Configuration Flipping in Distal Pocket of Multidrug Transporter MexB Impacts the Efflux Inhibitory Mechanism

Machine Learning-Guided Discovery of AcrB and MexB Efflux Pump Inhibitors

Multidrug efflux pump is one of the reasons behind the antimicrobial inactivity related to infection caused by Gram-negative pathogens. The inner membrane resistance-nodulation-cell division transporter proteins, AcrB and MexB, in association with outer membrane proteins, TolC and OprM, are responsible for the extrusion of a broad range of substrates, followed by recognizing them. Although various inhibitors were proposed to stop the efflux activity of the transporter protein, none of them had been approved clinically. Our study aims to identify potent inhibitor-like molecules employing supervised classification models trained upon the molecular descriptors of previously known inhibitors. Based on the intrinsic minimum inhibitory concentration (MIC) values of the reported inhibitors, they were classified into highly potent and less potent categories. A total of 10 different classification models were built using various molecular descriptors; among them, support vector machine, Random Forest, AdaBoost, and LightGBM models appeared to deliver promising results with >80% accuracy. These top four models were implemented on a library of 5043 to obtain 8 hit molecules after the multistep filtering process. To assess their activity toward AcrB and MexB, several molecular dynamics simulations of their ligand-bound structures were performed. We also calculated the binding free-energy values and analyzed other structural properties. Mol.3488 of the unknown molecules showed higher binding affinities for both AcrB and MexB. Also, the presence of "pyridopyrimidone" and "benzothiazole" moieties in the molecules and "V"-shaped orientation of ligands inside the deep binding pocket increase the binding affinity, thereby higher inhibitory properties.

Uncovering the Structural and Binding Insights of Dual Inhibitors Simultaneously Targeting Two Distinct Sites on EGFR Kinase

Epidermal growth factor receptor (EGFR) is the first growth factor receptor identified in normal cells that is related to the receptor tyrosine kinase, which causes regular cell division. A point mutation in EGFR intracellular kinase domain forces the abnormal cell divisions throughout time, leading to non-small cell lung cancer (NSCLC) transformation. Thus, competitive inhibitors that bind to the ATP binding pocket have been developed as a targeted therapy for NSCLC. The third-generation kinase inhibitor Osimertinib is currently playing a very vital role in the treatment of NSCLC. However, it is not effective toward the C797S kinase domain mutation. For this reason, fourth-generation kinase noncompetitive inhibitors are introduced which work through binding to an allosteric pocket near the ATP binding region and act as a better binding agent for this mutated kinase domain. However, the problem is that these single fourth-generation kinase inhibitors may not be as effective as a single agent. The aim of this work was to apply combinations of these two inhibitors together in different binding regions of EGFR without overlapping the resistance mechanism to obtain the key direct and indirect interactions occurring between them. Moreover, the free energy of dissociation of an inhibitor from its binding sites in the presence of a second inhibitor immobilized in another binding site was also the focus of the study. To realize this aim, we performed conventional molecular dynamics simulations and principal component analysis and dynamic cross-correlation matrices along with umbrella sampling. Our results demonstrated that binding of dual inhibitors triggered conformational changes of the protein more toward the inactive state. Furthermore, allosteric inhibitors bound more strongly to protein kinase EGFR than the orthosteric inhibitors in the presence of dual inhibitors. Finally, the binding mechanism and important hydrogen-bonding residues during unbinding of the inhibitors were fully elucidated. This study provides insight into the binding of the receptor-orthosteric inhibitor-allosteric inhibitor, which can be helpful for further design of novel inhibitors that have a better inhibitory action.

A growing battlefield in the war against biofilm-induced antimicrobial resistance: insights from reviews on antibiotic resistance

Biofilms are a common survival strategy employed by bacteria in healthcare settings, which enhances their resistance to antimicrobial and biocidal agents making infections difficult to treat. Mechanisms of biofilm-induced antimicrobial resistance involve reduced penetration of antimicrobial agents, increased expression of efflux pumps, altered microbial physiology, and genetic changes in the bacterial population. Factors contributing to the formation of biofilms include nutrient availability, temperature, pH, surface properties, and microbial interactions. Biofilm-associated infections can have serious consequences for patient outcomes, and standard antimicrobial therapies are often ineffective against biofilm-associated bacteria, making diagnosis and treatment challenging. Novel strategies, including antibiotics combination therapies (such as daptomycin and vancomycin, colistin and azithromycin), biofilm-targeted agents (such as small molecules (LP3134, LP3145, LP4010, LP1062) target c-di-GMP), and immunomodulatory therapies (such as the anti-PcrV IgY antibodies which target Type IIIsecretion system), are being developed to combat biofilm-induced antimicrobial resistance. A multifaceted approach to diagnosis, treatment, and prevention is necessary to address this emerging problem in healthcare settings.

Identification of efflux pump inhibitors for Pseudomonas aeruginosa MexAB-OprM via ligand-based pharmacophores, 2D-QSAR, molecular docking, and molecular dynamics approaches

Efflux pumps have been reported as one of the significant mechanisms by which bacteria evade the effects of multiple antibiotics. The tripartite efflux pump MexAB-OprM in Pseudomonas aeruginosa is one of the most significant multidrug efflux systems due to its broad resistance to antibiotics such as chloramphenicol, fluoroquinolones, lipophilic β-lactam antibiotics, nalidixic acid, novobiocin, rifampicin, and tetracycline. A promising strategy to overcome this resistance mechanism is to combine antibiotics with efflux pump inhibitors (EPIs), which can increase their intracellular concentration to enhance their biological activities. Based on 143 EPIs with chemically diverse skeletons, the 3D pharmacophore and 2D-QSAR modelings were developed and used for the virtual screening on 9.2 million compounds including ZINC15, DrugBank, and Traditional Chinese Medicine databases to identify new EPIs. The molecular docking was also performed to evaluate the binding affinity of potential EPIs to the distal-binding pocket of MexB and resulted in 611 potential EPIs. The structure-activity relationship analyses suggested that nitrogen heterocyclic compounds, piperazine and pyridine scaffolds, and amide derivatives are the most favorable chemically features for MexAB inhibitory activities. The results from molecular dynamics analysis in 100 ns indicated that ZINC009296881 and ZINC009200074 were the most potential MexB inhibitors with strong binding affinity to the distal pocket and MM/GBSA ∆Gbind values of - 38.97 and - 30.19 kcal mol-1, respectively. The predicted pharmacokinetic properties and toxicity of these compounds indicated their potential oral drugs. Multistep virtual screening of EPIs for MexAB-OprM, efflux pump multidrug resistant of P. aeruginosa.

The Art of War with Pseudomonas aeruginosa: Targeting Mex Efflux Pumps Directly to Strategically Enhance Antipseudomonal Drug Efficacy

Pseudomonas aeruginosa (P. aeruginosa) poses a grave clinical challenge due to its multidrug resistance (MDR) phenotype, leading to severe and life-threatening infections. This bacterium exhibits both intrinsic resistance to various antipseudomonal agents and acquired resistance against nearly all available antibiotics, contributing to its MDR phenotype. Multiple mechanisms, including enzyme production, loss of outer membrane proteins, target mutations, and multidrug efflux systems, contribute to its antimicrobial resistance. The clinical importance of addressing MDR in P. aeruginosa is paramount, and one pivotal determinant is the resistance-nodulation-division (RND) family of drug/proton antiporters, notably the Mex efflux pumps. These pumps function as crucial defenders, reinforcing the emergence of extensively drug-resistant (XDR) and pandrug-resistant (PDR) strains, which underscores the urgency of the situation. Overcoming this challenge necessitates the exploration and development of potent efflux pump inhibitors (EPIs) to restore the efficacy of existing antipseudomonal drugs. By effectively countering or bypassing efflux activities, EPIs hold tremendous potential for restoring the antibacterial activity against P. aeruginosa and other Gram-negative pathogens. This review focuses on concurrent MDR, highlighting the clinical significance of efflux pumps, particularly the Mex efflux pumps, in driving MDR. It explores promising EPIs and delves into the structural characteristics of the MexB subunit and its substrate binding sites.

Ramaswamy V, Vargiu AV, Malloci G, Bosin A, Ruggerone P. Common recognition topology of mex transporters of Pseudomonas aeruginosa revealed by molecular modelling

The secondary transporters of the resistance-nodulation-cell division (RND) superfamily mediate multidrug resistance in Gram-negative bacteria like Pseudomonas aeruginosa. Among these RND transporters, MexB, MexF, and MexY, with partly overlapping specificities, have been implicated in pathogenicity. Only the structure of the former has been resolved experimentally, which together with the lack of data about the functional dynamics of the full set of transporters, limited a systematic investigation of the molecular determinants defining their peculiar and shared features. In a previous work (Ramaswamy et al., Front. Microbiol., 2018, 9, 1144), we compared at an atomistic level the two main putative recognition sites (named access and deep binding pockets) of MexB and MexY. In this work, we expand the comparison by performing extended molecular dynamics (MD) simulations of these transporters and the pathologically relevant transporter MexF. We employed a more realistic model of the inner phospholipid membrane of P. aeruginosa and more accurate force-fields. To elucidate structure/dynamics-activity relationships we performed physico-chemical analyses and mapped the binding propensities of several organic probes on all transporters. Our data revealed the presence, also in MexF, of a few multifunctional sites at locations equivalent to the access and deep binding pockets detected in MexB. Furthermore, we report for the first time about the multidrug binding abilities of two out of five gates of the channels deputed to peripheral (early) recognition of substrates. Overall, our findings help to define a common “recognition topology” characterizing Mex transporters, which can be exploited to optimize transport and inhibition propensities of antimicrobial compounds.

Recognition of quinolone antibiotics by the multidrug efflux transporter MexB of Pseudomonas aeruginosa

The drug/proton antiporter MexB is the engine of the major efflux pump MexAB-OprM in Pseudomonas aeruginosa. This protein is known to transport a large variety of compounds, including antibiotics, thus conferring a multi-drug resistance phenotype. Due to the difficulty of producing co-crystals, only two X-ray structures of MexB in a complex with ligands are available to date, and mechanistic aspects are largely hypothesized based on the body of data collected for the homologous protein AcrB of Escherichia coli. In particular, a recent study (Ornik-Cha, Wilhelm, Kobylka et al., Nat. Commun., 2021, 12, 6919) reported a co-crystal structure of AcrB in a complex with levofloxacin, an antibiotic belonging to the important class of (fluoro)-quinolones. In this work, we performed a systematic ensemble docking campaign coupled to the cluster analysis and molecular-mechanics optimization of docking poses to study the interaction between 36 quinolone antibiotics and MexB. We additionally investigated surface complementarity between each molecule and the transporter and thoroughly assessed the computational protocol adopted against the known experimental data. Our study reveals different binding preferences of the investigated compounds towards the sub-sites of the large deep binding pocket of MexB, supporting the hypothesis that MexB substrates oscillate between different binding modes with similar affinity. Interestingly, small changes in the molecular structure translate into significant differences in MexB–quinolone interactions. All the predicted binding modes are available for download and visualization at the following link: https://www.dsf.unica.it/dock/mexb/quinolones.

Putative binding modes (BMs) of quinolones to the bacterial efflux transporter MexB were identified. Multiple interaction patterns are possible, supporting the hypothesis that substrates oscillate between different BMs with similar affinity.

Prediction of COMT Inhibitors Using Machine Learning and Molecular Dynamics Methods

Catechol O-methyltransferase (COMT) plays a vital role in deactivating neurotransmitters like dopamine, norepinephrine, etc., by methylating those compounds. However, the deactivation of an excess amount of neurotransmitters leads to serious mental ailments such as Parkinson's disease. Molecules that bind inside the enzyme's active site inhibit this methylation mechanism by methylating themselves, termed COMT inhibitors. Our study is focused on designing these inhibitors by various machine learning methods. First, we have developed a classification model with experimentally available COMT inhibitors, which helped us generate a new data set of small inhibitor-like molecules. Then, to predict the activity of the new molecules, we have applied regression techniques such as Random Forest, AdaBoost, gradient boosting, and support vector machines. Each of the regression models yielded an R² value > 70% for both training and test data sets. Finally, to validate our models, 200 ns long molecular dynamics (MD) simulations of the two known inhibitors with known IC₅₀ values and the resultant inhibitors were performed inside the binding pockets to check their stability within. The free energy barrier of the methyl transfer from S-adenosyl-l-methionine (SAM) to each inhibitor was determined by combining steered molecular dynamics (SMD) and umbrella sampling using the quantum mechanics/molecular mechanics (QM/MM) method.