Biology subjects

Malloci, G.

Publications and source records attributed to Malloci, G..

6 recordsLinked to original sources

bioRxiv2024

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

Knowledge of the structures formed by proteins and small molecules is key to understand the molecular principles of chemotherapy and for designing new and more effective drugs. During the early stage of a drug discovery program, it is customary to predict ligand-protein complexes in silico, particularly when screening large compound databases. 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 to generate bound-like conformations of very flexible and allosteric proteins bearing multiple binding sites by exploiting only information on the unbound structure and the putative binding sites. The protocol is validated on the paradigm enzyme adenylate kinase, for which we generated a significant fraction of bound-like structures. A fraction of these conformations, employed in ensemble-docking calculations, allowed to find native-like poses of substrates and inhibitors (binding to the active form of the enzyme), as well as catalytically incompetent analogs (binding the inactive form). Our protocol provides a general framework for the generation of bound-like conformations of challenging drug targets that are suitable to host different ligands, demonstrating high sensitivity to the fine chemical details that regulate proteins activity. We foresee applications in virtual screening, in the prediction of the impact of amino acid mutations on structure and dynamics, and in protein engineering.

biophysics↗

bioRxiv2023

Predicting Permeation of Compounds across the Outer Membrane of P. aeruginosa Using Molecular Descriptors: Advantages and Limitations

The ability of Gram-negative pathogens to adapt and protect themselves against antibiotics is a growing threat to public health. The low permeability of the outer membrane (OM) in combination with effective multidrug efflux pumps, constitute the two main antibiotic resistance mechanisms. Though much efforts have been devoted to discover new antibiotics that can bypass these defense mechanisms, no new antibiotic classes have been introduced into clinics in the last 35 years. Models that identify specific descriptors of molecular properties and predict the likelihood that a given compound is capable of successfully permeate the OM and inhibit bacterial growth while avoiding efflux could facilitate the discovery of novel classes of antibiotics. Here we evaluate 174 molecular descriptors of 1260 antimicrobial compounds and study their correlations with antibacterial activity in Gram-negative Pseudomonas aeruginosa. While part of these descriptors are computed using traditional approaches based on the physicochemical properties intrinsic to the compounds, ensemble docking and all-atom molecular dynamics (MD) simulations are used to derive additional bacterium-specific mechanistic properties. Descriptors of compound permeation across the OM were calculated using all-atom MD simulations of the compounds in different subregions of the OM model. Descriptors of interactions with efflux pumps were calculated from ensemble docking of compounds targeting specific binding pockets of MexB, the major efflux transporter of P. aeruginosa. Using these descriptors and the measured antibacterial inhibitory concentrations of compounds, we design and implement a statistical protocol to identify a subset of the molecular properties that are predictive of whether a given compound is a strong or weak permeator across the Gram-negative OM. Our results indicate that 88.4% of the compounds that show measurable antibacterial activity, follow very consistent rules of permeation, which highlight the critical role that the interaction between the compound and the OM have at predicting permeation. The remaining 11.6% of the compounds, although less predictive, are characterized by distinctive structural markers that can be used to minimize classification errors. An implementation of the permeation rules and the structural markers uncovered in our study is shown, and it demonstrates the accuracy of our approach in a set of previously unseen compounds. Taken together, our analysis sheds new light on the key molecular properties that drug candidates should have in order to be effective at OM permeation/inhibition of P. aeruginosa, and opens the gate to similar data-driven studies in other Gram-negative pathogens.

biophysics↗

bioRxiv2023

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 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. Previous analyses of antibacterial and biochemical activities showed that these compounds vary broadly in their efficiency as inhibitors or substrates of MexAB and can be categorized into different functional classes. Here, we performed multi-copy molecular dynamics simulations, machine learning analyses and site-directed mutagenesis of MexB to investigate interactions of MexB with representatives of the various classes. 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. ImportanceMultidrug 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, 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.

microbiology↗

bioRxiv2020

Perturbed structural dynamics underlie inhibition and altered specificity of the multidrug efflux pump AcrB

Resistance-nodulation-division (RND) efflux pumps play a key role in inherent and evolved multidrug-resistance (MDR) in bacteria. AcrB is the prototypical member of the RND family and acts to recognise and export a wide range of chemically distinct molecules out of bacteria, conferring resistance to a variety of antibiotics. Although high resolution structures exist for AcrB, its conformational fluctuations and their putative role in function are largely unknown, preventing a complete mechanistic understanding of efflux and inhibition. Here, we determine these structural dynamics in the presence of AcrB substrates using hydrogen/deuterium exchange mass spectrometry, complemented by molecular modelling, drug binding and bacterial susceptibility studies. We show that the well-studied efflux pump inhibitor phenylalanine-arginine-{beta}-naphthylamide (PA{beta}N) potentiates antibiotic activity by restraining drug-binding pocket dynamics, rather than preventing antibiotic binding. We also reveal that a drug-binding pocket substitution discovered within an MDR clinical isolate, AcrBG288D, modifies the plasticity of the transport pathway, which could explain its altered substrate specificity. Our results provide molecular insight into drug export and inhibition of a major MDR-conferring efflux pump and the important directive role of its dynamics.

biochemistry↗

bioRxiv2018

An enhanced-sampling MD-based protocol for molecular docking

Understanding molecular recognition of proteins by small molecules is key for drug design. Despite the number of experimental structures of ligand-protein complexes keeps growing, the number of available targets remains limited compared to the druggable genome, and structural diversity is generally low, which affects the chemical variance of putative lead compounds. From a computational perspective, molecular docking is widely used to mimic ligand-protein association in silico. Ensemble-docking approaches include flexibility through a set of different conformations of the protein obtained either experimentally or from computer simulations, e.g. molecular dynamics. However, 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 (EDES - Ensemble-Docking with Enhanced-sampling of pocket Shape) to generate druggable conformations of proteins only exploiting 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 ligands to generate holo-like binding site geometries. We assessed the method on two challenging proteins undergoing different extents of conformational changes upon ligand binding. In both cases our protocol generated a significant fraction of structures featuring a low RMSD from the experimental holo conformation. Moreover, ensemble docking calculations using those conformations yielded native-like poses among the top ranked ones for both targets. This proof of concept study paves the route towards an automated workflow to generate druggable conformations of proteins, which should become a precious tool for structure-based drug design.

biophysics↗

bioRxiv2017

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

Efflux pumps of the Resistance-Nodulation-cell Division superfamily confer multi-drug resistance to Gram-negative bacteria. AcrB of Escherichia coli is a paradigm model of these polyspecific transporters. The molecular determinants and the energetics of the functional rotation mechanism proposed for the export of substrates by this protein have not yet been unveiled. To this aim, we implemented an original protocol that allows mimicking substrate transport in silico. We show that the conformational changes occurring in AcrB enable the formation of a layer of structured waters on the surface of the substrate transport channel. This, in turn, allows for a fairly constant hydration of the substrate that facilitates its diffusion. Our findings reveal a new molecular mechanism of transport in polyspecific systems, whereby waters contribute by screening potentially strong substrate-protein interactions. The mechanistic understanding of a fundamental process related to multi-drug transport provided here could help rationalizing the behavior of other polyspecific systems.

biophysics↗