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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.

Fragment-based lead discovery has emerged as one of the most efficient screening strategies for finding hit molecules in drug discovery. Recently, a novel strategy based on a class of fragments characterized by an ultralow molecular weight (ULMW) has been proposed. These fragments bind to the target with a very low affinity, requiring reliable biophysical methods for detection. The most notable application of ULMW used a set of 81 fragments, named MiniFrags, and screened them by X-ray crystallography. We extended the utilization of this novel class of fragments to another gold standard technique for fragment-based screening: nuclear magnetic resonance (NMR). Here, we present a novel NMR protocol to detect and analyze such weak interactions in a challenging real-world scenario: a flexible target with a flat, water-exposed binding site. We identified a subset of 69 highly water-soluble MiniFrags that were screened against the antiapoptotic protein human Bfl-1.

Epitranscriptomic mRNA modifications affect gene expression, with their altered balance detected in various cancers. YTHDF proteins contain the YTH reader domain recognizing the m 6 A mark on mRNA and represent valuable drug targets. Crystallographic structures have been determined for all three family members; however, discrepancies are present in the organization of the m 6 A-binding pocket. Here, we present new crystallographic structures of the YTH domain of YTHDF1, accompanied by computational studies, showing that this domain can exist in different stable conformations separated by a significant energetic barrier. During the transition, additional conformations are explored, with peculiar druggable pockets appearing and offering new opportunities for the design of YTH-interfering small molecules.

The Bcl-2-associated athanogene 3 (BAG3) protein plays multiple roles in controlling cellular homeostasis, and it has been reported to be deregulated in many cancers, leading tumor cell apoptosis escape. BAG3 protein is then an emerging target for its oncogenic activities in both leukemia and solid cancers, such as medulloblastoma. In this work a series of forty-four compounds were designed and successfully synthesized by the modification and optimization of a previously reported 2,4-thiazolidinedione derivative 28. Using an efficient cloning and transfection in human embryonic kidney HEK-293T cells, BAG3 was collected and purified by chromatographic techniques such as IMAC and SEC, respectively. Subsequently, through Surface Plasmon Resonance (SPR) all the compounds were evaluated for their binding ability to BAG3, highlighting the compound FB49 as the one having the greatest affinity for the protein (K d  = 45 ± 6 μM) also against the reference compound 28. Further analysis carried out by Saturation Transfer Difference (STD) Nuclear Magnetic Resonance (NMR) spectroscopy further confirmed the highest affinity of FB49 for the protein. In vitro biological investigation showed that compound FB49 is endowed with an antiproliferative activity in the micromolar range in three human tumoral cell lines and more importantly is devoid of toxicity in human peripheral mononuclear cell deriving from healthy donors. Moreover, FB49 was able to block cell cycle in G1 phase and to induce apoptosis as well as autophagy in medulloblastoma HD-MB03 treated cells. In addition, FB49 demonstrated a synergistic effect when combined with a chemotherapy cocktail of Vincristine, Etoposide, Cisplatin, Cyclophosphamide (VECC). In conclusion we have demonstrated that FB49 is a new derivative able to bind human BAG3 with high affinity and could be used as BAG3 modulator in cancers correlated with overexpression of this protein., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Masson SAS.. All rights reserved.)

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Dodaro, Pavan, Menin, Salmaso, Sturlese and Moro.)

Human papillomavirus (HPV)-induced cancers still represent a major health issue for worldwide population and lack specific therapeutic regimens. Despite substantial advancements in anti-HPV vaccination, the incidence of HPV-related cancers remains high, thus there is an urgent need for specific anti-HPV drugs. The HPV E7 oncoprotein is a major driver of carcinogenesis that acts by inducing the degradation of several host factors. A target is represented by the cellular phosphatase PTPN14 and its E7-mediated degradation was shown to be crucial in HPV oncogenesis. Here, by exploiting the crystal structure of E7 bound to PTPN14, we performed an in silico screening of small-molecule compounds targeting the C-terminal CR3 domain of E7 involved in the interaction with PTPN14. We discovered a compound able to inhibit the E7/PTPN14 interaction in vitro and to rescue PTPN14 levels in cells, leading to a reduction in viability, proliferation, migration, and cancer-stem cell potential of HPV-positive cervical cancer cells. Mechanistically, as a consequence of PTPN14 rescue, treatment of cancer cells with this compound altered the Yes-associated protein (YAP) nuclear-cytoplasmic shuttling and downstream signaling. Notably, this compound was active against cervical cancer cells transformed by different high-risk (HR)-HPV genotypes indicating a potential broad-spectrum activity. Overall, our study reports the first-in-class inhibitor of E7/PTPN14 interaction and provides the proof-of-principle that pharmacological inhibition of this interaction by small-molecule compounds could be a feasible therapeutic strategy for the development of novel antitumoral drugs specific for HPV-associated cancers., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

The superbug Staphylococcus aureus ( S. aureus ) exhibits several resistance mechanisms, including efflux pumps, that strongly contribute to antimicrobial resistance. In particular, the NorA efflux pump activity is associated with S. aureus resistance to fluoroquinolone antibiotics ( e.g ., ciprofloxacin) by promoting their active extrusion from cells. Thus, since efflux pump inhibitors (EPIs) are able to increase antibiotic concentrations in bacteria as well as restore their susceptibility to these agents, they represent a promising strategy to counteract bacterial resistance. Additionally, the very recent release of two NorA efflux pump cryo-electron microscopy (cryo-EM) structures in complex with synthetic antigen-binding fragments (Fabs) represents a real breakthrough in the study of S. aureus antibiotic resistance. In this scenario, supervised molecular dynamics (SuMD) and molecular docking experiments were combined to investigate for the first time the molecular mechanisms driving the interaction between NorA and efflux pump inhibitors (EPIs), with the ultimate goal of elucidating how the NorA efflux pump recognizes its inhibitors. The findings provide insights into the dynamic NorA-EPI intermolecular interactions and lay the groundwork for future drug discovery efforts aimed at the identification of novel molecules to fight antimicrobial resistance.

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.

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., Competing Interests: The authors declare no conflict of interest.

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.

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.

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, M pro ) 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.

Ribonucleic acid (RNA) plays a key regulatory role within the cell, cooperating with proteins to control the genome expression and several biological processes. Due to its characteristic structural features, this polymer can mold itself into different three-dimensional structures able to recognize target biomolecules with high affinity and specificity, thereby attracting the interest of drug developers and medicinal chemists. One successful example of the exploitation of RNA's structural and functional peculiarities is represented by aptamers, a class of therapeutic and diagnostic tools that can recognize and tightly bind several pharmaceutically relevant targets, ranging from small molecules to proteins, making use of the available structural and conformational freedom to maximize the complementarity with their interacting counterparts. In this scientific work, we present the first application of Supervised Molecular Dynamics (SuMD), an enhanced sampling Molecular Dynamics-based method for the study of receptor-ligand association processes in the nanoseconds timescale, to the study of recognition pathways between RNA aptamers and proteins, elucidating the main advantages and limitations of the technique while discussing its possible role in the rational design of RNA-based therapeutics., (© The Author(s) 2022. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.)

The prediction of ligand efficacy has long been linked to thermodynamic properties such as the equilibrium dissociation constant, which considers both the association and the dissociation rates of a defined protein-ligand complex. In the last 15 years, there has been a paradigm shift, with an increased interest in the determination of kinetic properties such as the drug-target residence time since they better correlate with ligand efficacy compared to other parameters. In this article, we present thermal titration molecular dynamics (TTMD), an alternative computational method that combines a series of molecular dynamics simulations performed at progressively increasing temperatures with a scoring function based on protein-ligand interaction fingerprints for the qualitative estimation of protein-ligand-binding stability. The protocol has been applied to four different pharmaceutically relevant test cases, including protein kinase CK1δ, protein kinase CK2, pyruvate dehydrogenase kinase 2, and SARS-CoV-2 main protease, on a variety of ligands with different sizes, structures, and experimentally determined affinity values. In all four cases, TTMD was successfully able to distinguish between high-affinity compounds (low nanomolar range) and low-affinity ones (micromolar), proving to be a useful screening tool for the prioritization of compounds in a drug discovery campaign.

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Cozzaglio, Ceschi, Groaz, Sturlese and Sissi.)

The mitochondrial respiratory chain (MRC) is composed of four multiheteromeric enzyme complexes. According to the endosymbiotic origin of mitochondria, eukaryotic MRC derives from ancestral proteobacterial respiratory structures consisting of a minimal set of complexes formed by a few subunits associated with redox prosthetic groups. These enzymes, which are the "core" redox centers of respiration, acquired additional subunits, and increased their complexity throughout evolution. Cytochrome c oxidase (COX), the terminal component of MRC, has a highly interspecific heterogeneous composition. Mammalian COX consists of 14 different polypeptides, of which COX7B is considered the evolutionarily youngest subunit. We applied proteomic, biochemical, and genetic approaches to investigate the COX composition in the invertebrate model Drosophila melanogaster. We identified and characterized a novel subunit which is widely different in amino acid sequence, but similar in secondary and tertiary structures to COX7B, and provided evidence that this object is in fact replacing the latter subunit in virtually all protostome invertebrates. These results demonstrate that although individual structures may differ the composition of COX is functionally conserved between vertebrate and invertebrate species., (© 2022 The Authors. Published under the terms of the CC BY NC ND 4.0 license.)

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Pavan, Menin, Bassani, Sturlese and Moro.)

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.

The SARS-CoV-2 main protease (M pro ) has a pivotal role in mediating viral genome replication and transcription of the coronavirus, making it a promising target for drugs against the COVID-19 pandemic. Here, a crystal structure is presented in which M pro adopts an inactive state that has never been observed before, called new-inactive. It is shown that the oxyanion loop, which is involved in substrate recognition and enzymatic activity, adopts a new catalytically incompetent conformation and that many of the key interactions of the active conformation of the enzyme around the active site are lost. Solvation/desolvation energetic contributions play an important role in the transition from the inactive to the active state, with Phe140 moving from an exposed to a buried environment and Asn142 moving from a buried environment to an exposed environment. In new-inactive M pro a new cavity is present near the S2' subsite, and the N-terminal and C-terminal tails, as well as the dimeric interface, are perturbed, with partial destabilization of the dimeric assembly. This novel conformation is relevant both for comprehension of the mechanism of action of M pro within the catalytic cycle and for the successful structure-based drug design of antiviral drugs., (open access.)

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 A 2A 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.

We report a fast-track computationally driven discovery of new SARS-CoV-2 main protease (M pro ) inhibitors whose potency ranges from mM for the initial non-covalent ligands to sub-μM for the final covalent compound (IC 50 = 830 ± 50 nM). The project extensively relied on high-resolution all-atom molecular dynamics simulations and absolute binding free energy calculations performed using the polarizable AMOEBA force field. The study is complemented by extensive adaptive sampling simulations that are used to rationalize the different ligand binding poses through the explicit reconstruction of the ligand-protein conformation space. Machine learning predictions are also performed to predict selected compound properties. While simulations extensively use high performance computing to strongly reduce the time-to-solution, they were systematically coupled to nuclear magnetic resonance experiments to drive synthesis and for in vitro characterization of compounds. Such a study highlights the power of in silico strategies that rely on structure-based approaches for drug design and allows the protein conformational multiplicity problem to be addressed. The proposed fluorinated tetrahydroquinolines open routes for further optimization of M pro inhibitors towards low nM affinities., Competing Interests: P. R., M. M., L. L., J. W. P. and J.-P. P. are co-founders and shareholders of Qubit Pharmaceuticals., (This journal is © The Royal Society of Chemistry.)

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 (M pro ). 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.

Increasing application of computational approaches in these last decades has deeply modified the process of discovery and commercialization of new therapeutic entities. This is especially true in the field of neuroinflammation, in which both the peculiar anatomical localization and the presence of the blood-brain barrier make it mandatory to finely tune the candidates' physicochemical properties from the early stages of the discovery pipeline. The aim of this review is, therefore, to provide a general overview of neuroinflammation to the readers, together with the most common computational strategies that can be exploited to discover and design small molecules controlling neuroinflammation, especially those based on the knowledge of the three-dimensional structure of the biological targets of therapeutic interest. The techniques used to describe the molecular recognition mechanisms, such as molecular docking and molecular dynamics, will therefore be discussed, highlighting their advantages and limitations. Finally, we report several case studies in which computational methods have been applied to drug discovery for neuroinflammation, focusing on the research conducted in the last decade., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

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-X L , 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-X L binders. This represents, to date, the largest computational fragments screening entirely based on MD.

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 (M pro ). 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.

A novel class of potential MAO-B inhibitors was designed and synthesized in good yield by combining the pyridazinone moiety with the dithiocarbamate framework, two relevant pharmacophores for drug discovery. The biological results obtained for the different pyridazinone/dithiocarbamate hybrids (compounds 8-14) indicated that most of them reversibly and selectively inhibit the hMAO-B in vitro with IC 50 values in the µM range and exhibit not significant cellular toxicity. The analogues 9a 1 , 11a 1 , 12a 2 , 12b 1 and 12b 2 , which present the dithiocarbamate fragment derivatized with a piperidin-1-yl or pyrrolidin-1-yl group and placed at C3 or C4 of the diazine ring, were the most attractive compounds of these series. Molecular modeling studies were performed to analyze the binding mode to the enzyme and the structure activity relationships of the titled compounds, as well as to predict their drug-like properties., (Copyright © 2021 Elsevier Inc. All rights reserved.)

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.

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Hassankalhori, Bolcato, Bissaro, Sturlese and Moro.)

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.

Computational approaches supporting the early characterization of fragment molecular recognition mechanism represent a valuable complement to more expansive and low-throughput experimental techniques. In this retrospective study, we have investigated the geometric accuracy with which high-throughput supervised molecular dynamics simulations (HT-SuMD) can anticipate the experimental bound state for a set of 23 fragments targeting the SARS-CoV-2 main protease. Despite the encouraging results herein reported, in line with those previously described for other MD-based posing approaches, a high number of incorrect binding modes still complicate HT-SuMD routine application. To overcome this limitation, fragment pose stability has been investigated and integrated as part of our in-silico pipeline, allowing us to prioritize only the more reliable predictions., (© 2021 The Authors. ChemMedChem published by Wiley-VCH GmbH.)

Background: The neuronal apoptotic process requires the nuclear translocation of Apoptosis Inducing Factor (AIF) in complex with Cyclophilin A (CypA) with consequent chromatin condensation and DNA degradation events. Targeting CypA by delivering an AIF-blocking peptide (AIF(370-394)) provides a significant neuroprotection, demonstrating the biological relevance of the AIF/CypA complex. To date pharmaceutical compounds targeting this complex are missing., Methods: We designed and synthesized a set of mono and bicyclic AIF(370-394) analogs containing both disulfide and 1,2,3-triazole bridges, in the attempt to both stabilize the peptide conformation and improve its binding affinity to CypA. Peptide structures in solution and in complex with CypA have been studied by circular dichroism (CD), Nuclear Magnetic Resonance (NMR) and molecular modeling. The ability of stapled peptides to interact with CypA was evaluated by using Epic Corning label free technique and Isothermal Titration Calorimetry experiments., Results: We identified a stapled peptide analogue of AIF(370-394) with a ten-fold improved affinity for CypA. Molecular modeling studies reveal that the new peptide acquires β-turn/β-fold structures and shares with the parent molecule the same binding region on CypA., Conclusions: Data obtained provide invaluable assistance in designing new ligand of CypA for therapeutic approaches in neurodegenerative diseases., General Significance: Due to the crucial role of AIF/CypA complex formation in neurodegeneration, identification of selective inhibitors is of high importance for targeted therapies. We describe new bicyclic peptide inhibitors with improved affinity for CypA, investigating the kinetic, thermodynamic and structural effects of conformational constraints on the protein-ligand interaction, and their utility for drug design., Competing Interests: Declaration of Competing Interest Authors declare no conflict of interest., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Coronavirus SARS-CoV-2 is a recently discovered single-stranded RNA betacoronavirus, responsible for a severe respiratory disease known as coronavirus disease 2019, which is rapidly spreading. Chinese health authorities, as a response to the lack of an effective therapeutic strategy, started to investigate the use of lopinavir and ritonavir, previously optimized for the treatment and prevention of HIV/AIDS viral infection. Despite the clinical use of these two drugs, no information regarding their possible mechanism of action at the molecular level is still known for SARS-CoV-2. Very recently, the crystallographic structure of the SARS-CoV-2 main protease (M pro ), also known as C30 Endopeptidase, was published. Starting from this essential structural information, in the present work we have exploited supervised molecular dynamics, an emerging computational technique that allows investigating at an atomic level the recognition process of a ligand from its unbound to the final bound state. In this research, we provided molecular insight on the whole recognition pathway of Lopinavir, Ritonavir, and Nelfinavir, three potential C30 Endopeptidase inhibitors, with the last one taken into consideration due to the promising in-vitro activity shown against the structurally related SARS-CoV protease.

The 3-pyridazinylcoumarin scaffold was previously reported as an efficient core for the discovery of reversible and selective inhibitors of MAO-B, a validated drug target for PD therapy which also plays an important role in the AD progress. Looking for its structural optimization, novel compounds of hybrid structure coumarin-pyridazine, differing in polarizability and lipophilicity properties, were synthesized and tested against the two MAO isoforms, MAO-A and MAO-B (compounds 17a-f and 18a-f). All the designed compounds selectively inhibited the MAO-B isoenzyme, exhibiting many of them IC 50 values ranging from sub-micromolar to nanomolar grade and lacking neuronal toxicity. The 7-bromo-3-(6-bromopyridazin-3-yl)coumarin (18c), the most potent compound of these series (IC 50  = 60 nM), was subjected to further in vivo studies in a reserpine-induced mouse PD model. The obtained results suggest a promising potential for 18c as antiparkinsonian agent. Molecular modeling studies also provided valuable information about the enzyme-drug interactions and the potential pharmacokinetic profile of the novel compounds., (Copyright © 2020 Elsevier Inc. All rights reserved.)

The A 3 adenosine receptor (AR) is a G protein-coupled receptor (GPCR) overexpressed in the membrane of specific cancer cells. Thus, the development of nanosystems targeting this receptor could be a strategy to both treat and diagnose cancer. Iron-filled carbon nanotubes (CNTs) are an optimal platform for theranostic purposes, and the use of a magnetic field can be exploited for cancer magnetic cell sorting and thermal therapy. In this work, we have conjugated an A 3 AR ligand on the surface of iron-filled CNTs with the aim of targeting cells overexpressing A 3 ARs. In particular, two conjugates bearing PEG linkers of different length were designed. A docking analysis of A 3 AR showed that neither CNT nor linker interferes with ligand binding to the receptor; this was confirmed by in vitro preliminary radioligand competition assays on A 3 AR. Encouraged by this result, magnetic cell sorting was applied to a mixture of cells overexpressing or not the A 3 AR in which our compound displayed indiscriminate binding to all cells. Despite this, it is the first time that a GPCR ligand has been anchored to a magnetic nanosystem, thus it opens the door to new applications for cancer treatment., (© 2020 Wiley-VCH GmbH.)

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.

Fragment-based drug discovery (FBDD) is an innovative approach, progressively more applied in the academic and industrial context, to enhance hit identification for previously considered undruggable biological targets. In particular, FBDD discovers low-molecular-weight (LMW) ligands (<300Da) able to bind to therapeutically relevant macromolecules in an affinity range from the micromolar (μM) to millimolar (mM). X-ray crystallography (XRC) and nuclear magnetic resonance (NMR) spectroscopy are commonly the methods of choice to obtain 3D information about the bound ligand-protein complex, but this can occasionally be problematic, mainly for early, low-affinity fragments. The recent development of computational fragment-based approaches provides a further strategy for improving the identification of fragment hits. In this review, we summarize the state of the art of molecular dynamics simulations approaches used in FBDD, and discuss limitations and future perspectives for these approaches., (Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

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.

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 A 1 (A 1 AR) has been recently solved,providing important structural insights. In the present work, we rationalized the selectivity profile of two selective A 1 AR and A 2A AR 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., Competing Interests: The authors declare no conflict of interest.

Recent studies have highlighted the key role of Casein kinase 1 δ (CK1δ) in the development of several neurodegenerative pathologies, such as Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS). So far, CK1δ inhibitors are noncovalent ATP competitive ligands and no drugs are currently available for this molecular target, hence the interest in developing new CK1δ inhibitors. The study aims to identify new inhibitors able to bind the enzyme; by a dual approach in silico/in vitro, the virtual screening has been performed on an in-house chemical library, which was previously designed and synthesized for other targets. The work can, therefore, be seen in the scaffold repurposing logic. The proposed strategy has led to the identification of two hits, having a novel scaffold in the landscape of CK1δ inhibitors and with an activity in the micromolar range., Competing Interests: The authors declare no competing financial interest., (Copyright © 2020 American Chemical Society.)

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., (Copyright © 2020 Bissaro, Sturlese and Moro.)

Mitochondrial Ca 2+ 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 Ca 2+ uptake. Two of them, named MCU-i4 and MCU-i11, are confirmed to reliably decrease mitochondrial Ca 2+ 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 Ca 2+ 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 Ca 2+ uptake in muscle growth. Overall, MCU-i4 and MCU-i11 represent leading molecules for the development of MICU1-targeting drugs., Competing Interests: Declaration of Interests B.J., C.B., V.T.-E., D.H., B.O., S.S., G.M., and M.F. are employees of Novartis Pharma AG, and some are also shareholders of Novartis., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

A small number of fluorinated 7-phenyl-pyrroloquinolinone (7-PPyQ) derivatives was synthesized in an attempt to improve the metabolic stability of 3N-ethyl-7-PPyQ and 3N-benzoyl-7-PPyQ. The possible impacts of the fluorine-hydrogen isosterism on both biological activity and metabolic stability were evaluated. Introduction of a fluorine atom in the 2 or 3 position of the 7-phenyl ring yielded the 7-PPyQ derivatives 12, 13 and 15, which showed potent cytotoxicity (low micromolar and sub-nanomolar GI 50 s) both in human leukemic and solid tumor cell lines. None of them induced significant cell death in quiescent and proliferating human lymphocytes. Moreover, 12, 13 and 15 exhibited remarkable cytotoxic activity in the multidrug-resistant cell line CEM Vbl100 , suggesting that they are not substrates for P-glycoprotein. All compounds inhibited tubulin assembly and the binding of [ 3 H]colchicine to tubulin, with the best activity occurring with compound 15. Mechanistic studies carried out on compound 12 indicated that it caused (a) a strong G2/M arrest; (b) apoptosis in a time- and concentration-dependent manner; (c) a significant production of ROS (in good agreement with the observed mitochondrial depolarization); (d) caspase-3 and poly (ADP-ribose) polymerase activation; and (e) a decrease in the expression of anti-apoptotic proteins. In vivo experiments in a murine syngeneic tumor model demonstrated that compounds 12 and 15 significantly reduced tumor mass at doses four times lower than that required for the reference compound combretastatin A-4 phosphate. Neither monofluorination of the 7-phenyl ring of 3N-ethyl-7-PPyQ nor replacement of the benzoyl function of 3N-benzoyl-7-PPyQ with a 2-fluorobenzoyl moiety led to any improvement in the metabolic stability., (Copyright © 2019 Elsevier Masson SAS. All rights reserved.)

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.