Search

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.)