Modulatory Effect of Nicotinamide Adenine Dinucleotide Phosphate (NADPH) on the 2-Oxoglutarate Mitochondrial Carrier.

The 2-oxoglutarate carrier (OGC), pivotal in cellular metabolism, facilitates the exchange of key metabolites between mitochondria and cytosol. This study explores the influence of NADPH on OGC transport activity using proteoliposomes. Experimental data revealed the ability of NADPH to modulate the OGC activity, with a significant increase of 60% at 0.

TIRESIA and TISBE: Explainable Artificial Intelligence Based Web Platforms for the Transparent Assessment of the Developmental Toxicity of Chemicals and Drugs.

Developmental toxicity is key human health endpoint, especially relevant for safeguarding maternal and child well-being. It is an object of increasing attention from international regulatory bodies such as the US EPA (US Environmental Protection Agency) and ECHA (European CHemicals Agency). In this challenging scenario, non-test methods employing explainable artificial intelligence based techniques can provide a significant help to derive transparent predictive models whose results can be easily interpreted to assess the developmental toxicity of new chemicals at very early stages.

From Deep Learning to the Discovery of Promising VEGFR-2 Inhibitors.

Vascular endothelial growth factor receptor 2 (VEGFR-2) stands as a prominent therapeutic target in oncology, playing a critical role in angiogenesis, tumor growth, and metastasis. FDA-approved VEGFR-2 inhibitors are associated with diverse side effects. Thus, finding novel and more effective inhibitors is of utmost importance.

MzDOCK: A free ready-to-use GUI-based pipeline for molecular docking simulations.

Molecular docking is by far the most preferred approach in structure-based drug design for its effectiveness to predict the scoring and posing of a given bioactive small molecule into the binding site of its pharmacological target. Herein, we present MzDOCK, a new GUI-based pipeline for Windows operating system, designed with the intent of making molecular docking easier to use and higher reproducible even for inexperienced people. By harmonic integration of python and batch scripts, which employs various open source packages such as Smina (docking engine), OpenBabel (file conversion) and PLIP (analysis), MzDOCK includes many practical options such as: binding site configuration based on co-crystallized ligands; generation of enantiomers from SMILES input; application of different force fields (MMFF94, MMFF94s, UFF, GAFF, Ghemical) for energy minimization; retention of selectable ions and cofactors; sidechain flexibility of selectable binding site residues; multiple input file format (SMILES, PDB, SDF, Mol2, Mol); generation of reports and of pictures for interactive visualization.

Novel Dual-Acting Hybrids Targeting Type-2 Cannabinoid Receptors and Cholinesterase Activity Show Neuroprotective Effects In Vitro and Amelioration of Cognitive Impairment In Vivo.

Alzheimer's disease (AD) is a neurodegenerative form of dementia characterized by the loss of synapses and a progressive decline in cognitive abilities. Among current treatments for AD, acetylcholinesterase (AChE) inhibitors have efficacy limited to symptom relief, with significant side effects and poor compliance. Pharmacological agents that modulate the activity of type-2 cannabinoid receptors (CB2R) of the endocannabinoid system by activating or blocking them have also been shown to be effective against neuroinflammation.

CIRCE: Web-Based Platform for the Prediction of Cannabinoid Receptor Ligands Using Explainable Machine Learning.

The endocannabinoid system, which includes cannabinoid receptor 1 and 2 subtypes (CBR and CBR, respectively), is responsible for the onset of various pathologies including neurodegeneration, cancer, neuropathic and inflammatory pain, obesity, and inflammatory bowel disease. Given the high similarity of CBR and CBR, generating subtype-selective ligands is still an open challenge. In this work, the Cannabinoid Iterative Revaluation for Classification and Explanation (CIRCE) compound prediction platform has been generated based on explainable machine learning to support the design of selective CBR and CBR ligands.

Exploring the 1,3-benzoxazine chemotype for cannabinoid receptor 2 as a promising anti-cancer therapeutic.

The discovery of selective agonists of cannabinoid receptor 2 (CB) is strongly pursued to successfully tuning endocannabinoid signaling for therapeutic purposes. However, the design of selective CB agonists is still challenging because of the high homology with the cannabinoid receptor 1 (CB) and for the yet unclear molecular basis of the agonist/antagonist switch. Here, the 1,3-benzoxazine scaffold is presented as a versatile chemotype for the design of CB agonists from which 25 derivatives were synthesized.

New Insights Regarding Hemin Inhibition of the Purified Rat Brain 2-Oxoglutarate Carrier and Relationships with Mitochondrial Dysfunction.

A kinetic analysis of the transport assays on the purified rat brain 2-oxoglutarate/malate carrier (OGC) was performed starting from our recent results reporting about a competitive inhibitory behavior of hemin, a physiological porphyrin derivative, on the OGC reconstituted in an active form into proteoliposomes. The newly provided transport data and the elaboration of the kinetic equations show evidence that hemin exerts a mechanism of partially competitive inhibition, coupled with the formation of a ternary complex hemin-carrier substrate, when hemin targets the OGC from the matrix face. A possible interpretation of the provided kinetic analysis, which is supported by computational studies, could indicate the existence of a binding region responsible for the inhibition of the OGC and supposedly involved in the regulation of OGC activity.

TIRESIA: An eXplainable Artificial Intelligence Platform for Predicting Developmental Toxicity.

Herein, a robust and reproducible eXplainable Artificial Intelligence (XAI) approach is presented, which allows prediction of developmental toxicity, a challenging human-health endpoint in toxicology. The application of XAI as an alternative method is of the utmost importance with developmental toxicity being one of the most animal-intensive areas of regulatory toxicology. In this work, the established CAESAR (Computer Assisted Evaluation of industrial chemical Substances According to Regulations) training set made of 234 chemicals for model learning is employed.

Informed Use of 3D-QSAR for the Rational Design of Coumarin Derivatives as Potent and Selective MAO B Inhibitors.

The quantitative structure-activity relationship method based on the three-dimensional structure of the target molecules (3D-QSAR) represents a valuable predictive tool for the design of new bioactive agents. Herewith, a detailed procedure is described which uses a pool comprising 67 derivatives substituted at position 4 and 7 of the common coumarin scaffold as a benchmark for deriving a predictive 3D-QSAR model employed for guiding the rational design of 10 new potent and selective MAO B inhibitors.

Virtual Reverse Screening Approach to Target Type 2 Cannabinoid Receptor.

A screening pool consisting of 617710 drug-like query molecules properly filtered from the ChEMBL database was employed for a ligand-based reverse screening toward the type 2 cannabinoid receptor (CB) target. By using our recently developed PLATO polypharmacological web platform, 233 out of 617710 drug-like molecules were prioritized on the basis of the predicted bioactivity values, better than 0.2 μM with a probability of about 98%, toward the CB target.

Development of Halogenated-Chalcones Bearing with Dimethoxy Phenyl Head as Monoamine Oxidase-B Inhibitors.

Two series of dimethoxy-halogenated chalcones (DM1−DM20) were synthesized and tested for their ability to inhibit monoamine oxidase (MAOs). Compound DM2 exhibited the most significant inhibition against MAO-B with an IC50 value of 0.067 µM, followed by compound DM18 (IC50 = 0.

Recent Advances on Type-2 Cannabinoid (CB) Receptor Agonists and their Therapeutic Potential.

In the last decade, selective modulators of type-2 cannabinoid receptor (CB) have become a major focus to target endocannabinoid signaling in humans. Indeed, heterogeneously expressed within our body, CB actively regulates several physio-pathological processes, thus representing a promising target for developing specific and safe therapeutic drugs. If CB modulation has been extensively studied since the very beginning for the treatment of pain and inflammation, the more recent involvement of this receptor in other pathological conditions has further strengthened the pursuit of novel CB agonists in the last five years.

Assessing the Role of a Malonamide Linker in the Design of Potent Dual Inhibitors of Factor Xa and Cholinesterases.

The rational discovery of new peptidomimetic inhibitors of the coagulation factor Xa (fXa) could help set more effective therapeutic options (to prevent atrial fibrillation). In this respect, we explored the conformational impact on the enzyme inhibition potency of the malonamide bridge, compared to the glycinamide one, as a linker connecting the P1 benzamidine anchoring moiety to the P4 aryl group of novel selective fXa inhibitors. We carried out structure-activity relationship (SAR) studies aimed at investigating - or -benzamidine as the P1 basic group as well as diversely decorated aryl moieties as P4 fragments.

Development of a Novel Class of Pyridazinone Derivatives as Selective MAO-B Inhibitors.

Sixteen compounds () were synthesized and evaluated for their inhibitory activities against monoamine oxidase A and B (MAOs). Most of the derivatives showed potent and highly selective MAO-B inhibition. Compound was the most potent inhibitor against MAO-B with an IC value of 0.

Rational Discovery of Antiviral Whey Protein-Derived Small Peptides Targeting the SARS-CoV-2 Main Protease.

In the present work, and for the first time, three whey protein-derived peptides (IAEK, IPAVF, MHI), endowed with ACE inhibitory activity, were examined for their antiviral activity against the SARS-CoV-2 3C-like protease (3CL) and Human Rhinovirus 3C protease (3C) by employing molecular docking. Computational studies showed reliable binding poses within 3CL for the three investigated small peptides, considering docking scores as well as the binding free energy values. Validation by in vitro experiments confirmed these results.

PLATO: A Predictive Drug Discovery Web Platform for Efficient Target Fishing and Bioactivity Profiling of Small Molecules.

PLATO (Polypharmacology pLATform predictiOn) is an easy-to-use drug discovery web platform, which has been designed with a two-fold objective: to fish putative protein drug targets and to compute bioactivity values of small molecules. Predictions are based on the similarity principle, through a reverse ligand-based screening, based on a collection of 632,119 compounds known to be experimentally active on 6004 protein targets. An efficient backend implementation allows to speed-up the process that returns results for query in less than 20 s.

Praseodymium trivalent ion is an effective inhibitor of mitochondrial basic amino acids and carnitine/acylcarnitine carriers.

We herein report the identification of the lantanide praseodymium trivalent ion Pr as inhibitor of mitochondrial transporters for basic amino acids and phylogenetically related carriers belonging to the Slc25 family. The inhibitory effect of Pr has been tested using mitochondrial transporters reconstituted into liposomes being effective in the micromolar range, acting as a competitive inhibitor of the human basic amino acids carrier (BAC, Slc25A29), the human carnitine/acylcarnitine carrier (CAC, Slc25A20). Furthermore, we provide computational evidence that the complete inhibition of the transport activity of the recombinant proteins is due to the Pr coordination to key acidic residues of the matrix salt bridge network.

Halogenated Coumarin-Chalcones as Multifunctional Monoamine Oxidase-B and Butyrylcholinesterase Inhibitors.

A series of halogenated coumarin-chalcones were synthesized, characterized, and their inhibitory activities against monoamine oxidases (MAOs), acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and β-site amyloid precursor protein cleaving enzyme 1 (BACE-1) were evaluated. Compound most potently inhibited MAO-B with an IC value of 0.51 μM, followed by (IC = 0.

Design, Synthesis and Biological Evaluation of Aromatase Inhibitors Based on Sulfonates and Sulfonamides of Resveratrol.

A library of sulfonate and sulfonamide derivatives of Resveratrol was synthesized and tested for its aromatase inhibitory potential. Interestingly, sulfonate derivatives were found to be more active than sulfonamide bioisosteres with IC values in the low micromolar range. The sulfonate analogues - and exhibited good in vitro antiproliferative activity on the MCF7 cell line, evidenced by MTT and LDH release assays.

Selected Class of Enamides Bearing Nitro Functionality as Dual-Acting with Highly Selective Monoamine Oxidase-B and BACE1 Inhibitors.

A small series of nitro group-bearing enamides was designed, synthesized (-), and evaluated for their inhibitory profiles of monoamine oxidases (MAOs) and β-site amyloid precursor protein cleaving enzyme 1 (β-secretase, BACE1). Compounds and exhibited a more potent MAO-B inhibition (IC value = 0.0092 and 0.

Quantitative Polypharmacology Profiling Based on a Multifingerprint Similarity Predictive Approach.

We present a new quantitative ligand-based bioactivity prediction approach employing a multifingerprint similarity search algorithm, enabling the polypharmacological profiling of small molecules. Quantitative bioactivity predictions are made on the basis of the statistical distributions of multiple Tanimoto similarity θ values, calculated through 13 different molecular fingerprints, and of the variation of the measured biological activity, reported as ΔpIC, for all of the ligands sharing a given protein drug target. The application data set comprises as much as 4241 protein drug targets as well as 418 485 ligands selected from ChEMBL (release 25) by employing a set of well-defined filtering rules.