A chemical modification of a peroxisome proliferator-activated receptor pan agonist produced a shift to a new dual alpha/gamma partial agonist endowed with mitochondrial pyruvate carrier inhibition and antidiabetic properties.

New analogs of the PPAR pan agonist AL29-26 encompassed ligand (S)-7 showing potent activation of PPARα and -γ subtypes as a partial agonist. In vitro experiments and docking studies in the presence of PPAR antagonists were performed to help interpretation of biological data and investigate the main interactions at the binding sites. Further in vitro experiments showed that (S)-7 induced anti-steatotic effects and enhancement of the glucose uptake. This latter effect could be partially ascribed to a significant inhibition of the mitochondrial pyruvate carrier demonstrating that (S)-7 also acted through insulin-independent mechanisms. In vivo experiments showed that this compound reduced blood glucose and lipid levels in a diabetic mice model displaying no toxicity on bone, kidney, and liver. To our knowledge, this is the first example of dual PPARα/γ partial agonist showing these combined effects representing, therefore, the potential lead of new drugs for treatment of dyslipidemic type 2 diabetes.

Synthesis and in vitro cytotoxicity of benzoxazole-based PPARα/γ antagonists in colorectal cancer cell lines.

A series of benzoxazole-based amides and sulfonamides were synthesized and evaluated for their human peroxisome proliferator-activated receptor (PPAR)α and PPARγ activity. All tested compounds showed a dual antagonist profile on both PPAR subtypes; based on transactivation results, seven compounds were selected to test their in vitro antiproliferative activity in a panel of eight cancer cell lines with different expression rates of PPARα and PPARγ. 3f was identified as the most cytotoxic compound, with higher potency in the colorectal cancer cell lines HT-29 and HCT116. Compound 3f induced a concentration-dependent activation of caspases and cell-cycle arrest in both colorectal cancer models. Docking experiments were also performed to shed light on the putative binding mode of this novel class of dual PPARα/γ antagonists.

"DompeKeys": a set of novel substructure-based descriptors for efficient chemical space mapping, development and structural interpretation of machine learning models, and indexing of large databases.

The conversion of chemical structures into computer-readable descriptors, able to capture key structural aspects, is of pivotal importance in the field of cheminformatics and computer-aided drug design. Molecular fingerprints represent a widely employed class of descriptors; however, their generation process is time-consuming for large databases and is susceptible to bias. Therefore, descriptors able to accurately detect predefined structural fragments and devoid of lengthy generation procedures would be highly desirable. To meet additional needs, such descriptors should also be interpretable by medicinal chemists, and suitable for indexing databases with trillions of compounds. To this end, we developed-as integral part of EXSCALATE, Dompé's end-to-end drug discovery platform-the DompeKeys (DK), a new substructure-based descriptor set, which encodes the chemical features that characterize compounds of pharmaceutical interest. DK represent an exhaustive collection of curated SMARTS strings, defining chemical features at different levels of complexity, from specific functional groups and structural patterns to simpler pharmacophoric points, corresponding to a network of hierarchically interconnected substructures. Because of their extended and hierarchical structure, DK can be used, with good performance, in different kinds of applications. In particular, we demonstrate how they are very well suited for effective mapping of chemical space, as well as substructure search and virtual screening. Notably, the incorporation of DK yields highly performing machine learning models for the prediction of both compounds' activity and metabolic reaction occurrence. The protocol to generate the DK is freely available at https://dompekeys.exscalate.eu and is fully integrated with the Molecular Anatomy protocol for the generation and analysis of hierarchically interconnected molecular scaffolds and frameworks, thus providing a comprehensive and flexible tool for drug design applications.

Novel Reversible Inhibitors of Xanthine Oxidase Targeting the Active Site of the Enzyme.

Xanthine oxidase (XO) is a flavoprotein catalysing the oxidation of hypoxanthine to xanthine and then to uric acid, while simultaneously producing reactive oxygen species. Altered functions of XO may lead to severe pathological diseases, including gout-causing hyperuricemia and oxidative damage of tissues. These findings prompted research studies aimed at targeting the activity of this crucial enzyme. During the course of a virtual screening study aimed at the discovery of novel inhibitors targeting another oxidoreductase, superoxide dismutase, we identified four compounds with non-purine-like structures, namely ALS-1, -8, -15 and -28, that were capable of causing direct inhibition of XO. The kinetic studies of their inhibition mechanism allowed a definition of these compounds as competitive inhibitors of XO. The most potent molecule was ALS-28 (Ki 2.7 ± 1.5 µM), followed by ALS-8 (Ki 4.5 ± 1.5 µM) and by the less potent ALS-15 (Ki 23 ± 9 µM) and ALS-1 (Ki 41 ± 14 µM). Docking studies shed light on the molecular basis of the inhibitory activity of ALS-28, which hinders the enzyme cavity channel for substrate entry consistently with the competitive mechanism observed in kinetic studies. Moreover, the structural features emerging from the docked poses of ALS-8, -15 and -1 may explain the lower inhibition power with respect to ALS-28. All these structurally unrelated compounds represent valuable candidates for further elaboration into promising lead compounds.

Broad-spectrum coronavirus 3C-like protease peptidomimetic inhibitors effectively block SARS-CoV-2 replication in cells: Design, synthesis, biological evaluation, and X-ray structure determination.

Despite the approval of vaccines, monoclonal antibodies and restrictions during the pandemic, the demand for new efficacious and safe antivirals is compelling to boost the therapeutic arsenal against the COVID-19. The viral 3-chymotrypsin-like protease (3CLpro) is an essential enzyme for replication with high homology in the active site across CoVs and variants showing an almost unique specificity for Leu-Gln as P2-P1 residues, allowing the development of broad-spectrum inhibitors. The design, synthesis, biological activity, and cocrystal structural information of newly conceived peptidomimetic covalent reversible inhibitors are herein described. The inhibitors display an aldehyde warhead, a Gln mimetic at P1 and modified P2-P3 residues. Particularly, functionalized proline residues were inserted at P2 to stabilize the ß-turn like bioactive conformation, modulating the affinity. The most potent compounds displayed low/sub-nM potency against the 3CLpro of SARS-CoV-2 and MERS-CoV and inhibited viral replication of three human CoVs, i.e. SARS-CoV-2, MERS-CoV, and HCoV 229 in different cell lines. Particularly, derivative 12 exhibited nM-low µM antiviral activity depending on the virus, and the highest selectivity index. Some compounds were co-crystallized with SARS-CoV-2 3CLpro validating our design. Altogether, these results foster future work toward broad-spectrum 3CLpro inhibitors to challenge CoVs related pandemics.

New avenues in artificial-intelligence-assisted drug discovery.

Over the past decade, the amount of biomedical data available has grown at unprecedented rates. Increased automation technology and larger data volumes have encouraged the use of machine learning (ML) or artificial intelligence (AI) techniques for mining such data and extracting useful patterns. Because the identification of chemical entities with desired biological activity is a crucial task in drug discovery, AI technologies have the potential to accelerate this process and support decision making. In addition, the advent of deep learning (DL) has shown great promise in addressing diverse problems in drug discovery, such as de novo molecular design. Herein, we will appraise the current state-of-the-art in AI-assisted drug discovery, discussing the recent applications covering generative models for chemical structure generation, scoring functions to improve binding affinity and pose prediction, and molecular dynamics to assist in the parametrization, featurization and generalization tasks. Finally, we will discuss current hurdles and the strategies to overcome them, as well as potential future directions.

A New Antidiabetic Agent Showing Short- and Long-Term Effects Due to Peroxisome Proliferator-Activated Receptor Alpha/Gamma Dual Agonism and Mitochondrial Pyruvate Carrier Inhibition.

A new series of analogues or derivatives of the previously reported PPARα/γ dual agonist LT175 allowed the identification of ligand 10, which was able to potently activate both PPARα and -γ subtypes as full and partial agonists, respectively. Docking studies were performed to provide a molecular explanation for this different behavior on the two different targets. In vivo experiments showed that this compound induced a significant reduction in blood glucose and lipid levels in an STZ-induced diabetic mouse model displaying no toxic effects on bone, kidney, and liver. By examining in depth the antihyperglycemic activity of 10, we found out that it produced a slight but significant inhibition of the mitochondrial pyruvate carrier, acting also through insulin-independent mechanisms. This is the first example of a PPARα/γ dual agonist reported to show this inhibitory effect representing, therefore, the potential lead of a new class of drugs for treatment of dyslipidemic type 2 diabetes.

Easy access to α-ketoamides as SARS-CoV-2 and MERS Mpro inhibitors via the PADAM oxidation route.

SARS-CoV-2 caused worldwide the current outbreak called COVID-19. Despite multiple countermeasures implemented, there is an urgent global need for new potent and efficient antiviral drugs against this pathogen. In this context, the main protease (Mpro) of SARS-CoV-2 is an essential viral enzyme and plays a pivotal role in viral replication and transcription. Its specific cleavage of polypeptides after a glutamine residue has been considered as a key element to design novel antiviral drugs. Herein, we reported the design, synthesis and structure-activity relationships of novel α-ketoamides as covalent reversible inhibitors of Mpro, exploiting the PADAM oxidation route. The reported compounds showed µM to nM activities in enzymatic and in the antiviral cell-based assays against SARS-CoV-2 Mpro. In order to assess inhibitors' binding mode, two co-crystal structures of SARS-CoV-2 Mpro in complex with our inhibitors were solved, which confirmed the covalent binding of the keto amide moiety to the catalytic Cys145 residue of Mpro. Finally, in order to interrogate potential broad-spectrum properties, we assessed a selection of compounds against MERS Mpro where they showed nM inhibitory potency, thus highlighting their potential as broad-spectrum coronavirus inhibitors.

Impairment of Nucleolin Activity and Phosphorylation by a Trachylobane Diterpene from Psiadia punctulata in Cancer Cells.

Human nucleolin (hNcl) is a multifunctional protein involved in the progression of various cancers and plays a key role in other pathologies. Therefore, there is still unsatisfied demand for hNcl modulators. Recently, we demonstrated that the plant ent-kaurane diterpene oridonin inhibits hNcl but, unfortunately, this compound is quite toxic for healthy cells. Trachylobane diterpene 6,19-dihydroxy-ent-trachiloban-17-oic acid (compound 12) extracted from Psiadia punctulata (DC.) Vatke (Asteraceae) emerged as a ligand of hNcl from a cellular thermal shift assay (CETSA)-based screening of a small library of diterpenes. Effective interaction between this compound and the protein was demonstrated to occur both in vitro and inside two different types of cancer cells. Based on the experimental and computational data, a model of the hNcl/compound 12 complex was built. Because of this binding, hNcl mRNA chaperone activity was significantly reduced, and the level of phosphorylation of the protein was affected. At the biological level, cancer cell incubation with compound 12 produced a cell cycle block in the subG0/G1 phase and induced early apoptosis, whereas no cytotoxicity towards healthy cells was observed. Overall, these results suggested that 6,19-dihydroxy-ent-trachiloban-17-oic could represent a selective antitumoral agent and a promising lead for designing innovative hNcl inhibitors also usable for therapeutic purposes.

In Silico Identification of Novel Inhibitors Targeting the Homodimeric Interface of Superoxide Dismutase from the Dental Pathogen Streptococcus mutans.

The microaerophile Streptococcus mutans, the main microaerophile responsible for the development of dental plaque, has a single cambialistic superoxide dismutase (SmSOD) for its protection against reactive oxygen species. In order to discover novel inhibitors of SmSOD, possibly interfering with the biofilm formation by this pathogen, a virtual screening study was realised using the available 3D-structure of SmSOD. Among the selected molecules, compound ALS-31 was capable of inhibiting SmSOD with an IC50 value of 159 µM. Its inhibition power was affected by the Fe/Mn ratio in the active site of SmSOD. Furthermore, ALS-31 also inhibited the activity of other SODs. Gel-filtration of SmSOD in the presence of ALS-31 showed that the compound provoked the dissociation of the SmSOD homodimer in two monomers, thus compromising the catalytic activity of the enzyme. A docking model, showing the binding mode of ALS-31 at the dimer interface of SmSOD, is presented. Cell viability of the fibroblast cell line BJ5-ta was not affected up to 100 µM ALS-31. A preliminary lead optimization program allowed the identification of one derivative, ALS-31-9, endowed with a 2.5-fold improved inhibition power. Interestingly, below this concentration, planktonic growth and biofilm formation of S. mutans cultures were inhibited by ALS-31, and even more by its derivative, thus opening the perspective of future drug design studies to fight against dental caries.

A chemoinformatics search for peroxisome proliferator-activated receptors ligands revealed a new pan-agonist able to reduce lipid accumulation and improve insulin sensitivity.

The peroxisome proliferator-activated receptors (PPARs) are nuclear receptors involved in the regulation of the metabolic homeostasis and therefore represent valuable therapeutic targets for the treatment of metabolic diseases. The development of more balanced drugs interacting with PPARs, devoid of the side-effects showed by the currently marketed PPARγ full agonists, is considered the major challenge for the pharmaceutical companies. Here we present a chemoinformatics search approach for new ligands that let us identify a novel PPAR pan-agonist with a very attractive activity profile being able to reduce lipid accumulation and improve insulin sensitivity. This compound represents, therefore, the potential lead of a new class of drugs for treatment of dyslipidemic type 2 diabetes.

Targeting SARS-CoV-2 Proteases and Polymerase for COVID-19 Treatment: State of the Art and Future Opportunities.

The newly emerged coronavirus, called SARS-CoV-2, is the causing pathogen of pandemic COVID-19. The identification of drugs to treat COVID-19 and other coronavirus diseases is an urgent global need, thus different strategies targeting either virus or host cell are still under investigation. Direct-acting agents, targeting protease and polymerase functionalities, represent a milestone in antiviral therapy. The 3C-like (or Main) protease (3CLpro) and the nsp12 RNA-dependent RNA-polymerase (RdRp) are the best characterized SARS-CoV-2 targets and show the highest degree of conservation across coronaviruses fostering the identification of broad-spectrum inhibitors. Coronaviruses also possess a papain-like protease, another essential enzyme, still poorly characterized and not equally conserved, limiting the identification of broad-spectrum agents. Herein, we provide an exhaustive comparative analysis of SARS-CoV-2 proteases and RdRp with respect to other coronavirus homologues. Moreover, we highlight the most promising inhibitors of these proteins reported so far, including the possible strategies for their further development.

In Silico Drug Design and Discovery: Big Data for Small Molecule Design.

Across life sciences, the steadily and rapidly increasing amount of data provide new opportunities for advancing knowledge and represent a key driver of emerging technological advancements [...].

"Molecular Anatomy": a new multi-dimensional hierarchical scaffold analysis tool.

The scaffold representation is widely employed to classify bioactive compounds on the basis of common core structures or correlate compound classes with specific biological activities. In this paper, we present a novel approach called "Molecular Anatomy" as a flexible and unbiased molecular scaffold-based metrics to cluster large set of compounds. We introduce a set of nine molecular representations at different abstraction levels, combined with fragmentation rules, to define a multi-dimensional network of hierarchically interconnected molecular frameworks. We demonstrate that the introduction of a flexible scaffold definition and multiple pruning rules is an effective method to identify relevant chemical moieties. This approach allows to cluster together active molecules belonging to different molecular classes, capturing most of the structure activity information, in particular when libraries containing a huge number of singletons are analyzed. We also propose a procedure to derive a network visualization that allows a full graphical representation of compounds dataset, permitting an efficient navigation in the scaffold's space and significantly contributing to perform high quality SAR analysis. The protocol is freely available as a web interface at https://ma.exscalate.eu .

Altered Local Interactions and Long-Range Communications in UK Variant (B.1.1.7) Spike Glycoprotein.

The COVID-19 pandemic is caused by SARS-CoV-2. Currently, most of the research efforts towards the development of vaccines and antibodies against SARS-CoV-2 were mainly focused on the spike (S) protein, which mediates virus entry into the host cell by binding to ACE2. As the virus SARS-CoV-2 continues to spread globally, variants have emerged, characterized by multiple mutations of the S glycoprotein. Herein, we employed microsecond-long molecular dynamics simulations to study the impact of the mutations of the S glycoprotein in SARS-CoV-2 Variant of Concern 202012/01 (B.1.1.7), termed the "UK variant", in comparison with the wild type, with the aim to decipher the structural basis of the reported increased infectivity and virulence. The simulations provided insights on the different dynamics of UK and wild-type S glycoprotein, regarding in particular the Receptor Binding Domain (RBD). In addition, we investigated the role of glycans in modulating the conformational transitions of the RBD. The overall results showed that the UK mutant experiences higher flexibility in the RBD with respect to wild type; this behavior might be correlated with the increased transmission reported for this variant. Our work also adds useful structural information on antigenic "hotspots" and epitopes targeted by neutralizing antibodies.

A Series of Ferulic Acid Amides Reveals Unexpected Peroxiredoxin 1 Inhibitory Activity with in†vivo Antidiabetic and Hypolipidemic Effects.

Insulin resistance is a major pathophysiological feature in the development of type 2 diabetes (T2DM). Ferulic acid is known for attenuating the insulin resistance and reducing the blood glucose in T2DM rats. In this work, we designed and synthesized a library of new ferulic acid amides (FAA), which could be considered as ring opening derivatives of the antidiabetic PPARγ agonists Thiazolidinediones (TZDs). However, since these compounds displayed weak PPAR transactivation capacity, we employed a proteomics approach to unravel their molecular target(s) and identified the peroxiredoxin 1 (PRDX1) as a direct binding target of FAAs. Interestingly, PRDX1, a protein with antioxidant and chaperone activity, has been implied in the development of T2DM by inducing hepatic insulin resistance. SPR, mass spectrometry-based studies, docking experiments and in vitro inhibition assay confirmed that compounds VIe and VIf bound PRDX1 and induced a dose-dependent inhibition. Furthermore, VIe and VIf significantly improved hyperglycemia and hyperlipidemia in streptozotocin-nicotinamide (STZ-NA)-induced diabetic rats as confirmed by histopathological examinations. These results provide guidance for developing the current FAAs as new potential antidiabetic agents.

Binding Mode Exploration of B1 Receptor Antagonists' by the Use of Molecular Dynamics and Docking Simulation-How Different Target Engagement Can Determine Different Biological Effects.

The kinin B1 receptor plays a critical role in the chronic phase of pain and inflammation. The development of B1 antagonists peaked in recent years but almost all promising molecules failed in clinical trials. Little is known about these molecules' mechanisms of action and additional information will be necessary to exploit the potential of the B1 receptor. With the aim of contributing to the available knowledge of the pharmacology of B1 receptors, we designed and characterized a novel class of allosteric non-peptidic inhibitors with peculiar binding characteristics. Here, we report the binding mode analysis and pharmacological characterization of a new allosteric B1 antagonist, DFL20656. We analyzed the binding of DFL20656 by single point mutagenesis and radioligand binding assays and we further characterized its pharmacology in terms of IC50, B1 receptor internalization and in vivo activity in comparison with different known B1 antagonists. We highlighted how different binding modes of DFL20656 and a Merck compound (compound 14) within the same molecular pocket can affect the biological and pharmacological properties of B1 inhibitors. DFL20656, by its peculiar binding mode, involving tight interactions with N114, efficiently induced B1 receptor internalization and evoked a long-lasting effect in an in vivo model of neuropathic pain. The pharmacological characterization of different B1 antagonists highlighted the effects of their binding modes on activity, receptor occupancy and internalization. Our results suggest that part of the failure of most B1 inhibitors could be ascribed to a lack of knowledge about target function and engagement.

SARS-CoV-2 Entry Inhibitors: Small Molecules and Peptides Targeting Virus or Host Cells.

The pandemic evolution of SARS-CoV-2 infection is forcing the scientific community to unprecedented efforts to explore all possible approaches against COVID-19. In this context, targeting virus entry is a promising antiviral strategy for controlling viral infections. The main strategies pursued to inhibit the viral entry are considering both the virus and the host factors involved in the process. Primarily, direct-acting antivirals rely on inhibition of the interaction between ACE2 and the receptor binding domain (RBD) of the Spike (S) protein or targeting the more conserved heptad repeats (HRs), involved in the membrane fusion process. The inhibition of host TMPRSS2 and cathepsins B/L may represent a complementary strategy to be investigated. In this review, we discuss the development entry inhibitors targeting the S protein, as well as the most promising host targeting strategies involving TMPRSS2 and CatB/L, which have been exploited so far against CoVs and other related viruses.

Computational Studies of SARS-CoV-2 3CLpro: Insights from MD Simulations.

Given the enormous social and health impact of the pandemic triggered by severe acute respiratory syndrome 2 (SARS-CoV-2), the scientific community made a huge effort to provide an immediate response to the challenges posed by Coronavirus disease 2019 (COVID-19). One of the most important proteins of the virus is an enzyme, called 3CLpro or main protease, already identified as an important pharmacological target also in SARS and Middle East respiratory syndrome virus (MERS) viruses. This protein triggers the production of a whole series of enzymes necessary for the virus to carry out its replicating and infectious activities. Therefore, it is crucial to gain a deeper understanding of 3CLpro structure and function in order to effectively target this enzyme. All-atoms molecular dynamics (MD) simulations were performed to examine the different conformational behaviors of the monomeric and dimeric form of SARS-CoV-2 3CLpro apo structure, as revealed by microsecond time scale MD simulations. Our results also shed light on the conformational dynamics of the loop regions at the entry of the catalytic site. Studying, at atomic level, the characteristics of the active site and obtaining information on how the protein can interact with its substrates will allow the design of molecules able to block the enzymatic function crucial for the virus.

Sulfonimide and Amide Derivatives as Novel PPARα Antagonists: Synthesis, Antiproliferative Activity, and Docking Studies.

An agonist-antagonist switching strategy was performed to discover novel PPARα antagonists. Phenyldiazenyl derivatives of fibrates were developed, bearing sulfonimide or amide functional groups. A second series of compounds was synthesized, replacing the phenyldiazenyl moiety with amide or urea portions. Final compounds were screened by transactivation assay, showing good PPARα antagonism and selectivity at submicromolar concentrations. When tested in cancer cell models expressing PPARα, selected derivatives induced marked effects on cell viability. Notably, 3c, 3d, and 10e displayed remarkable antiproliferative effects in two paraganglioma cell lines, with CC50 lower than commercial PPARα antagonist GW6471 and a negligible toxicity on normal fibroblast cells. Docking studies were also performed to elucidate the binding mode of these compounds and to help interpretation of SAR data.