Computational approaches in efflux pump inhibitors: current status and prospects

Highlights

• Resistance in gram-negative bacteria predominantly by RND efflux pumps.

• Pivotal role of periplasmic cleft and domain in the recognition of substrates.

• Interaction studies of efflux pump inhibitors by Molecular Dynamics simulation.

• Structure complementarity and hydrophobicity are the key feature in design aspects.

• Phe residues play predominant role in the extrusion of substrates by efflux pumps.

Treatment of bacterial infections is currently threatened by the development of antibiotic resistance and a poor pipeline of new antibiotics. Efflux pumps (EPs) are an integral part of the defense machinery of bacteria, preventing the entry of molecules, such as antibiotics, into the intracellular environment and resulting in antibiotic resistance. Therefore, research has focused on the discovery of novel EP inhibitors (EPIs), such as PAβN, D13-9001, and MBX2319. however, there are still no US Food and Drug Administration (FDA)-approved drugs targeting EPs because of the inadequate assimilation of the inhibitors. Here, we discuss the use of computational approaches for molecular mechanistic studies of EPIs to help direct future research.

Introduction

Antibiotic resistance has become a major global threat and bacteria continue to evolve mechanisms of resistance. Extrusion of drugs from the bacterial intracellular environment through multidrug EPs has a pivotal role in this resistance 1, 2, 3, 4. EPs are an integral part of the defense machinery of bacteria, and their expression on the bacterial cell wall regulates the internal concentration of antibiotics. Therefore, targeting EPs could boost the efficacy of antibiotics 1, 2.

EPs are classified based on the sources of energy used (Fig. 1) [5]: the major facilitator superfamily (MFS), staphylococcal multiresistance superfamily (SMR), and resistance nodulation cell-division superfamily (RND) utilize proton motive force for EP mechanism, whereas, the ATP binding cassette (ABC) and multidrug and toxic compound extrusion (MATE) superfamilies utilize ATP, and sodium and proton motive forces, respectively as energy sources. In 2015, another novel multidrug EP (Acinetobacter chlorhexidine efflux; AceI) from Acinetobacter baumannii was identified by Hassan et al. This novel family of multidrug EPs was designated the ‘Proteobacterial antimicrobial compound efflux’ (PACE) superfamily because they are common in Proteobacteria 6, 7, 8.

Which superfamily of EPs should be targeted to combat antibiotic resistance? The answer lies in the priority list of pathogens classified by the WHO. Pathogens are categorized into three priority tiers based on their drug resistance (Fig. 2). Gram-negative bacteria are most important because they lead to infections that are untreatable with most available antibiotics and a few are pan-resistant [9]. Therefore, targeting the RND superfamily EPs (expressed commonly in Gram-negative bacteria) using EPIs (adjuvants) will be pivotal to rejuvenate the potency of antibiotics against resistant Gram-negative pathogens. RND EPs recognize and translocate a huge number of substrates via their functional unit, which is a tripartite EP comprising outer membrane factors (OMF), a membrane fusion protein (MFP), and an inner membrane protein (IMP). How the RND EP extrudes structurally diverse compounds remains unclear 10, 11. Although experimental data and structural features of these proteins have enabled researchers to understand the complexity of the proteins, less is known of the energetics and molecular determinants of the processes governing EP activity [12].

Computational studies are approaches that can be combined with experimental data to determine the pathway responsible for antibiotic resistance. In this review, we discuss the structural features and mechanistic aspects of RND EPs that have been probed using computational approaches. We highlight the outcomes of computational studies on the AdeABC pump of Acinetobacter baumannii [13], the AcrAB-TolC pump of Enterobacteriaceae [14], and the MexAB-OprM and MexXY-OprM pumps of Pseudomonas aeruginosa [15]. We also focus on computational aspects that have been used for the design of EPIs against these EPs.