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 antibacterial agents suitable for treatment of P. aeruginosa infections. IMPORTANCE Efflux pump avoidance and inhibition are desired properties for the optimization of antibacterial activities against Gram-negative bacteria. However, molecular and physicochemical interactions defining the interface between compounds and efflux pumps remain poorly understood. We identified properties that correlate with efflux avoidance and inhibition, are predictive of similar features in structurally diverse compounds, and allow researchers to distinguish between efflux substrates, inhibitors, and avoiders in P. aeruginosa. The developed predictive models are based on the descriptors representative of different clusters comprising a physically intuitive combination of properties. Molecular shape (represented by acylindricity), amphiphilicity (anisotropic polarizability), aromaticity (number of aromatic rings), and the partition coefficient (LogD) are physicochemical predictors of efflux inhibitors, whereas interactions with Pro668 and Leu674 residues of MexB distinguish between inhibitors/substrates and efflux avoiders. The predictive models and efflux rules are applicable to compounds with unrelated chemical scaffolds and pave the way for development of compounds with the desired efflux interface properties.

With the spreading of antibiotic resistance, the translocation of antibiotics through bacterial envelopes is crucial for their antibacterial activity. In Gram-negative bacteria, the interplay between membrane permeability and drug efflux pumps must be investigated as a whole. Here, we quantified the intracellular accumulation of a series of fluoroquinolones in population and in individual cells of Escherichia coli according to the expression of the AcrB efflux transporter. Computational results supported the accumulation levels measured experimentally and highlighted how fluoroquinolones side chains interact with specific residues of the distal pocket of the AcrB tight monomer during recognition and binding steps.

The putative mechanism by which bacterial RND-type multidrug efflux pumps recognize and transport their substrates is a complex and fascinating enigma of structural biology. How a single protein can recognize a huge number of unrelated compounds and transport them through one or just a few mechanisms is an amazing feature not yet completely unveiled. The appearance of cooperativity further complicates the understanding of structure-dynamics-activity relationships in these complex machineries. Experimental techniques may have limited access to the molecular determinants and to the energetics of key processes regulating the activity of these pumps. Computer simulations are a complementary approach that can help unveil these features and inspire new experiments. Here we review recent computational studies that addressed the various molecular processes regulating the activity of RND efflux pumps.

The drug/proton antiporter AcrB, part of the major efflux pump AcrABZ-TolC in Escherichia coli, is characterized by its impressive ability to transport chemically diverse compounds, conferring a multidrug resistance phenotype. However, the molecular features differentiating between good and poor substrates of the pump have yet to be identified. In this work, we combined molecular docking with molecular dynamics simulations to study the interactions between AcrB and two representative cephalosporins, cefepime and ceftazidime (a good and poor substrate of AcrB, respectively). Our analysis revealed different binding preferences of the two compounds toward the subsites of the large deep binding pocket of AcrB. Cefepime, although less hydrophobic than ceftazidime, showed a higher affinity than ceftazidime for the so-called hydrophobic trap, a region known for binding inhibitors and substrates. This supports the hypothesis that surface complementarity between the molecule and AcrB, more than the intrinsic hydrophobicity of the antibiotic, is a feature required for the interaction within this region. Oppositely, the preference of ceftazidime for binding outside the hydrophobic trap might not be optimal for triggering allosteric conformational changes needed to the transporter to accomplish its function. Altogether, our findings could provide valuable information for the design of new antibiotics less susceptible to the efflux mechanism.

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Nucleic acids are highly charged biopolymers whose secondary structure is strongly dependent on electrostatic interactions. Solvent molecules and ions are also believed to play an important role in mediating and directing both sequence recognition and interactions with other molecules, such as proteins and a variety of ligands. Therefore, to fully understand the biological functions of DNA, it is necessary to understand the interactions with the surrounding counterions. It is well known that monovalent counterions can bind to the minor groove of DNA with consecutive sequences of four, or more, adenine and thymine (A-tracts) with relatively long residence times. However, much less is known about their binding to the backbone and to the major groove. In this work, we used molecular dynamics simulations to both investigate the interactions between the backbone and major groove of DNA and one of its physiological counterions (Na+) and evaluate the relationship between these interactions and the nucleotide sequence. Three dodecamers, namely CGAAAATTTTCG, CGCTCTAGAGCG, and CGCGAATTCGCG, were simulated using the Toukan–Rahman flexible SPC water model and Smith and Dang parameters for Na+, revealing a significant sequence dependence on the ion binding to both backbone and major groove. In the absence of experimental data on the atomistic details of the studied interactions, the reliability of the results was evaluated performing the simulations with additional sets of potential parameters for ions and solvent, namely the Ȧqvist or the Joung and Cheatham ion parameters and the TIP3P water model. This allowed us to evaluate the results by verifying which features are preserved independently from the parameters adopted.

Protein plasticity, while often linked to biological function, also provides opportunities for rational design of selective and potent inhibitors of their function. The application of computational methods to the prediction of concealed protein concavities is challenging, as the motions involved can be significant and occur over long time scales. Here we introduce the swarm-enhanced sampling molecular dynamics (sesMD) method as a tool to improve sampling of conformational landscapes. In this approach, a swarm of replica simulations interact cooperatively via a set of pairwise potentials incorporating attractive and repulsive components. We apply the sesMD approach to explore the conformations of the DFG motif in the protein p38α mitogen-activated protein kinase. In contrast to multiple MD simulations, sesMD trajectories sample a range of DFG conformations, some of which map onto existing crystal structures. Simulated structures intermediate between the DFG-in and DFG-out conformations are predicted to have druggable pockets of interest for structure-based ligand design.

Polymorphisms in the region of the calmodulin-dependent kinase isoform D (CaMK1D) gene are associated with increased incidence of diabetes, with the most common polymorphism resulting in increased recognition by transcription factors and increased protein expression. While reducing CaMK1D expression has a potentially beneficial effect on glucose processing in human hepatocytes, there are no known selective inhibitors of CaMK1 kinases that can be used to validate or translate these findings. Here we describe the development of a series of potent, selective, and drug-like CaMK1 inhibitors that are able to provide significant free target cover in mouse models and are therefore useful as in vivo tool compounds. Our results show that a lead compound from this series improves insulin sensitivity and glucose control in the diet-induced obesity mouse model after both acute and chronic administration, providing the first in vivo validation of CaMK1D as a target for diabetes therapeutics.