Tripartite efflux pumps of the RND superfamily: what did we learn from computational studies?

Bacterial resistance to antibiotics has been long recognized as a priority to address for human health. Among all micro-organisms, the so-called multi-drug resistant (MDR) bacteria, which are resistant to most, if not all drugs in our current arsenal, are particularly worrisome. The World Health Organization has prioritized the ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacter species) pathogens, which include four Gram-negative bacterial species. In these bacteria, active extrusion of antimicrobial compounds out of the cell by means of 'molecular guns' known as efflux pumps is a main determinant of MDR phenotypes. The resistance-nodulation-cell division (RND) superfamily of efflux pumps connecting the inner and outer membrane in Gram-negative bacteria is crucial to the onset of MDR and virulence, as well as biofilm formation. Thus, understanding the molecular basis of the interaction of antibiotics and inhibitors with these pumps is key to the design of more effective therapeutics. With the aim to contribute to this challenge, and complement and inspire experimental research, in silico studies on RND efflux pumps have flourished in recent decades. Here, we review a selection of such investigations addressing the main determinants behind the polyspecificity of these pumps, the mechanisms of substrate recognition, transport and inhibition, as well as the relevance of their assembly for proper functioning, and the role of protein-lipid interactions. The journey will end with a perspective on the role of computer simulations in addressing the challenges posed by these beautifully complex machineries and in supporting the fight against the spread of MDR bacteria.

Interaction of Radiopharmaceuticals with Somatostatin Receptor 2 Revealed by Molecular Dynamics Simulations.

The development of drugs targeting somatostatin receptor 2 (SSTR2), generally overexpressed in neuroendocrine tumors, is focus of intense research. A few molecules in conjugation with radionuclides are in clinical use for both diagnostic and therapeutic purposes. These radiopharmaceuticals are composed of a somatostatin analogue biovector conjugated to a chelator moiety bearing the radionuclide. To date, despite valuable efforts, a detailed molecular-level description of the interaction of radiopharmaceuticals in complex with SSTR2 has not yet been accomplished. Therefore, in this work, we carefully analyzed the key dynamical features and detailed molecular interactions of SSTR2 in complex with six radiopharmaceutical compounds selected among the few already in use (64Cu/68Ga-DOTATATE, 68Ga-DOTATOC, 64Cu-SARTATE) and some in clinical development (68Ga-DOTANOC, 64Cu-TETATATE). Through molecular dynamics simulations and exploiting recently available structures of SSTR2, we explored the influence of the different portions of the compounds (peptide, radionuclide, and chelator) in the interaction with the receptor. We identified the most stable binding modes and found distinct interaction patterns characterizing the six compounds. We thus unveiled detailed molecular interactions crucial for the recognition of this class of radiopharmaceuticals. The microscopically well-founded analysis presented in this study provides guidelines for the design of new potent ligands targeting SSTR2.

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.

Molecular insights into the Patched1 drug efflux inhibitory activity of panicein A hydroquinone: a computational study.

Human Hedgehog receptor Patched1 (PTCH1) is able to efflux chemotherapeutics of different chemical structure out of cancer cells thus contributing to multidrug resistance phenomena in tumor treatment. A screening of natural compounds purified from marine sponges led to the identification of the first PTCH1 efflux inhibitor, panicein A hydroquinone (PAH), demonstrated to increase doxorubicin toxicity in vitro and vemurafenib toxicity in vitro and in vivo. In this work we combined different computational techniques to gain molecular insights of the inhibitory activity of PAH and some of its active and inactive analogues. We first performed a thorough characterization and druggability analysis of the main putative substrate binding pockets known from available cryo-electron microscopy structures. Further, dynamical descriptors of the active and inactive PAH analogues were extracted from microsecond-long all-atom molecular dynamics simulations in water solution. Finally, a blind ensemble docking methodology coupled with the conformational analysis of compounds enabled rationalization of the interaction between PTCH1 and PAH and derivatives in terms of their intrinsic physico-chemical properties. Our results suggest that the Neck pocket is the preferential binding site for PAH analogues on PTCH1, and that compounds assuming an open cylindric-like shape in solution are most likely to be good binders for PTCH1.

Coupling enhanced sampling of the apo-receptor with template-based ligand conformers selection: performance in pose prediction in the D3R Grand Challenge 4.

We report the performance of our newly introduced Ensemble Docking with Enhanced sampling of pocket Shape (EDES) protocol coupled to a template-based algorithm to generate near-native ligand conformations in the 2019 iteration of the Grand Challenge (GC4) organized by the D3R consortium. Using either AutoDock4.2 or HADDOCK2.2 docking programs (each software in two variants of the protocol) our method generated native-like poses among the top 5 submitted for evaluation for most of the 20 targets with similar performances. The protein selected for GC4 was the human beta-site amyloid precursor protein cleaving enzyme 1 (BACE-1), a transmembrane aspartic-acid protease. We identified at least one pose whose heavy-atoms RMSD was less than 2.5 Å from the native conformation for 16 (80%) and 17 (85%) of the 20 targets using AutoDock and HADDOCK, respectively. Dissecting the possible sources of errors revealed that: (i) our EDES protocol (with minor modifications) was able to sample sub-ångstrom conformations for all 20 protein targets, reproducing the correct conformation of the binding site within ~ 1 Å RMSD; (ii) as already shown by some of us in GC3, even in the presence of near-native protein structures, a proper selection of ligand conformers is crucial for the success of ensemble-docking calculations. Importantly, our approach performed best among the protocols exploiting only structural information of the apo protein to generate conformations of the receptor for ensemble-docking calculations.

Molecular Interactions of Carbapenem Antibiotics with the Multidrug Efflux Transporter AcrB of Escherichia coli.

The drug/proton antiporter AcrB, engine of the major efflux pump AcrAB(Z)-TolC of Escherichia coli and other bacteria, is characterized by its impressive ability to transport chemically diverse compounds, conferring a multi-drug resistance (MDR) phenotype. Although hundreds of small molecules are known to be AcrB substrates, only a few co-crystal structures are available to date. Computational methods have been therefore intensively employed to provide structural and dynamical fingerprints related to transport and inhibition of AcrB. In this work, we performed a systematic computational investigation to study the interaction between representative carbapenem antibiotics and AcrB. We focused on the interaction of carbapenems with the so-called distal pocket, a region known for its importance in binding inhibitors and substrates of AcrB. Our findings reveal how the different physico-chemical nature of these antibiotics is reflected on their binding preference for AcrB. The molecular-level information provided here could help design new antibiotics less susceptible to the efflux mechanism.

Holo-like and Druggable Protein Conformations from Enhanced Sampling of Binding Pocket Volume and Shape.

Understanding molecular recognition of small molecules by proteins in atomistic detail is key for drug design. Molecular docking is a widely used computational method to mimic ligand-protein association in silico. However, predicting conformational changes occurring in proteins upon ligand binding is still a major challenge. Ensemble docking approaches address this issue by considering a set of different conformations of the protein obtained either experimentally or from computer simulations, e.g., molecular dynamics. However, holo structures prone to host (the correct) ligands are generally poorly sampled by standard molecular dynamics simulations of the apo protein. In order to address this limitation, we introduce a computational approach based on metadynamics simulations called ensemble docking with enhanced sampling of pocket shape (EDES) that allows holo-like conformations of proteins to be generated by exploiting only their apo structures. This is achieved by defining a set of collective variables that effectively sample different shapes of the binding site, ultimately mimicking the steric effect due to the ligand. We assessed the method on three challenging proteins undergoing different extents of conformational changes upon ligand binding. In all cases our protocol generates a significant fraction of structures featuring a low RMSD from the experimental holo geometry. Moreover, ensemble docking calculations using those conformations yielded in all cases native-like poses among the top-ranked ones.

Complexes formed by the siderophore-based monosulfactam antibiotic BAL30072 and their interaction with the outer membrane receptor PiuA of P. aeruginosa.

Nuclear magnetic resonance and infrared spectroscopy have been used to investigate the formation of complexes of BAL30072 with Fe3+ and Ga3+ in solution and to collect geometrical parameters supporting reliable 3D structure models. Structural models for the ligand-metal complexes with different stoichiometries have been characterized using density functional theory calculations. Blind ensemble docking to the PiuA receptor from P. aeruginosa was performed for the different complexes to compare binding affinities and statistics of the residues most frequently contacted. When compared to analogues, BAL30072 was found to have an intrinsic propensity to form complexes with low ligand-to-metal stoichiometry. By using one of the sulfate oxygen atoms as a third donor in addition to the bidentate pyridinone moiety, BAL30072 can form a L2M complex, which was predicted to be the one with the best binding affinity to PiuA. The example of BAL30072 strongly suggests that a lower stoichiometry might be the one recognized by the receptor, so that to focus only on the highest stoichiometry might be misleading for siderophores with less than six donors.

Water-mediated interactions enable smooth substrate transport in a bacterial efflux pump.

BACKGROUND: Efflux pumps of the Resistance-Nodulation-cell Division superfamily confer multi-drug resistance to Gram-negative bacteria. The most-studied polyspecific transporter belonging to this class is the inner-membrane trimeric antiporter AcrB of Escherichia coli. In previous studies, a functional rotation mechanism was proposed for its functioning, according to which the three monomers undergo concerted conformational changes facilitating the extrusion of substrates. However, the molecular determinants and the energetics of this mechanism still remain unknown, so its feasibility must be proven mechanistically. METHODS: A computational protocol able to mimic the functional rotation mechanism in AcrB was developed. By using multi-bias molecular dynamics simulations we characterized the translocation of the substrate doxorubicin driven by conformational changes of the protein. In addition, we estimated for the first time the free energy profile associated to this process. RESULTS: We provided a molecular view of the process in agreement with experimental data. Moreover, we showed that the conformational changes occurring in AcrB enable the formation of a layer of structured waters on the internal surface of the transport channel. This water layer, in turn, allows for a fairly constant hydration of the substrate, facilitating its diffusion over a smooth free energy profile. CONCLUSIONS: Our findings reveal a new molecular mechanism of polyspecific transport whereby water contributes by screening potentially strong substrate-protein interactions. GENERAL SIGNIFICANCE: We provided a mechanistic understanding of a fundamental process related to multi-drug transport. Our results can help rationalizing the behavior of other polyspecific transporters and designing compounds avoiding extrusion or inhibitors of efflux pumps.

A Database of Force-Field Parameters, Dynamics, and Properties of Antimicrobial Compounds.

We present an on-line database of all-atom force-field parameters and molecular properties of compounds with antimicrobial activity (mostly antibiotics and some beta-lactamase inhibitors). For each compound, we provide the General Amber Force Field parameters for the major species at physiological pH, together with an analysis of properties of interest as extracted from µs-long molecular dynamics simulations in explicit water solution. The properties include number and population of structural clusters, molecular flexibility, hydrophobic and hydrophilic molecular surfaces, the statistics of intraand inter-molecular H-bonds, as well as structural and dynamical properties of solvent molecules within first and second solvation shells. In addition, the database contains several key molecular parameters, such as energy of the frontier molecular orbitals, vibrational properties, rotational constants, atomic partial charges and electric dipole moment, computed by Density Functional Theory. The present database (to our knowledge the first extensive one including dynamical properties) is part of a wider project aiming to build-up a database containing structural, physico-chemical and dynamical properties of medicinal compounds using different force-field parameters with increasing level of complexity and reliability. The database is freely accessible at http://www.dsf.unica.it/translocation/db/.

Impact of corpus callosum integrity on functional interhemispheric connectivity and cognition in healthy subjects.

To examine the corpus callosum's (CC) integrity in terms of fractional anisotropy (FA) and how it affects resting-state hemispheric connectivity (rs-IHC) and cognitive function in healthy individuals. Sixty-eight healthy individuals were recruited for the study. The global FA (gFA) and FA values of each CC tract (forceps minor, body, tapetum, and forceps major) were evaluated using diffusion-weighted imaging (DWI) sequences. The homotopic functional connectivity technique was used to quantify the effects of FA in the CC tracts on bilateral functional connectivity, including the confounding effect of gFA. Brain regions with higher or lower rs-IHC were identified using the threshold-free cluster enhancement family-wise error-corrected p-value of 0.05. The null hypothesis was rejected if the p-value was ≤ 0.05 for the nonparametric partial correlation technique. Several clusters of increased rs-IHC were identified in relation to the FA of individual CC tracts, each with a unique topographic distribution and extension. Only forceps minor FA values correlated with cognitive scores. The integrity of CC influences rs-IHC differently in healthy subjects. Specifically, forceps minor anisotropy impacts rs-IHC and cognition more than other CC tracts do.

Predicting binding events in very flexible, allosteric, multi-domain proteins.

Knowledge of the structures formed by proteins and small ligands is of fundamental importance for understanding molecular principles of chemotherapy and for designing new and more effective drugs. Due to the still high costs and to the several limitations of experimental techniques, it is most often desirable to predict these ligand-protein complexes in silico, particularly when screening for new putative drugs from databases of millions of compounds. While virtual screening based on molecular docking is widely used for this purpose, it generally fails in mimicking binding events associated with large conformational changes in the protein, particularly when the latter involve multiple domains. In this work, we describe a new methodology aimed at generating bound-like conformations of very flexible and allosteric proteins bearing multiple binding sites. Validation was performed on the enzyme adenylate kinase (ADK), a paradigmatic example of proteins that undergo very large conformational changes upon ligand binding. By only exploiting the unbound structure and the putative binding sites of the protein, we generated a significant fraction of bound-like structures, which employed in ensemble-docking calculations allowed to find native-like poses of substrates, inhibitors, and catalytically incompetent binders. Our protocol provides a general framework for the generation of bound-like conformations of flexible proteins that are suitable to host different ligands, demonstrating high sensitivity to the fine chemical details that regulate protein's activity. We foresee applications in virtual screening for difficult targets, prediction of the impact of amino acid mutations on structure and dynamics, and protein engineering.

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.

Peptide Stereochemistry Effects from pKa-Shift to Gold Nanoparticle Templating in a Supramolecular Hydrogel.

The divergent supramolecular behavior of a series of tripeptide stereoisomers was elucidated through spectroscopic, microscopic, crystallographic, and computational techniques. Only two epimers were able to effectively self-organize into amphipathic structures, leading to supramolecular hydrogels or crystals, respectively. Despite the similarity between the two peptides' turn conformations, stereoconfiguration led to different abilities to engage in intramolecular hydrogen bonding. Self-assembly further shifted the pKa value of the C-terminal side chain. As a result, across the pH range 4-6, only one epimer predominated sufficiently as a zwitterion to reach the critical molar fraction, allowing gelation. By contrast, the differing pKa values and higher dipole moment of the other epimer favored crystallization. The four stereoisomers were further tested for gold nanoparticle (AuNP) formation, with the supramolecular hydrogel being the key to control and stabilize AuNPs, yielding a nanocomposite that catalyzed the photodegradation of a dye. Importantly, the AuNP formation occurred without the use of reductants other than the peptide, and the redox chemistry was investigated by LC-MS, NMR, and infrared scattering-type near field optical microscopy (IR s-SNOM). This study provides important insights for the rational design of simple peptides as minimalistic and green building blocks for functional nanocomposites.

Molecular simulations of SSTR2 dynamics and interaction with ligands.

The cyclic peptide hormone somatostatin regulates physiological processes involved in growth and metabolism, through its binding to G-protein coupled somatostatin receptors. The isoform 2 (SSTR2) is of particular relevance for the therapy of neuroendocrine tumours for which different analogues to somatostatin are currently in clinical use. We present an extensive and systematic computational study on the dynamics of SSTR2 in three different states: active agonist-bound, inactive antagonist-bound and apo inactive. We exploited the recent burst of SSTR2 experimental structures to perform µs-long multi-copy molecular dynamics simulations to sample conformational changes of the receptor and rationalize its binding to different ligands (the agonists somatostatin and octreotide, and the antagonist CYN154806). Our findings suggest that the apo form is more flexible compared to the holo ones, and confirm that the extracellular loop 2 closes upon the agonist octreotide but not upon the antagonist CYN154806. Based on interaction fingerprint analyses and free energy calculations, we found that all peptides similarly interact with residues buried into the binding pocket. Conversely, specific patterns of interactions are found with residues located in the external portion of the pocket, at the basis of the extracellular loops, particularly distinguishing the agonists from the antagonist. This study will help in the design of new somatostatin-based compounds for theranostics of neuroendocrine tumours.

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.

Optoelectronic properties of (ZnO)60 isomers.

We studied the optoelectronic properties of six possible structures of the (ZnO)(60) cluster using density functional theory (DFT). Vertical ionization energies and electron affinities are calculated through total energy differences, while the optical absorption spectra are obtained by using hybrid time-dependent DFT. The (ZnO)(60) cluster has been proven to be particularly stable and it is of potential interest for future applications in nanoelectronics, but its ground-state configuration has been unknown to date. Since the relative stability inferred from total energy calculations suffers from a strong dependence on the computational scheme adopted, we combined it with optical spectroscopy to identify the most abundant geometrical structure of this cluster. The calculated optical spectra are different for each isomer and they could be thus used in comparison with experimental data to explain the ground state of (ZnO)(60).

Inhibition of the drug efflux activity of Ptch1 as a promising strategy to overcome chemotherapy resistance in cancer cells.

The development of inhibitors of key biological mechanisms involved in multidrug resistance (MDR) burden meets an important medical need but still represents a challenging task. Major MDR targets in both bacterial and cancer cells are multidrug efflux systems. Several aspects should be considered in the attempt to design efficient inhibitors of these systems such as toxicity, stability, permeability as a few examples. In order to successfully design promising new compounds, a full understanding of the efflux mechanism is required, from both biological and structural points of view. It is nowadays well established that the success rate in classical drug design and biological evaluation improves when combined with in silico methodologies. In this review, we focus on the biological evaluation and molecular mechanistic insights of inhibitors of the drug efflux activity of the Hedgehog receptor Patched1 (Ptch1). Ptch1 is known to be over-expressed in many types of cancers, but its activity and role in the resistance to chemotherapy of cancer cells have been highlighted only recently. Remarkably, due to its peculiar efflux mechanism, inhibition of Ptch1 was shown to be particularly relevant for improving the efficacy of chemotherapy without concomitant toxicity for healthy cells or potential side effects. To date, three compounds have been identified as efficient Ptch1 inhibitors, namely astemizole, methiothepin and panicein A hydroquinone. Due to the chemical and structural differences of these molecules, the hit-to-lead drug design is not straightforward. This review describes how the merging of in vitro, in vivo and in silico studies provides molecular details that could contribute to the rational design of new Ptch1 inhibitors.

Molecular rationale for the impairment of the MexAB-OprM efflux pump by a single mutation in MexA.

Efflux pumps of the Resistance-Nodulation-cell Division (RND) superfamily contribute to intrinsic and acquired resistance in Gram-negative pathogens by expelling chemically unrelated antibiotics with high efficiency. They are tripartite systems constituted by an inner-membrane-anchored transporter, an outer membrane factor protein, and a membrane fusion protein. Multimerization of the membrane fusion protein is an essential prerequisite for full functionality of these efflux pumps. In this work, we employed complementary computational techniques to investigate the stability of a dimeric unit of MexA (the membrane fusion protein of the MexAB-OprM RND efflux pump of Pseudomonas aeruginosa), and to provide a molecular rationale for the effect of the G72S substitution, which affects MexAB-OprM functionality by impairing the assembly of MexA. Our findings indicate that: i) dimers of this protein are stable in multiple µs-long molecular dynamics simulations; ii) the mutation drastically alters the conformational equilibrium of MexA, favouring a collapsed conformation that is unlikely to form dimers or higher order assemblies. Unveiling the mechanistic aspects underlying large conformational distortions induced by minor sequence changes is informative to efforts at interfering with the activity of this elusive bacterial weapon. In this respect, our work further confirms how molecular simulations can give important contribution and useful insights to characterize the mechanism of highly complex biological systems.

AB-DB: Force-Field parameters, MD trajectories, QM-based data, and Descriptors of Antimicrobials.

Antibiotic resistance is a major threat to public health. The development of chemo-informatic tools to guide medicinal chemistry campaigns in the efficint design of antibacterial libraries is urgently needed. We present AB-DB, an open database of all-atom force-field parameters, molecular dynamics trajectories, quantum-mechanical properties, and curated physico-chemical descriptors of antimicrobial compounds. We considered more than 300 molecules belonging to 25 families that include the most relevant antibiotic classes in clinical use, such as ß-lactams and (fluoro)quinolones, as well as inhibitors of key bacterial proteins. We provide traditional descriptors together with properties obtained with Density Functional Theory calculations. Noteworthy, AB-DB contains less conventional descriptors extracted from µs-long molecular dynamics simulations in explicit solvent. In addition, for each compound we make available force-field parameters for the major micro-species at physiological pH. With the rise of multi-drug-resistant pathogens and the consequent need for novel antibiotics, inhibitors, and drug re-purposing strategies, curated databases containing reliable and not straightforward properties facilitate the integration of data mining and statistics into the discovery of new antimicrobials.