Promising Molecular Architectures for Two-Photon Probes in the Diagnosis of α-Synuclein Aggregates.

The abnormal deposition of protein in the brain is the central factor in neurodegenerative disorders (NDs). These detrimental aggregates, stemming from the misfolding and subsequent irregular aggregation of α-synuclein protein, are primarily accountable for conditions such as Parkinson's disease, Alzheimer's disease, and dementia. Two-photon-excited (TPE) probes are a promising tool for the early-stage diagnosis of these pathologies as they provide accurate spatial resolution, minimal intrusion, and the ability for prolonged observation. To identify compounds with the potential to function as diagnostic probes using two-photon techniques, we explore three distinct categories of compounds: Hydroxyl azobenzene (AZO-OH); Dicyano-vinyl bithiophene (DCVBT); and Tetra-amino phthalocyanine (PcZnNH2). The molecules were structurally and optically characterized using a multi-technique approach via UV-vis absorption, Raman spectroscopy, three-dimensional fluorescence mapping (PLE), time-resolved photoluminescence (TRPL), and pump and probe measurements. Furthermore, quantum chemical and molecular docking calculations were performed to provide insights into the photophysical properties of the compounds as well as to assess their affinity with the α-synuclein protein. This innovative approach seeks to enhance the accuracy of in vivo probing, contributing to early Parkinson's disease (PD) detection and ultimately allowing for targeted intervention strategies.

Machine Learning Integrating Protein Structure, Sequence, and Dynamics to Predict the Enzyme Activity of Bovine Enterokinase Variants.

Despite recent advances in computational protein science, the dynamic behavior of proteins, which directly governs their biological activity, cannot be gleaned from sequence information alone. To overcome this challenge, we propose a framework that integrates the peptide sequence, protein structure, and protein dynamics descriptors into machine learning algorithms to enhance their predictive capabilities and achieve improved prediction of the protein variant function. The resulting machine learning pipeline integrates traditional sequence and structure information with molecular dynamics simulation data to predict the effects of multiple point mutations on the fold improvement of the activity of bovine enterokinase variants. This study highlights how the combination of structural and dynamic data can provide predictive insights into protein functionality and address protein engineering challenges in industrial contexts.

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.

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.

A framework for dissecting affinities of multidrug efflux transporter AcrB to fluoroquinolones.

Sufficient concentration of antibiotics close to their target is key for antimicrobial action. Among the tools exploited by bacteria to reduce the internal concentration of antibiotics, multidrug efflux pumps stand out for their ability to capture and expel many unrelated compounds out of the cell. Determining the specificities and efflux efficiency of these pumps towards their substrates would provide quantitative insights into the development of antibacterial strategies. In this light, we developed a competition efflux assay on whole cells, that allows measuring the efficacy of extrusion of clinically used quinolones in populations and individual bacteria. Experiments reveal the efficient competitive action of some quinolones that restore an active concentration of other fluoroquinolones. Computational methods show how quinolones interact with the multidrug efflux transporter AcrB. Combining experiments and computations unveils a key molecular mechanism acting in vivo to detoxify bacterial cells. The developed assay can be generalized to the study of other efflux pumps.

The Structural and Functional Study of Efflux Pumps Belonging to the RND Transporters Family from Gram-Negative Bacteria.

Antimicrobial-resistant bacterial infections are a major and costly public health concern [...].

Pyridylpiperazine-based allosteric inhibitors of RND-type multidrug efflux pumps.

Efflux transporters of the RND family confer resistance to multiple antibiotics in Gram-negative bacteria. Here, we identify and chemically optimize pyridylpiperazine-based compounds that potentiate antibiotic activity in E. coli through inhibition of its primary RND transporter, AcrAB-TolC. Characterisation of resistant E. coli mutants and structural biology analyses indicate that the compounds bind to a unique site on the transmembrane domain of the AcrB L protomer, lined by key catalytic residues involved in proton relay. Molecular dynamics simulations suggest that the inhibitors access this binding pocket from the cytoplasm via a channel exclusively present in the AcrB L protomer. Thus, our work unveils a class of allosteric efflux-pump inhibitors that likely act by preventing the functional catalytic cycle of the RND pump.

Native or Non-Native Protein-Protein Docking Models? Molecular Dynamics to the Rescue.

Molecular docking excels at creating a plethora of potential models of protein-protein complexes. To correctly distinguish the favorable, native-like models from the remaining ones remains, however, a challenge. We assessed here if a protocol based on molecular dynamics (MD) simulations would allow distinguishing native from non-native models to complement scoring functions used in docking. To this end, the first models for 25 protein-protein complexes were generated using HADDOCK. Next, MD simulations complemented with machine learning were used to discriminate between native and non-native complexes based on a combination of metrics reporting on the stability of the initial models. Native models showed higher stability in almost all measured properties, including the key ones used for scoring in the Critical Assessment of PRedicted Interaction (CAPRI) competition, namely the positional root mean square deviations and fraction of native contacts from the initial docked model. A random forest classifier was trained, reaching a 0.85 accuracy in correctly distinguishing native from non-native complexes. Reasonably modest simulation lengths of the order of 50-100 ns are sufficient to reach this accuracy, which makes this approach applicable in practice.

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.

The challenge of intracellular antibiotic accumulation, a function of fluoroquinolone influx versus bacterial efflux.

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.

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.

Molecular basis for the different interactions of congeneric substrates with the polyspecific transporter AcrB.

The drug/proton antiporter AcrB, which is part of the major efflux pump AcrABZ-TolC in Escherichia coli, is the paradigm transporter of the resistance-nodulation-cell division (RND) superfamily. Despite the impressive ability of AcrB to transport many chemically unrelated compounds, only a few of these ligands have been co-crystallized with the protein. Therefore, the molecular features that distinguish good substrates of the pump from poor ones have remained poorly understood to date. In this work, a thorough in silico protocol was employed to study the interactions of a series of congeneric compounds with AcrB to examine how subtle chemical differences affect the recognition and transport of substrates by this protein. Our analysis allowed us to discriminate among different compounds, mainly in terms of specific interactions with diverse sub-sites within the large distal pocket of AcrB. Our findings could provide valuable information for the design of new antibiotics that can evade the antimicrobial resistance mediated by efflux pump machinery.

A New Critical Conformational Determinant of Multidrug Efflux by an MFS Transporter.

Secondary multidrug (Mdr) transporters utilize ion concentration gradients to actively remove antibiotics and other toxic compounds from cells. The model Mdr transporter MdfA from Escherichia coli exchanges dissimilar drugs for protons. The transporter should open at the cytoplasmic side to enable access of drugs into the Mdr recognition pocket. Here we show that the cytoplasmic rim around the Mdr recognition pocket represents a previously overlooked important regulatory determinant in MdfA. We demonstrate that increasing the positive charge of the electrically asymmetric rim dramatically inhibits MdfA activity and sometimes even leads to influx of planar, positively charged compounds, resulting in drug sensitivity. Our results suggest that unlike the mutants with the electrically modified rim, the membrane-embedded wild-type MdfA exhibits a significant probability of an inward-closed conformation, which is further increased by drug binding. Since MdfA binds drugs from its inward-facing environment, these results are intriguing and raise the possibility that the transporter has a sensitive, drug-induced conformational switch, which favors an inward-closed state.

Computer simulations of the activity of RND efflux pumps.

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.

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.

HIV-1 Protease Dimerization Dynamics Reveals a Transient Druggable Binding Pocket at the Interface.

The binding mechanism of HIV-1 protease monomers leading to the catalytically competent dimeric enzyme has been investigated by means of state-of-the-art atomistic simulations. The emerging picture allows a deeper understanding of experimental observations and reveals that water molecules trapped at the interface have an important role in slowing down the kinetics of the association process. Unexpectedly, a cryptic binding pocket is identified at the interface of the complex, corresponding to a partially bound dimer that lacks enzymatic function. The pocket has a transient nature with a lifetime longer than 1 µs, and it displays very favorable druggability features. Docking as well as MM-GBSA free-energy calculations further support the possibility to target the new binding site by means of inhibitors able to prevent the complete dimerization by capturing the inactive conformation. This discovery could open the way to the rational design of a new class of anti-HIV drugs.

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/.

Molecular recognition of DNA by ligands: roughness and complexity of the free energy profile.

Understanding the molecular mechanism by which probes and chemotherapeutic agents bind to nucleic acids is a fundamental issue in modern drug design. From a computational perspective, valuable insights are gained by the estimation of free energy landscapes as a function of some collective variables (CVs), which are associated with the molecular recognition event. Unfortunately the choice of CVs is highly non-trivial because of DNA's high flexibility and the presence of multiple association-dissociation events at different locations and/or sliding within the grooves. Here we have applied a modified version of Locally-Scaled Diffusion Map (LSDMap), a nonlinear dimensionality reduction technique for decoupling multiple-timescale dynamics in macromolecular systems, to a metadynamics-based free energy landscape calculated using a set of intuitive CVs. We investigated the binding of the organic drug anthramycin to a DNA 14-mer duplex. By performing an extensive set of metadynamics simulations, we observed sliding of anthramycin along the full-length DNA minor groove, as well as several detachments from multiple sites, including the one identified by X-ray crystallography. As in the case of equilibrium processes, the LSDMap analysis is able to extract the most relevant collective motions, which are associated with the slow processes within the system, i.e., ligand diffusion along the minor groove and dissociation from it. Thus, LSDMap in combination with metadynamics (and possibly every equivalent method) emerges as a powerful method to describe the energetics of ligand binding to DNA without resorting to intuitive ad hoc reaction coordinates.

Molecular motions in drug design: the coming age of the metadynamics method.

Metadynamics is emerging as a useful free energy method in physics, chemistry and biology. Recently, it has been applied also to investigate ligand binding to biomolecules of pharmacological interest. Here, after introducing the basic idea of the method, we review applications to challenging targets for pharmaceutical intervention. We show that this methodology, especially when combined with a variety of other computational approaches such as molecular docking and/or molecular dynamics simulation, may be useful to predict structure and energetics of ligand/target complexes even when the targets lack a deep binding cavity, such as DNA and proteins undergoing fibrillation in neurodegenerative diseases. Furthermore, the method allows investigating the routes of molecular recognition and the associated binding energy profiles, providing a molecular interpretation to experimental data.

Copper-1,10-phenanthroline complexes binding to DNA: structural predictions from molecular simulations.

Copper-1,10-phenanthroline (phen) complexes Cu(phen)(2)(), Cu(2-Clip-phen), and Cu(3-Clip-phen) (Clip = a serinol bridge between the phen parts) are typically employed as DNA-cleaving agents and are now becoming increasingly important for building multifunctional drugs with improved cytotoxic properties. For instance, Cu(3-Clip-phen) has been combined with distamycin-like minor-groove binders and cisplatin-derivatives, leading to promising results. Density Functional Theory (DFT) and docking calculations as well as molecular dynamics (MD) simulations were performed to describe the mode of binding to DNA of these complexes. Our data suggest the minor-groove binding to be more probable than (partial) intercalation and major-groove binding. In addition, it was found that a combination of factors including planarity, van der Waals interactions with DNA, and structural complementarities may be the key for the cleavage efficiency of these copper complexes.