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Ribonucleic acids are gradually becoming relevant players among putative drug targets, thanks to the increasing amount of structural data exploitable for the rational design of selective and potent binders that can modulate their activity. Mainly, this information allows employing different computational techniques for predicting how well would a ribonucleic-targeting agent fit within the active site of its target macromolecule. Due to some intrinsic peculiarities of complexes involving nucleic acids, such as structural plasticity, surface charge distribution, and solvent-mediated interactions, the application of routinely adopted methodologies like molecular docking is challenged by scoring inaccuracies, while more physically rigorous methods such as molecular dynamics require long simulation times which hamper their conformational sampling capabilities. In the present work, we present the first application of Thermal Titration Molecular Dynamics (TTMD), a recently developed method for the qualitative estimation of unbinding kinetics, to characterize RNA-ligand complexes. In this article, we explored its applicability as a post-docking refinement tool on RNA in complex with small molecules, highlighting the capability of this method to identify the native binding mode among a set of decoys across various pharmaceutically relevant test cases.

Neuroblastoma (NB) is the most commonly diagnosed extracranial solid tumor in children, accounting for 15% of all childhood cancer deaths. Although the 5-year survival rate of patients with a high-risk disease has increased in recent decades, NB remains a challenge in pediatric oncology, and the identification of novel potential therapeutic targets and agents is an urgent clinical need. The RNA-binding protein LIN28B has been identified as an oncogene in NB and is associated with a poor prognosis. Given that LIN28B acts by negatively regulating the biogenesis of the tumor suppressor let-7 miRNAs, we reasoned that selective interference with the LIN28B/let-7 miRNA interaction would increase let-7 miRNA levels, ultimately leading to reduced NB aggressiveness. Here, we selected (−)-epigallocatechin 3-gallate (EGCG) out of 4959 molecules screened as the molecule with the best inhibitory activity on LIN28B/let-7 miRNA interaction and showed that treatment with PLC/PLGA-PEG nanoparticles containing EGCG (EGCG-NPs) led to an increase in mature let-7 miRNAs and a consequent inhibition of NB cell growth. In addition, EGCG-NP pretreatment reduced the tumorigenic potential of NB cells in vivo. These experiments suggest that the LIN28B/let-7 miRNA axis is a good therapeutic target in NB and that EGCG, which can interfere with this interaction, deserves further preclinical evaluation.

Despite a huge effort by the scientific community to determine the animal reservoir of SARS-CoV-2, which led to the identification of several SARS-CoV-2-related viruses both in bats and in pangolins, the origin of SARS-CoV-2 is still not clear. Recently, Temmam et al. reported the discovery of bat coronaviruses with a high degree of genome similarity with SARS-CoV-2, especially concerning the RBDs of the S protein, which mediates the capability of such viruses to enter and therefore infect human cells through a hACE2-dependent pathway. These viruses, especially the one named BANAL-236, showed a higher affinity for the hACE2 compared to the original strain of SARS-CoV-2. In the present work, we analyse the similarities and differences between the 3CL protease (main protease, Mpro) of these newly reported viruses and SARS-CoV-2, discussing their relevance relative to the efficacy of existing therapeutic approaches against COVID-19, particularly concerning the recently approved orally available Paxlovid, and the development of future ones.

Since the outbreak of the COVID-19 pandemic in December 2019, the SARS-CoV-2 genome has undergone several mutations. The emergence of such variants has resulted in multiple pandemic waves, contributing to sustaining to date the number of infections, hospitalisations, and deaths despite the swift development of vaccines, since most of these mutations are concentrated on the Spike protein, a viral surface glycoprotein that is the main target for most vaccines. A milestone in the fight against the COVID-19 pandemic has been represented by the development of Paxlovid, the first orally available drug against COVID-19, which acts on the Main Protease (Mpro). In this article, we analyse the structural features of both the Spike protein and the Mpro of the recently reported SARS-CoV-2 variant XE, as well the closely related XD and XF ones, discussing their impact on the efficacy of existing treatments against COVID-19 and on the development of future ones.

ABSTRACT Every year, dengue virus (DENV) causes one hundred million infections worldwide that can result in dengue disease and severe dengue. Two other mosquito-borne flaviviruses, i.e., Zika virus (ZIKV) and West Nile virus (WNV), are responsible of prolonged outbreaks and are associated with severe neurological diseases, congenital defects, and eventually death. These three viruses, despite their importance for global public health, still lack specific drug treatments. Here, we describe the structure-guided discovery of small molecules with pan-flavivirus antiviral potential by a virtual screening of ~1 million structures targeting the NS3-NS5 interaction surface of different flaviviruses. Two molecules inhibited the interaction between DENV NS3 and NS5 in vitro and the replication of all DENV serotypes as well as ZIKV and WNV and exhibited low propensity to select resistant viruses. Remarkably, one molecule demonstrated efficacy in a mouse model of dengue by reducing peak viremia, viral load in target organs, and associated tissue pathology. This study provides the proof of concept that targeting the flaviviral NS3-NS5 interaction is an effective therapeutic strategy able to reduce virus replication in vivo and discloses new chemical scaffolds that could be further developed, thus providing a significant milestone in the development of much awaited broad-spectrum antiflaviviral drugs. IMPORTANCE More than one-third of the human population is at risk of infection by different mosquito-borne flaviviruses. Despite this, no specific antiviral drug is currently available. In this work, using a computational approach based on molecular dynamics simulation and virtual screening of ~1 million small-molecule structures, we identified a compound that targets the interaction between the two sole flaviviral enzymes, i.e., NS3 and NS5. This compound demonstrated pan-serotype anti-DENV activity and pan-flavivirus potential in infected cells, low propensity to select viral resistant mutant viruses, and efficacy in a mouse model of dengue. Broad-spectrum antivirals are much awaited, and this work represents a significant advance toward the development of therapeutic molecules with extended antiflavivirus potential that act by an innovative mechanism and could be used alone or in combination with other antivirals.

G-quadruplexes (G4s) are nucleic acid secondary structures detected within human chromosomes, that cluster at gene promoters and enhancers. This suggests that G4s may play specific roles in the regulation of gene expression. Within a distinct subgroup of G-rich domains, the formation of two or more adjacent G4 units (G4-repeats) is feasible. Recently it was shown that Vimentin, a protein highly expressed within mesenchymal cells, selectively recognizes these arrangements. Putative G4-repeats have been searched within the human gene proximal promoters by the bioinformatics tool QPARSE and they resulted to be enriched at genes related to epithelial-to-mesenchymal transition (EMT). This suggested that Vimentin binding at these sites might be relevant for the maintenance of the mesenchymal phenotype. Among all the identified sequences, in the present study we selected the one located within the promoter of the TEAD4 oncogene. TEAD4 codifies for a transcriptional enhancer factor, TEAD4, that actively promotes EMT, supporting, cell proliferation and migration. Moreover, in colorectal cancer cells TEAD4 directly enhances the expression of Vimentin. Thus, the possible interaction of Vimentin with TEAD4 promoter could highlight a positive feedback loop between these two factors, associated to important tumor metastasis related events. Here, we exploited spectroscopic and electrophoretic measurements under different conditions to address the folding behavior of the selected sequence. This allowed us to validate the folding of TEAD4 promoter into a G4-repeat able to interact with Vimentin.

In the last 20 years, fragment-based drug discovery (FBDD) has become a popular and consolidated approach within the drug discovery pipeline, due to its ability to bring several drug candidates to clinical trials, some of them even being approved and introduced to the market. A class of targets that have proven to be particularly suitable for this method is represented by kinases, as demonstrated by the approval of BRAF inhibitor vemurafenib. Within this wide and diverse set of proteins, protein kinase CK1δ is a particularly interesting target for the treatment of several widespread neurodegenerative diseases, such as Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis. Computational methodologies, such as molecular docking, are already routinely and successfully applied in FBDD campaigns alongside experimental techniques, both in the hit-discovery and in the hit-optimization stage. Concerning this, the open-source software Autogrow, developed by the Durrant lab, is a semi-automated computational protocol that exploits a combination between a genetic algorithm and a molecular docking software for de novo drug design and lead optimization. In the current work, we present and discuss a modified version of the Autogrow code that implements a custom scoring function based on the similarity between the interaction fingerprint of investigated compounds and a crystal reference. To validate its performance, we performed both a de novo and a lead-optimization run (as described in the original publication), evaluating the ability of our fingerprint-based protocol to generate compounds similar to known CK1δ inhibitors based on both the predicted binding mode and the electrostatic and shape similarity in comparison with the standard Autogrow protocol.

Molecular docking is one of the most widely used computational approaches in the field of rational drug design, thanks to its favorable balance between the rapidity of execution and the accuracy of provided results. Although very efficient in exploring the conformational degrees of freedom available to the ligand, docking programs can sometimes suffer from inaccurate scoring and ranking of generated poses. To address this issue, several post-docking filters and refinement protocols have been proposed throughout the years, including pharmacophore models and molecular dynamics simulations. In this work, we present the first application of Thermal Titration Molecular Dynamics (TTMD), a recently developed method for the qualitative estimation of protein-ligand unbinding kinetics, to the refinement of docking results. TTMD evaluates the conservation of the native binding mode throughout a series of molecular dynamics simulations performed at progressively increasing temperatures with a scoring function based on protein-ligand interaction fingerprints. The protocol was successfully applied to retrieve the native-like binding pose among a set of decoy poses of drug-like ligands generated on four different pharmaceutically relevant biological targets, including casein kinase 1δ, casein kinase 2, pyruvate dehydrogenase kinase 2, and SARS-CoV-2 main protease.

The chemical structure of PF-07321332, the first orally available Covid-19 clinical candidate, has recently been revealed by Pfizer. No information has been provided about the interaction pattern between PF-07321332 and its biomolecular counterpart, the SARS-CoV-2 main protease (Mpro). In the present work, we exploited Supervised Molecular Dynamics (SuMD) simulations to elucidate the key features that characterise the interaction between this drug candidate and the protease, emphasising similarities and differences with other structurally related inhibitors such as Boceprevir and PF-07304814. The structural insights provided by SuMD will hopefully be able to inspire the rational discovery of other potent and selective protease inhibitors.

Fragment-based lead discovery (FBLD) is one of the most efficient methods to develop new drugs. We present here a new computational protocol called High-Throughput Supervised Molecular Dynamics (HT-SuMD), which makes it possible to automatically screen up to thousands of fragments, representing therefore a new valuable resource to prioritise fragments in FBLD campaigns. The protocol was applied to Bcl-XL, an oncological protein target involved in the regulation of apoptosis through protein–protein interactions. Initially, HT-SuMD performances were validated against a robust NMR-based screening, using the same set of 100 fragments. These independent results showed a remarkable agreement between the two methods. Then, a virtual screening on a larger library of additional 300 fragments was carried out and the best hits were validated by NMR. Remarkably, all the in silico selected fragments were confirmed as Bcl-XL binders. This represents, to date, the largest computational fragments screening entirely based on MD.

Trypanosoma brucei is a species of kinetoplastid causing sleeping sickness in humans and nagana in cows and horses. One of the peculiarities of this species of parasites is represented by their redox metabolism. One of the proteins involved in this redox machinery is the monothiol glutaredoxin 1 (1CGrx1) which is characterized by a unique disordered N-terminal extension exclusively conserved in trypanosomatids and other organisms. This region modulates the binding profile of the glutathione/trypanothione binding site, one of the functional regions of 1CGrx1. No endogenous ligands are known to bind this protein which does not present well-shaped binding sites, making it target particularly challenging to target. With the aim of targeting this peculiar system, we carried out two different screenings: (i) a fragment-based lead discovery campaign directed to the N-terminal as well as to the canonical binding site of 1CGrx1; (ii) a structure-based virtual screening directed to the 1CGrx1 canonical binding site. Here we report a small molecule that binds at the glutathione binding site in which the binding mode of the molecule was deeply investigated by Nuclear Magnetic Resonance (NMR). This compound represents an important step in the attempt to develop a novel strategy to interfere with the peculiar Trypanosoma Brucei redox system, making it possible to shed light on the perturbation of this biochemical machinery and eventually to novel therapeutic possibilities.

Macrocycles are attractive structures for drug development due to their favorable structural features, potential in binding to targets with flat featureless surfaces, and their ability to disrupt protein–protein interactions. Moreover, large novel highly diverse libraries of low-molecular-weight macrocycles with therapeutically favorable characteristics have been recently established. Considering the mentioned facts, having a validated, fast, and accurate computational protocol for studying the molecular recognition and binding mode of this interesting new class of macrocyclic peptides deemed to be helpful as well as insightful in the quest of accelerating drug discovery. To that end, the ability of the in-house supervised molecular dynamics protocol called SuMD in the reproduction of the X-ray crystallography final binding state of a macrocyclic non-canonical tetrapeptide—from a novel library of 8,988 sub-kilodalton macrocyclic peptides—in the thrombin active site was successfully validated. A comparable binding mode with the minimum root-mean-square deviation (RMSD) of 1.4 Å at simulation time point 71.6 ns was achieved. This method validation study extended the application domain of the SuMD sampling method for computationally cheap, fast but accurate, and insightful macrocycle–protein molecular recognition studies.

Amyotrophic lateral sclerosis (ALS) is a degenerating disease involving the motor neurons, which causes a progressive loss of movement ability, usually leading to death within 2 to 5 years from the diagnosis. Much effort has been put into research for an effective therapy for its eradication, but still, no cure is available. The only two drugs approved for this pathology, Riluzole and Edaravone, are onlyable to slow down the inevitable disease progression. As assessed in the literature, drug targets such as protein kinases have already been extensively examined as potential drug targets for ALS, with some molecules already in clinical trials. Here, we focus on the involvement of another very important and studied class of biological entities, G protein-coupled receptors (GPCRs), in the onset and progression of ALS. This workaimsto give an overview of what has been already discovered on the topic, providing useful information and insights that can be used by scientists all around the world who are putting efforts into the fight against this very important neurodegenerating disease.

The function of the allosteric sodium ion in stabilizing the inactive form of GPCRs has been extensively described in the past decades. Its presence has been reported to be essential for the binding of antagonist molecules in the orthosteric site of these very important therapeutical targets. Among the GPCR–antagonist crystal structures available, in most cases, the sodium ion could not be experimentally resolved, obliging computational scientists using GPCRs as targets for virtual screening to ask: “Should the sodium ion affect the accuracy of pose prediction in docking GPCR antagonists?” In the present study, we examined the performance of three orthogonal docking programs in the self-docking of GPCR antagonists to try to answer this question. The results of the present work highlight that if the sodium ion is resolved in the crystal structure used as the target, it should also be taken into account during the docking calculations. If the crystallographic studies were not able to resolve the sodium ion then no advantage would be obtained if this is manually inserted in the virtual target. The outcomes of the present analysis are useful for researchers exploiting molecular docking-based virtual screening to efficiently identify novel GPCR antagonists.

Adenosine receptors have been a promising class of targets for the development of new therapies for several diseases. In recent years, a renewed interest in this field has risen, thanks to the implementation of a novel class of agonists that lack the ribose moiety, once considered essential for the agonistic profile. Recently, an X-ray crystal structure of the A2A adenosine receptor has been solved, providing insights about the receptor activation from this novel class of agonists. Starting from this structural information, we have performed supervised molecular dynamics (SuMD) simulations to investigate the binding pathway of a non-nucleoside adenosine receptor agonist as well as one of three classic agonists. Furthermore, we analyzed the possible role of water molecules in receptor activation.

Although proteins have represented the molecular target of choice in the development of new drug candidates, the pharmaceutical importance of ribonucleic acids has gradually been growing. The increasing availability of structural information has brought to light the existence of peculiar three-dimensional RNA arrangements, which can, contrary to initial expectations, be recognized and selectively modulated through small chemical entities or peptides. The application of classical computational methodologies, such as molecular docking, for the rational development of RNA-binding candidates is, however, complicated by the peculiarities characterizing these macromolecules, such as the marked conformational flexibility, the singular charges distribution, and the relevant role of solvent molecules. In this work, we have thus validated and extended the applicability domain of SuMD, an all-atoms molecular dynamics protocol that allows to accelerate the sampling of molecular recognition events on a nanosecond timescale, to ribonucleotide targets of pharmaceutical interest. In particular, we have proven the methodological ability by reproducing the binding mode of viral or prokaryotic ribonucleic complexes, as well as that of artificially engineered aptamers, with an impressive degree of accuracy.

Summary: Mitochondrial Ca2+ uptake depends on the mitochondrial calcium uniporter (MCU) complex, a highly selective channel of the inner mitochondrial membrane (IMM). Here, we screen a library of 44,000 non-proprietary compounds for their ability to modulate mitochondrial Ca2+ uptake. Two of them, named MCU-i4 and MCU-i11, are confirmed to reliably decrease mitochondrial Ca2+ influx. Docking simulations reveal that these molecules directly bind a specific cleft in MICU1, a key element of the MCU complex that controls channel gating. Accordingly, in MICU1-silenced or deleted cells, the inhibitory effect of the two compounds is lost. Moreover, MCU-i4 and MCU-i11 fail to inhibit mitochondrial Ca2+ uptake in cells expressing a MICU1 mutated in the critical amino acids that forge the predicted binding cleft. Finally, these compounds are tested ex vivo, revealing a primary role for mitochondrial Ca2+ uptake in muscle growth. Overall, MCU-i4 and MCU-i11 represent leading molecules for the development of MICU1-targeting drugs. : Di Marco et al. report the discovery of MCU-i4 and MCU-i11, two negative modulators of the MCU that decrease mitochondrial Ca2+ uptake. MCU-i4 and MCU-i11 bind MICU1, the key MCU interactor that controls channel gating, and MICU1 is required for their activity. Thus, these small molecules represent lead MICU1-targeting compounds. Keywords: mitochondrial calcium uptake, MICU1, mitochondrial calcium uniporter, MCU, high-throughput screening, HTS, molecular modeling, active compounds, small molecules

In the latest few decades, molecular docking has imposed itself as one of the most used approaches for computational drug discovery. Several docking benchmarks have been published, comparing the performance of different algorithms in respect to a molecular target of interest, usually evaluating their ability in reproducing the experimental data, which, in most cases, comes from X-ray structures. In this study, we elucidated the variation of the performance of three docking algorithms, namely GOLD, Glide, and PLANTS, in replicating the coordinates of the crystallographic ligands of SARS-CoV-2 main protease (Mpro). Through the comparison of the data coming from docking experiments and the values derived from the calculation of the solvent exposure of the crystallographic ligands, we highlighted the importance of this last variable for docking performance. Indeed, we underlined how an increase in the percentage of the ligand surface exposed to the solvent in a crystallographic complex makes it harder for the docking algorithms to reproduce its conformation. We further validated our hypothesis through molecular dynamics simulations, showing that the less stable protein–ligand complexes (in terms of root-mean-square deviation and root-mean-square fluctuation) tend to be derived from the cases in which the solvent exposure of the ligand in the starting system is higher.

Abstract Glutaredoxins (Grx) are small proteins conserved throughout all the kingdoms of life that are engaged in a wide variety of biological processes and share a common thioredoxin-fold. Among them, class II Grx are redox-inactive proteins involved in iron-sulfur (FeS) metabolism. They contain a single thiol group in their active site and use low molecular mass thiols such as glutathione as ligand for binding FeS-clusters. In this study, we investigated molecular aspects of 1CGrx1 from the pathogenic parasite Trypanosoma brucei brucei, a mitochondrial class II Grx that fulfills an indispensable role in vivo. Mitochondrial 1CGrx1 from trypanosomes differs from orthologues in several features including the presence of a parasite-specific N-terminal extension (NTE) whose role has yet to be elucidated. Previously we have solved the structure of a truncated form of 1CGrx1 containing only the conserved glutaredoxin domain but lacking the NTE. Our aim here is to investigate the effect of the NTE on the conformation of the protein. We therefore solved the NMR structure of the full-length protein, which reveals subtle but significant differences with the structure of the NTE-less form. By means of different experimental approaches, the NTE proved to be intrinsically disordered and not involved in the non-redox dependent protein dimerization, as previously suggested. Interestingly, the portion comprising residues 65–76 of the NTE modulates the conformational dynamics of the glutathione-binding pocket, which may play a role in iron-sulfur cluster assembly and delivery. Furthermore, we disclosed that the class II-strictly conserved loop that precedes the active site is critical for stabilizing the protein structure. So far, this represents the first communication of a Grx containing an intrinsically disordered region that defines a new protein subgroup within class II Grx.

The serine-threonine checkpoint kinase 1 (Chk1) plays a critical role in the cell cycle arrest in response to DNA damage. In the last decade, Chk1 inhibitors have emerged as a novel therapeutic strategy to potentiate the anti-tumour efficacy of cytotoxic chemotherapeutic agents. In the search for new Chk1 inhibitors, a congeneric series of 2-aryl-2 H-pyrazolo[4,3-c]quinolin-3-one (PQ) was evaluated by in-vitro and in-silico approaches for the first time. A total of 30 PQ structures were synthesised in good to excellent yields using conventional or microwave heating, highlighting that 14 of them are new chemical entities. Noteworthy, in this preliminary study two compounds 4e2 and 4h2 have shown a modest but significant reduction in the basal activity of the Chk1 kinase. Starting from these preliminary results, we have designed the second generation of analogous in this class and further studies are in progress in our laboratories.

Fragment-Based Drug Discovery (FBDD) has become, in recent years, a consolidated approach in the drug discovery process, leading to several drug candidates under investigation in clinical trials and some approved drugs. Among these successful applications of the FBDD approach, kinases represent a class of targets where this strategy has demonstrated its real potential with the approved kinase inhibitor Vemurafenib. In the Kinase family, protein kinase CK1 isoform δ (CK1δ) has become a promising target in the treatment of different neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis. In the present work, we set up and applied a computational workflow for the identification of putative fragment binders in large virtual databases. To validate the method, the selected compounds were tested in vitro to assess the CK1δ inhibition.

The mammalian protein prestin is expressed in the lateral membrane wall of the cochlear hair outer cells and is responsible for the electromotile response of the basolateral membrane, following hyperpolarisation or depolarisation of the cells. Its impairment marks the onset of severe diseases, like non-syndromic deafness. Several studies have pointed out possible key roles of residues located in the Transmembrane Domain (TMD) that differentiate mammalian prestins as incomplete transporters from the other proteins belonging to the same solute-carrier (SLC) superfamily, which are classified as complete transporters. Here, we exploit the homology of a prototypical incomplete transporter (rat prestin, rPres) and a complete transporter (zebrafish prestin, zPres) with target structures in the outward open and inward open conformations. The resulting models are then embedded in a model membrane and investigated via a rigorous molecular dynamics simulation protocol. The resulting trajectories are analyzed to obtain quantitative descriptors of the equilibration phase and to assess a structural comparison between proteins in different states, and between different proteins in the same state. Our study clearly identifies a network of key residues at the interface between the gate and the core domains of prestin that might be responsible for the conformational change observed in complete transporters and hindered in incomplete transporters. In addition, we study the pathway of Cl− ions in the presence of an applied electric field towards their putative binding site in the gate domain. Based on our simulations, we propose a tilt and shift mechanism of the helices surrounding the ion binding cavity as the working principle of the reported conformational changes in complete transporters.

New 7-amino-2-phenylpyrazolo[4,3-d]pyrimidine derivatives, substituted at the 5-position with aryl(alkyl)amino- and 4-substituted-piperazin-1-yl- moieties, were synthesized with the aim of targeting human (h) adenosine A1 and/or A2A receptor subtypes. On the whole, the novel derivatives 1–24 shared scarce or no affinities for the off-target hA2B and hA3 ARs. The 5-(4-hydroxyphenethylamino)- derivative 12 showed both good affinity (Ki = 150 nM) and the best selectivity for the hA2A AR while the 5-benzylamino-substituted 5 displayed the best combined hA2A (Ki = 123 nM) and A1 AR affinity (Ki = 25 nM). The 5-phenethylamino moiety (compound 6) achieved nanomolar affinity (Ki = 11 nM) and good selectivity for the hA1 AR. The 5-(N4-substituted-piperazin-1-yl) derivatives 15–24 bind the hA1 AR subtype with affinities falling in the high nanomolar range. A structure-based molecular modeling study was conducted to rationalize the experimental binding data from a molecular point of view using both molecular docking studies and Interaction Energy Fingerprints (IEFs) analysis.

Fragment-Based Drug Discovery (FBDD) approaches have gained popularity not only in industry but also in academic research institutes. However, the computational prediction of the binding mode adopted by fragment-like molecules within a protein binding site is still a very challenging task. One of the most crucial aspects of fragment binding is related to the large amounts of bound waters in the targeted binding pocket. The binding affinity of fragments may not be sufficient to displace the bound water molecules. In the present work, we confirmed the importance of the bound water molecules in the correct prediction of the fragment binding mode. Moreover, we investigate whether the use of methods based on explicit solvent molecular dynamics simulations can improve the accuracy of fragment posing. The protein chosen for this study is HSP-90.

Adenosine receptors (ARs), like many otherGprotein-coupledreceptors (GPCRs), are targets of primary interest indrug design. However, one of the main limits for the development of drugs for this class of GPCRs is the complex selectivity profile usually displayed by ligands. Numerous efforts have been madefor clarifying the selectivity of ARs, leading to the development of many ligand-based models. The structure of the AR subtype A1 (A1AR) has been recently solved, providing important structural insights. In the present work, we rationalized the selectivity profile of two selective A1AR and A2AAR antagonists, investigating their recognition trajectories obtained by Supervised Molecular Dynamics from an unbound state and monitoring the role of the water molecules in the binding site.

While a plethora of different protein–ligand docking protocols have been developed over the past twenty years, their performances greatly depend on the provided input protein–ligand pair. In this study, we developed a machine-learning model that uses a combination of convolutional and fully connected neural networks for the task of predicting the performance of several popular docking protocols given a protein structure and a small compound. We also rigorously evaluated the performance of our model using a widely available database of protein–ligand complexes and different types of data splits. We further open-source all code related to this study so that potential users can make informed selections on which protocol is best suited for their particular protein–ligand pair.

Virtual screening (VS) is a computational methodology that streamlines the drug discovery process by reducing costs and required resources through the in silico identification of potential drug candidates. Structure-based VS (SBVS) exploits knowledge about the three-dimensional (3D) structure of protein targets and uses the docking methodology as search engine for novel hits. The success of a SBVS campaign strongly depends upon the accuracy of the docking protocol used to select the candidates from large chemical libraries. The identification of suitable protocols is therefore a crucial step in the setup of SBVS experiments. Carrying out extensive benchmark studies, however, is usually a tangled task that requires users’ proficiency in handling different file formats and philosophies at the basis of the plethora of existing software packages. We present here DockBench 1.0, a platform available free of charge that eases the pipeline by automating the entire procedure, from docking benchmark to VS setups. In its current implementation, DockBench 1.0 handles seven docking software packages and offers the possibility to test up to seventeen different protocols. The main features of our platform are presented here and the results of the benchmark study of human Checkpoint kinase 1 (hChk1) are discussed as validation test.

The use and misuse of antibiotics has resulted in critical conditions for drug-resistant bacteria emergency, accelerating the development of antimicrobial resistance (AMR). In this context, the co-administration of an antibiotic with a compound able to restore sufficient antibacterial activity may be a successful strategy. In particular, the identification of efflux pump inhibitors (EPIs) holds promise for new antibiotic resistance breakers (ARBs). Indeed, bacterial efflux pumps have a key role in AMR development; for instance, NorA efflux pump contributes to Staphylococcus aureus (S. aureus) resistance against fluoroquinolone antibiotics (e.g., ciprofloxacin) by promoting their active extrusion from the cells. Even though NorA efflux pump is known to be a potential target for EPIs development, the absence of structural information about this protein and the little knowledge available on its mechanism of action have strongly hampered rational drug discovery efforts in this area. In the present work, we investigated at the molecular level the substrate recognition pathway of NorA through a Supervised Molecular Dynamics (SuMD) approach, using a NorA homology model. Specific amino acids were identified as playing a key role in the efflux pump-mediated extrusion of its substrate, paving the way for a deeper understanding of both the mechanisms of action and the inhibition of such efflux pumps.

One of the most intriguing findings highlighted from G protein-coupled receptor (GPCR) crystallography is the presence, in many members of class A, of a partially hydrated sodium ion in the middle of the seven transmembrane helices (7TM) bundle. In particular, the human adenosine A2A receptor (A2A AR) is the first GPCR in which a monovalent sodium ion was crystallized in a distal site from the canonical orthosteric one, corroborating, from a structural point of view, its role as a negative allosteric modulator. However, the molecular mechanism by which the sodium ion influences the recognition of the A2A AR agonists is not yet fully understood. In this study, the supervised molecular dynamics (SuMD) technique was exploited to analyse the sodium ion recognition mechanism and how its presence influences the binding of the endogenous agonist adenosine. Due to a higher degree of flexibility of the receptor extracellular (EC) vestibule, we propose the sodium-bound A2A AR as less efficient in stabilizing the adenosine during the different steps of binding.

The number of entries in the Protein Data Bank (PDB) has doubled in the last decade, and it has increased tenfold in the last twenty years. The availability of an ever-growing number of structures is having a huge impact on the Structure-Based Drug Discovery (SBDD), allowing investigation of new targets and giving the possibility to have multiple structures of the same macromolecule in a complex with different ligands. Such a large resource often implies the choice of the most suitable complex for molecular docking calculation, and this task is complicated by the plethora of possible posing and scoring function algorithms available, which may influence the quality of the outcomes. Here, we report a large benchmark performed on the PDBbind database containing more than four thousand entries and seventeen popular docking protocols. We found that, even in protein families wherein docking protocols generally showed acceptable results, certain ligand-protein complexes are poorly reproduced in the self-docking procedure. Such a trend in certain protein families is more pronounced, and this underlines the importance in identification of a suitable protein−ligand conformation coupled to a well-performing docking protocol.

A new series of pyrazolo[4,3-e][1,2,4]triazolo[1,5-c]pyrimidine (PTP) derivatives has been developed in order to explore their affinity and selectivity profile at the four adenosine receptor subtypes. In particular, the PTP scaffold was conjugated at the C2 position with the 1-(3-trifluoromethyl-benzyl)-1H-pyrazole, a group believed to confer potency and selectivity toward the human (h) A2B adenosine receptor (AR) to the xanthine ligand 8-(1-(3-(trifluoromethyl)benzyl)-1H-pyrazol-4-yl)-1,3-dimethyl-1H-purine-2,6(3H,7H)-dione (CVT 6975). Interestingly, the synthesized compounds turned out to be inactive at the hA2B AR but they displayed affinity at the hA3 AR in the nanomolar range. The best compound of the series (6) shows both high affinity (hA3 AR Ki = 11 nM) and selectivity (A1/A3 and A2A/A3 > 9090; A2B/A3 > 909) at the hA3 AR. To better rationalize these results, a molecular docking study on the four AR subtypes was performed for all the synthesized compounds. In addition, CTV 6975 and two close analogues have been subjected to the same molecular docking protocol to investigate the role of the 1-(3-trifluoromethyl-benzyl)-1H-pyrazole on the binding at the four ARs.