal transduction system, CpxRA, abolishes the virulence of a number of pathogens in human and murine infection models. Recently, 2,3,4,9-tetrahydro-1H-carbazol-1-amines were shown to activate the CpxRA system by inhibiting the phosphatase activity of CpxA. Herein we report the initial structure-activity relationships of this scaffold by focusing on three approaches 1) A-ring substitution, 2) B-ring deconstruction to provide N-arylated amino acid derivatives, and 3) C-ring elimination to give 2-ethylamino substituted indoles. These studies demonstrate that the A-ring is amenable to functionalization and provides a promising avenue for continued optimization of this chemotype. Further investigations revealed that the C-ring is not necessary for activity, although it likely provides conformational constraint that is beneficial to potency, and that the (R) stereochemistry is required at the primary amine. Simplification of the scaffold through deconstruction of the B-ring led to inactive compounds, highlighting the importance of the indole core. A new lead compound 26 was identified, which manifests a ∼30-fold improvement in CpxA phosphatase inhibition over the initial hit. Comparison of amino and des-amino derivatives in bacterial strains differing in membrane permeability and efflux capabilities demonstrate that the amine is required not only for target engagement but also for permeation and accumulation in Escherichia coli

Predictive rules of efflux inhibition and avoidance in Pseudomonas aeruginosa

Antibiotic-resistant bacteria rapidly spread in clinical and natural environments and challenge our modern lifestyle. A major component of defense against antibiotics in Gram-negative bacteria is a drug permeation barrier created by active efflux across the outer membrane. We identified molecular determinants defining the propensity of small peptidomimetic molecules to avoid and inhibit efflux pumps in Pseudomonas aeruginosa, a human pathogen notorious for its antibiotic resistance.Combining experimental and computational protocols, we mapped the fate of the compounds from structure-activity relationships through their dynamic behavior in solution, permeation across both the inner and outer membranes, and interaction with MexB, the major efflux transporter of P. aeruginosa. We identified predictors of efflux avoidance and inhibition and demonstrated their power by using a library of traditional antibiotics and compound series and by generating new inhibitors of MexB. The identified predictors will enable the discovery and optimization of anti-bacterial agents suitable for treatment of P. aeruginosa infections

A Selective Antibiotic for Lyme Disease

Lyme disease is on the rise. Caused by a spirochete Borreliella burgdorferi, it affects an estimated 500,000 people in the United States alone. The antibiotics currently used to treat Lyme disease are broad spectrum, damage the microbiome, and select for resistance in non-target bacteria. We therefore sought to identify a compound acting selectively against B. burgdorferi. A screen of soil micro-organisms revealed a compound highly selective against spirochetes, including B. burgdorferi. Unexpectedly, this compound was determined to be hygromycin A, a known antimicrobial produced by Streptomyces hygroscopicus. Hygromycin A targets the ribosomes and is taken up by B. burgdorferi, explaining its selectivity. Hygromycin A cleared the B. burgdorferi infection in mice, including animals that ingested the compound in a bait, and was less disruptive to the fecal microbiome than clinically relevant antibiotics. This selective antibiotic holds the promise of providing a better therapeutic for Lyme disease and eradicating it in the environment

Synergy between Active Efflux and Outer Membrane Diffusion Defines Rules of Antibiotic Permeation into Gram-Negative Bacteria

Gram-negative bacteria are notoriously resistant to antibiotics, but the extent of the resistance varies broadly between species. We report that in significant human pathogens Acinetobacter baumannii, Pseudomonas aeruginosa, and Burkholderia spp., the differences in antibiotic resistance are largely defined by their penetration into the cell. For all tested antibiotics, the intracellular penetration was determined by a synergistic relationship between active efflux and the permeability barrier. We found that the outer membrane (OM) and efflux pumps select compounds on the basis of distinct properties and together universally protect bacteria from structurally diverse antibiotics. On the basis of their interactions with the permeability barriers, antibiotics can be divided into four clusters that occupy defined physicochemical spaces. Our results suggest that rules of intracellular penetration are intrinsic to these clusters. The identified specificities in the permeability barriers should help in the designing of successful therapeutic strategies against antibiotic-resistant pathogens

Predicting permeation of compounds across the outer membrane of P. aeruginosa using molecular descriptors

Abstract The ability Gram-negative pathogens have at adapting and protecting themselves against antibiotics has increasingly become a public health threat. Data-driven models identifying molecular properties that correlate with outer membrane (OM) permeation and growth inhibition while avoiding efflux could guide the discovery of novel classes of antibiotics. Here we evaluate 174 molecular descriptors in 1260 antimicrobial compounds and study their correlations with antibacterial activity in Gram-negative Pseudomonas aeruginosa. The descriptors are derived from traditional approaches quantifying the compounds’ intrinsic physicochemical properties, together with, bacterium-specific from ensemble docking of compounds targeting specific MexB binding pockets, and all-atom molecular dynamics simulations in different subregions of the OM model. Using these descriptors and the measured inhibitory concentrations, we design a statistical protocol to identify predictors of OM permeation/inhibition. We find consistent rules across most of our data highlighting the role of the interaction between the compounds and the OM. An implementation of the rules uncovered in our study is shown, and it demonstrates the accuracy of our approach in a set of previously unseen compounds. Our analysis sheds new light on the key properties drug candidates need to effectively permeate/inhibit P. aeruginosa, and opens the gate to similar data-driven studies in other Gram-negative pathogens

Predicting permeation of compounds across the outer membrane of P. aeruginosa using molecular descriptors

The ability Gram-negative pathogens have at adapting and protecting themselves against antibiotics has increasingly become a public health threat. Data-driven models identifying molecular properties that correlate with outer membrane (OM) permeation and growth inhibition while avoiding efflux could guide the discovery of novel classes of antibiotics. Here we evaluate 174 molecular descriptors in 1260 antimicrobial compounds and study their correlations with antibacterial activity in Gram-negative Pseudomonas aeruginosa. The descriptors are derived from traditional approaches quantifying the compounds' intrinsic physicochemical properties, together with, bacterium-specific from ensemble docking of compounds targeting specific MexB binding pockets, and all-atom molecular dynamics simulations in different subregions of the OM model. Using these descriptors and the measured inhibitory concentrations, we design a statistical protocol to identify predictors of OM permeation/inhibition. We find consistent rules across most of our data highlighting the role of the interaction between the compounds and the OM. An implementation of the rules uncovered in our study is shown, and it demonstrates the accuracy of our approach in a set of previously unseen compounds. Our analysis sheds new light on the key properties drug candidates need to effectively permeate/inhibit P. aeruginosa, and opens the gate to similar data-driven studies in other Gram-negative pathogens