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. In this study, a deep learning (DL) classification model was first developed and then employed to select putative active VEGFR-2 inhibitors from an in-house chemical library including 187 druglike compounds. A pool of 18 promising candidates was shortlisted and screened against VEGFR-2 by using molecular docking. Finally, two compounds, RHE-334 and EA-11, were prioritized as promising VEGFR-2 inhibitors by employing PLATO, our target fishing and bioactivity prediction platform. Based on this rationale, we prepared RHE-334 and EA-11 and successfully tested their anti-proliferative potential against MCF-7 human breast cancer cells with IC50 values of 26.78±4.02 and 38.73±3.84 µM, respectively. Their toxicities were instead challenged against the WI-38. Interestingly, expression studies indicated that, in the presence of RHE-334, VEGFR-2 was equal to 0.52±0.03, thus comparable to imatinib equal to 0.63±0.03. In conclusion, this workflow based on theoretical and experimental approaches demonstrates effective in identifying VEGFR-2 inhibitors and can be easily adapted to other medicinal chemistry goals.

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. Users can download for free MzDOCK at the following link: https://github.com/Muzatheking12/MzDOCK.

Small Molecules for the Treatment of Long-COVID-Related Vascular Damage and Abnormal Blood Clotting: A Patent-Based Appraisal.

People affected by COVID-19 are exposed to, among others, abnormal clotting and endothelial dysfunction, which may result in deep vein thrombosis, cerebrovascular disorders, and ischemic and non-ischemic heart diseases, to mention a few. Treatments for COVID-19 include antiplatelet (e.g., aspirin, clopidogrel) and anticoagulant agents, but their impact on morbidity and mortality has not been proven. In addition, due to viremia-associated interconnected prothrombotic and proinflammatory events, anti-inflammatory drugs have also been investigated for their ability to mitigate against immune dysregulation due to the cytokine storm. By retrieving patent literature published in the last two years, small molecules patented for long-COVID-related blood clotting and hematological complications are herein examined, along with supporting evidence from preclinical and clinical studies. An overview of the main features and therapeutic potentials of small molecules is provided for the thromboxane receptor antagonist ramatroban, the pan-caspase inhibitor emricasan, and the sodium-hydrogen antiporter 1 (NHE-1) inhibitor rimeporide, as well as natural polyphenolic compounds.

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. Herein, we describe the design, synthesis, and pharmacological effects in vitro and in vivo of dual-acting compounds that inhibit AChE and butyrylcholinesterase (BChE) and target CB2R. Within the investigated series, compound 4g proved to be the most promising. It achieved IC50 values in the low micromolar to submicromolar range against both human cholinesterase isoforms while antagonizing CB2R with Ki of 31 nM. Interestingly, 4g showed neuroprotective effects on the SH-SY5Y cell line thanks to its ability to prevent oxidative stress-induced cell toxicity and reverse scopolamine-induced amnesia in the Y-maze forced alternation test in vivo.

TISBE: A Public Web Platform for the Consensus-Based Explainable Prediction of Developmental Toxicity.

Despite being extremely relevant for the protection of prenatal and neonatal health, the developmental toxicity (Dev Tox) is a highly complex endpoint whose molecular rationale is still largely unknown. The lack of availability of high-quality data as well as robust nontesting methods makes its understanding even more difficult. Thus, the application of new explainable alternative methods is of utmost importance, with Dev Tox being one of the most animal-intensive research themes of regulatory toxicology. Descending from TIRESIA (Toxicology Intelligence and Regulatory Evaluations for Scientific and Industry Applications), the present work describes TISBE (TIRESIA Improved on Structure-Based Explainability), a new public web platform implementing four fundamental advancements for in silico analyses: a three times larger dataset, a transparent XAI (explainable artificial intelligence) framework employing a fragment-based fingerprint coding, a novel consensus classifier based on five independent machine learning models, and a new applicability domain (AD) method based on a double top-down approach for better estimating the prediction reliability. The training set (TS) includes as many as 1008 chemicals annotated with experimental toxicity values. Based on a 5-fold cross-validation, a median value of 0.410 for the Matthews correlation coefficient was calculated; TISBE was very effective, with a median value of sensitivity and specificity equal to 0.984 and 0.274, respectively. TISBE was applied on two external pools made of 1484 bioactive compounds and 85 pediatric drugs taken from ChEMBL (Chemical European Molecular Biology Laboratory) and TEDDY (Task-Force in Europe for Drug Development in the Young) repositories, respectively. Notably, TISBE gives users the option to clearly spot the molecular fragments responsible for the toxicity or the safety of a given chemical query and is available for free at https://prometheus.farmacia.uniba.it/tisbe.

Making sense of chemical space network shows signs of criticality.

Chemical space modelling has great importance in unveiling and visualising latent information, which is critical in predictive toxicology related to drug discovery process. While the use of traditional molecular descriptors and fingerprints may suffer from the so-called curse of dimensionality, complex networks are devoid of the typical drawbacks of coordinate-based representations. Herein, we use chemical space networks (CSNs) to analyse the case of the developmental toxicity (Dev Tox), which remains a challenging endpoint for the difficulty of gathering enough reliable data despite very important for the protection of the maternal and child health. Our study proved that the Dev Tox CSN has a complex non-random organisation and can thus provide a wealth of meaningful information also for predictive purposes. At a phase transition, chemical similarities highlight well-established toxicophores, such as aryl derivatives, mostly neurotoxic hydantoins, barbiturates and amino alcohols, steroids, and volatile organic compounds ether-like chemicals, which are strongly suspected of the Dev Tox onset and can thus be employed as effective alerts for prioritising chemicals before testing.

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 (CB1R and CB2R, 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 CB1R and CB2R, 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 CB1R and CB2R ligands. Multilayer classifiers were combined with Shapley value analysis to facilitate explainable predictions. In test calculations, CIRCE predictions reached ∼80% accuracy and structural features determining ligand predictions were rationalized. CIRCE was designed as a web-based prediction platform that is made freely available as a part of our study.

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 (CB2) is strongly pursued to successfully tuning endocannabinoid signaling for therapeutic purposes. However, the design of selective CB2 agonists is still challenging because of the high homology with the cannabinoid receptor 1 (CB1) 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 CB2 agonists from which 25 derivatives were synthesized. Among these, compound 7b5 (CB2 EC50 = 110 nM, CB1 EC50 > 10 µM) demonstrated to impair proliferation of triple negative breast cancer BT549 cells and to attenuate the release of pro-inflammatory cytokines in a CB2-dependent manner. Furthermore, 7b5 abrogated the activation of extracellular signal-regulated kinase (ERK) 1/2, a key pro-inflammatory and oncogenic enzyme. Finally, molecular dynamics studies suggested a new rationale for the in vitro measured selectivity and for the observed agonist behavior.

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. Two test sets, including as a whole 585 chemicals, were instead used for validation and generalization purposes. The proposed framework favorably compares with the state-of-the-art approaches in terms of accuracy, sensitivity, and specificity, thus resulting in a reliable support system for developmental toxicity ensuring informativeness, uncertainty estimation, generalization, and transparency. Based on the eXtreme Gradient Boosting (XGB) algorithm, our predictive model provides easy interpretative keys based on specific molecular descriptors and structural alerts enabling one to distinguish toxic and nontoxic chemicals. Inspired by the Organisation for Economic Co-operation and Development (OECD) principles for the validation of Quantitative Structure-Activity Relationships (QSARs) for regulatory purposes, the results are summarized in a standard report in portable document format, enclosing also details concerned with a density-based model applicability domain and SHAP (SHapley Additive exPlanations) explainability, the latter particularly useful to better understand the effective roles played by molecular features. Notably, our model has been implemented in TIRESIA (Toxicology Intelligence and Regulatory Evaluations for Scientific and Industry Applications), a free of charge web platform available at http://tiresia.uniba.it.

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 (CB2) 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 CB2 target. Building on these results, the occurrence of putative CB2-related targets was also investigated for prospective repurposing studies.

Recent Advances on Type-2 Cannabinoid (CB2) Receptor Agonists and their Therapeutic Potential.

In the last decade, selective modulators of type-2 cannabinoid receptor (CB2) have become a major focus to target endocannabinoid signaling in humans. Indeed, heterogeneously expressed within our body, CB2 actively regulates several physio-pathological processes, thus representing a promising target for developing specific and safe therapeutic drugs. If CB2 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 CB2 agonists in the last five years. Against this background, here we discuss the most recent evidence of the protective effects of CB2 against pathological conditions, emphasizing central nervous system disorders, bone and synovial diseases, and cancer. We also summarize the most recent advances in the development of CB2 agonists, focusing on the correlation between different chemical classes and diverse therapeutic applications. Data mining includes a review of the CB2 ligands disclosed in patents also released in the last five years. Finally, we discuss how the recent elucidation of CB2 tertiary structure has provided new details for the rational design of novel and more selective CB2 agonists, thus supporting innovative strategies to develop effective therapeutics. Our overview of the current knowledge on CB2 agonists provides pivotal information on the structure and function of different classes of molecules and opens possible avenues for future research.

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.

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. The proposed regulatory binding site is located on OGC mitochondrial matrix loops, where hemin could establish specific interactions with residues involved in the substrate recognition and/or conformational changes responsible for the translocation of mitochondrial carrier substrates. The regulatory binding site would be placed about 6 Å below the substrate binding site of the OGC, facing the mitochondrial matrix, and would allow the simultaneous binding of hemin and 2-oxoglutarate or malate to different regions of the carrier. Overall, the presented experimental and computational analyses help to shed light on the possible existence of the hemin-carrier substrate ternary complex, confirming the ability of the OGC to bind porphyrin derivatives, and in particular hemin, with possible consequences for the mitochondrial redox state mediated by the malate/aspartate shuttle led by the mitochondrial carriers OGC and AGC.

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 = 0.118 µM), with selectivity index (SI) values of 93.88 and >338.98, respectively. However, none of the substances successfully inhibited MAO-A. The MAO-B inhibitors DM2 and DM18 were competitive and reversible, with Ki values of 0.032 ± 0.004 and 0.045 ± 0.001 µM, respectively. DM2 was non-toxic below 100 µg/mL in the cytotoxic test using the Vero epithelial cell line by the MTT method. According to molecular docking studies, DM2 and DM18 formed very similar conformations within the MAO-B binding pocket, with the ortho-chlorine and ortho-fluorine aromatic rings sandwiched between F168 and Y326. These conformations were predicted to show better interactions with the targeted MAO-B than MAO-A. In particular, the induced-fit docking of the dimethoxy phenyl ring of DM2 facing the hydrophobic pocket made up of FAD, Y398, and Y435 had an impact on F168 in the docking pocket. Taken together, DM2 and DM18 may be suitable candidates for treating neurodegenerative conditions such as Parkinson's disease.

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 para- or meta-benzamidine as the P1 basic group as well as diversely decorated aryl moieties as P4 fragments. To this end, twenty-three malonamide derivatives were synthesized and tested as inhibitors of fXa and thrombin (thr); the molecular determinants behind potency and selectivity were also studied by employing molecular docking. The malonamide linker, compared to the glycinamide one, does significantly increase anti-fXa potency and selectivity. The meta-benzamidine (P1) derivatives bearing 2',4'-difluoro-biphenyl as the P4 moiety proved to be highly potent reversible fXa-selective inhibitors, achieving inhibition constants (Ki) in the low nanomolar range. The most active compounds were also tested against cholinesterase (ChE) isoforms (acetyl- or butyrylcholinesterase, AChE, and BChE), and some of them returned single-digit micromolar inhibition potency against AChE and/or BChE, both being drug targets for symptomatic treatment of mild-to-moderate Alzheimer's disease. Compounds 19h and 22b were selected as selective fXa inhibitors with potential as multimodal neuroprotective agents.

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

Sixteen compounds (TR1-TR16) 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 TR16 was the most potent inhibitor against MAO-B with an IC50 value of 0.17 µM, followed by TR2 (IC50 = 0.27 µM). TR2 and TR16 selectivity index (SI) values for MAO-B versus MAO-A were 84.96 and higher than 235.29, respectively. Compared to the basic structures, the para-chloro substituent in TR2 and TR16 increased the inhibitory activity of MAO-B. TR2 and TR16 were reversible MAO-B inhibitors that were competitive, with Ki values of 0.230 ± 0.004 and 0.149 ± 0.016 µM, respectively. The PAMPA method indicated that compounds TR2 and TR16 had the tendency to traverse the blood-brain barrier. Docking investigations revealed that lead compounds were beneficial for MAO-B inhibition via association with key as well as selective E84 or Y326 residues, but not for MAO-A inhibition via interaction primarily driven by hydrophobic contacts. In conclusion, TR2 and TR16 are therapeutic prospects for the management of multiple neurodegenerative diseases.

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 (3CLpro) and Human Rhinovirus 3C protease (3Cpro) by employing molecular docking. Computational studies showed reliable binding poses within 3CLpro 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. In particular, IPAVF exhibited the highest inhibitory activity by returning an IC50 equal to 1.21 µM; it was followed by IAEK, which registered an IC50 of 154.40 µM, whereas MHI was less active with an IC50 equal to 2700.62 µM. On the other hand, none of the assayed peptides registered inhibitory activity against 3Cpro. Based on these results, the herein presented small peptides are introduced as promising molecules to be exploited in the development of "target-specific antiviral" agents against SARS-CoV-2.

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. The graphical user interface is intuitive to give practitioners easy input and transparent output, which is available as a standard report in portable document format. PLATO has been validated on thousands of external data, with performances better than those of other parallel approaches. PLATO is available free of charge (http://plato.uniba.it/ accessed on 13 April 2022).

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 Pr3+ as inhibitor of mitochondrial transporters for basic amino acids and phylogenetically related carriers belonging to the Slc25 family. The inhibitory effect of Pr3+ 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 Pr3+ coordination to key acidic residues of the matrix salt bridge network. Besides being used as a first choice stop inhibitor for functional studies in vitro of mitochondrial carriers reconstituted in proteoliposomes, Pr3+ might also represent a useful tool for structural studies of the mitochondrial carrier family.

Trimethoxy Crown Chalcones as Multifunctional Class of Monoamine Oxidase Enzyme Inhibitors.

BACKGROUND: Chalcones with methoxy substituent are considered as a promising framework for the inhibition of monoamine oxidase (MAO) enzymes. METHODS: A series of nine trimethoxy substituted chalcones (TMa-TMi) was synthesized and evaluated as a multifunctional class of MAO inhibitors. All the synthesized compounds were investigated for their in vitro MAO inhibition, kinetics, reversibility, blood-brain barrier (BBB) permeation, and cytotoxicity and antioxidant potentials. RESULTS: In the present study, compound (2E)-3-(4-nitrophenyl)-1-(3,4,5-trimethoxyphenyl)prop- 2-en-1-one (TMf) was provided with a MAO-A inhibition constant value equal to 3.47±0.09 µM with a selectivity of 0.008, thus comparable to that of moclobemide, a well known potent hMAOA inhibitor (SI=0.010). Compound (2E)-3-(4-bromophenyl)-1-(3,4,5-trimethoxyphenyl)prop-2- en-1-one (TMh) show good MAO-B inhibition with inhibition constant of 0.46±0.009 µM. The PAMPA assay demonstrated that all the synthesized derivatives can cross the BBB successfully. The cytotoxicity studies revealed that TMf and TMh have 88.22 and 80.18 % cell viability at 25 µM. Compound TMf appeared as the most promising antioxidant molecule with IC50 values, relative to DPPH and H2O2 radical activities equal to 6.02±0.17 and 7.25±0.07 µM. To shed light on the molecular interactions of TMf and TMh towards MAO-A and MAO-B, molecular docking simulations and MM/GBSA calculations have been carried out. CONCLUSION: The lead molecules TMf and TMh with multi-functional nature can be further employed for the treatment of various neurodegenerative disorders and depressive states.