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.

Novel 6-alkyl-bridged 4-arylalkylpiperazin-1-yl derivatives of azepino[4,3-b]indol-1(2H)-one as potent BChE-selective inhibitors showing protective effects against neurodegenerative insults

Due to the putative role of butyrylcholinesterase (BChE) in regulation of acetylcholine levels and functions in the late stages of the Alzheimer's disease (AD), the potential of selective inhibitors (BChEIs) has been envisaged as an alternative to administration of acetylcholinesterase inhibitors (AChEIs). Starting from our recent findings, herein the synthesis and in vitro evaluation of cholinesterase (ChE) inhibition of a novel series of some twenty 3,4,5,6-tetrahydroazepino[4,3-b]indol-1(2H)-one derivatives, bearing at the indole nitrogen diverse alkyl-bridged 4-arylalkylpiperazin-1-yl chains, are reported. The length of the spacers, as well as the type of arylalkyl group affected the enzyme inhibition potency and BChE/AChE selectivity. Two compounds, namely 14c (IC50 = 163 nM) and 14d (IC50 = 65 nM), bearing at the nitrogen atom in position 6 a n-pentyl- or n-heptyl-bridged 4-phenethylpiperazin-1-yl chains, respectively, proved to be highly potent mixed-type inhibitors of both equine and human BChE isoforms, showing more than two order magnitude of selectivity over AChE. The study of binding kinetics through surface plasmon resonance (SPR) highlighted differences in their BChE residence times (8 and 47 s for 14c and 14d, respectively). Moreover, 14c and 14d proved to hit other mechanisms known to trigger neurodegeneration underlying AD and other CNS disorders. Unlike 14c, compound 14d proved also capable of inhibiting by more than 60% the in vitro self-induced aggregation of neurotoxic amyloid-β (Aβ) peptide at 100 μM concentration. On the other hand, 14c was slightly better than 14d in counteracting, at 1 and 10 μM concentration, glutamate excitotoxicity, due to over-excitation of NMDA receptors, and hydrogen peroxide-induced oxidative stress assessed in neuroblastoma cell line SH-SY5Y. This paper is dedicated to Prof. Marcello Ferappi, former dean of the Faculty of Pharmacy of the University of Bari, in the occasion of his 90th birthday.

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.

Where developmental toxicity meets explainable artificial intelligence: state-of-the-art and perspectives

INTRODUCTION

The application of Artificial Intelligence (AI) to predictive toxicology is rapidly increasing, particularly aiming to develop non-testing methods that effectively address ethical concerns and reduce economic costs. In this context, Developmental Toxicity (Dev Tox) stands as a key human health endpoint, especially significant for safeguarding maternal and child well-being.

AREAS COVERED

This review outlines the existing methods employed in Dev Tox predictions and underscores the benefits of utilizing New Approach Methodologies (NAMs), specifically focusing on eXplainable Artificial Intelligence (XAI), which proves highly efficient in constructing reliable and transparent models aligned with recommendations from international regulatory bodies.

EXPERT OPINION

The limited availability of high-quality data and the absence of dependable Dev Tox methodologies render XAI an appealing avenue for systematically developing interpretable and transparent models, which hold immense potential for both scientific evaluations and regulatory decision-making.

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.

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.

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.

Investigation on Novel E/Z 2-Benzylideneindan-1-One-Based Photoswitches with AChE and MAO-B Dual Inhibitory Activity

The multitarget therapeutic strategy, as opposed to the more traditional 'one disease-one target-one drug', may hold promise in treating multifactorial neurodegenerative syndromes, such as Alzheimer's disease (AD) and related dementias. Recently, combining a photopharmacology approach with the multitarget-directed ligand (MTDL) design strategy, we disclosed a novel donepezil-like compound, namely 2-(4-((diethylamino)methyl)benzylidene)-5-methoxy-2,3-dihydro-1H-inden-1-one (1a), which in the E isomeric form (and about tenfold less in the UV-B photo-induced isomer Z) showed the best activity as dual inhibitor of the AD-related targets acetylcholinesterase (AChE) and monoamine oxidase B (MAO-B). Herein, we investigated further photoisomerizable 2-benzylideneindan-1-one analogs 1b-h with the unconjugated tertiary amino moiety bearing alkyls of different bulkiness and lipophilicity. For each compound, the thermal stable E geometric isomer, along with the E/Z mixture as produced by UV-B light irradiation in the photostationary state (PSS, 75% Z), was investigated for the inhibition of human ChEs and MAOs. The pure E-isomer of the N-benzyl(ethyl)amino analog 1h achieved low nanomolar AChE and high nanomolar MAO-B inhibition potencies (IC50s 39 and 355 nM, respectively), whereas photoisomerization to the Z isomer (75% Z in the PSS mixture) resulted in a decrease (about 30%) of AChE inhibitory potency, and not in the MAO-B one. Molecular docking studies were performed to rationalize the different E/Z selectivity of 1h toward the two target enzymes.

Exploration of a new class of monoamine oxidase B inhibitors by assembling benzyloxy pharmacophore on halogenated chalcones

Eight derivatives of benzyloxy-derived halogenated chalcones (BB1-BB8) were synthesized and tested for their ability to inhibit monoamine oxidases (MAOs). MAO-A was less efficiently inhibited by all compounds than MAO-B. Additionally, the majority of the compounds displayed significant MAO-B inhibitory activities at 1 μM with residual activities of less than 50%. With an IC50 value of 0.062 μM, compound BB4 was the most effective in inhibiting MAO-B, followed by compound BB2 (IC50  = 0.093 μM). The lead molecules showed good activity than the reference MAO-B inhibitors (Lazabemide IC50  = 0.11 μM and Pargyline Pargyline IC50  = 0.14). The high selectivity index (SI) values for MAO-B were observed in compounds BB2 and BB4 (430.108 and 645.161, respectively). Kinetics and reversibility experiments revealed that BB2 and BB4 were reversible competitive MAO-B inhibitors with Ki values of 0.030 ± 0.014 and 0.011 ± 0.005 μM, respectively. Swiss target prediction confirmed the high probability in the targets of MAO-B for both compounds. Hypothetical binding mode revealed that the BB2 or BB4 is similarly oriented to the binding cavity of MAO-B. Based on the modelling results, BB4 showed a stable confirmation during the dynamic simulation. From these results, it was concluded that BB2 and BB4 were potent selective reversible MAO-B inhibitors and they can be considered drug candidates for treating related neurodegenerative diseases such as Parkinson's disease.

Short-term anti-remodeling effects of gliflozins in diabetic patients with heart failure and reduced ejection fraction: an explainable artificial intelligence approach

Introduction: Sodium-glucose cotransporter type 2 inhibitors (SGLT2i), gliflozins, play an emerging role for the treatment of heart failure with reduced left ventricular ejection fraction (HFrEF). Nevertheless, the effects of SGLT2i on ventricular remodeling and function have not been completely understood yet. Explainable artificial intelligence represents an unprecedented explorative option to clinical research in this field. Based on echocardiographic evaluations, we identified some key clinical responses to gliflozins by employing a machine learning approach. Methods: Seventy-eight consecutive diabetic outpatients followed for HFrEF were enrolled in the study. Using a random forests classification, a single subject analysis was performed to define the profile of patients treated with gliflozins. An explainability analysis using Shapley values was used to outline clinical parameters that mostly improved after gliflozin therapy and machine learning runs highlighted specific variables predictive of gliflozin response. Results: The five-fold cross-validation analyses showed that gliflozins patients can be identified with a 0.70 ± 0.03% accuracy. The most relevant parameters distinguishing gliflozins patients were Right Ventricular S'-Velocity, Left Ventricular End Systolic Diameter and E/e' ratio. In addition, low Tricuspid Annular Plane Systolic Excursion values along with high Left Ventricular End Systolic Diameter and End Diastolic Volume values were associated to lower gliflozin efficacy in terms of anti-remodeling effects. Discussion: In conclusion, a machine learning analysis on a population of diabetic patients with HFrEF showed that SGLT2i treatment improved left ventricular remodeling, left ventricular diastolic and biventricular systolic function. This cardiovascular response may be predicted by routine echocardiographic parameters, with an explainable artificial intelligence approach, suggesting a lower efficacy in case of advanced stages of cardiac remodeling.

Targeting protein-protein interactions with low molecular weight and short peptide modulators: insights on disease pathways and starting points for drug discovery

INTRODUCTION

Protein-protein interactions (PPIs) have been often considered undruggable targets although they are attractive for the discovery of new therapeutics. The spread of artificial intelligence and machine learning complemented with experimental methods is likely to change the perspectives of protein-protein modulator research. Noteworthy, some novel low molecular weight (LMW) and short peptide modulators of PPIs are already in clinical trials for the treatment of relevant diseases.

AREAS COVERED

This review focuses on the main molecular properties of protein-protein interfaces and on key concepts pertaining to the modulation of PPIs. The authors survey recently reported state-of-the-art methods dealing with the rational design of PPI modulators and highlight the role of several computer-based approaches.

EXPERT OPINION

Interfering specifically with large protein interfaces is still an open challenge. The initial concerns about the unfavorable physicochemical properties of many of these modulators are nowadays less acute with several molecules lying beyond the rule of 5, orally available and successful in clinical trials. As the cost of biologics interfering with PPIs is very high, it would seem reasonable to put more effort, both in academia and the private sectors, on actively developing novel low molecular weight compounds and short peptides to perform this task.

Growth hormone secretagogues modulate inflammation and fibrosis in mdx mouse model of Duchenne muscular dystrophy

Introduction

Growth hormone secretagogues (GHSs) exert multiple actions, being able to activate GHS-receptor 1a, control inflammation and metabolism, to enhance GH/insulin-like growth factor-1 (IGF-1)-mediated myogenesis, and to inhibit angiotensin-converting enzyme. These mechanisms are of interest for potentially targeting multiple steps of pathogenic cascade in Duchenne muscular dystrophy (DMD).

Methods

Here, we aimed to provide preclinical evidence for potential benefits of GHSs in DMD, via a multidisciplinary in vivo and ex vivo comparison in mdx mice, of two ad hoc synthesized compounds (EP80317 and JMV2894), with a wide but different profile. 4-week-old mdx mice were treated for 8 weeks with EP80317 or JMV2894 (320 µg/kg/d, s.c.).

Results

In vivo, both GHSs increased mice forelimb force (recovery score, RS towards WT: 20% for EP80317 and 32% for JMV2894 at week 8). In parallel, GHSs also reduced diaphragm (DIA) and gastrocnemius (GC) ultrasound echodensity, a fibrosis-related parameter (RS: ranging between 26% and 75%). Ex vivo, both drugs ameliorated DIA isometric force and calcium-related indices (e.g., RS: 40% for tetanic force). Histological analysis highlighted a relevant reduction of fibrosis in GC and DIA muscles of treated mice, paralleled by a decrease in gene expression of TGF-β1 and Col1a1. Also, decreased levels of pro-inflammatory genes (IL-6, CD68), accompanied by an increment in Sirt-1, PGC-1α and MEF2c expression, were observed in response to treatments, suggesting an overall improvement of myofiber metabolism. No detectable transcript levels of GHS receptor-1a, nor an increase of circulating IGF-1 were found, suggesting the presence of a novel receptor-independent mechanism in skeletal muscle. Preliminary docking studies revealed a potential binding capability of JMV2894 on metalloproteases involved in extracellular matrix remodeling and cytokine production, such as ADAMTS-5 and MMP-9, overactivated in DMD.

Discussion

Our results support the interest of GHSs as modulators of pathology progression in mdx mice, disclosing a direct anti-fibrotic action that may prove beneficial to contrast pathological remodeling.

N-adamantyl-anthranil amide derivatives: New selective ligands for the cannabinoid receptor subtype 2 (CB2R)

Cannabinoid type 2 receptor (CB2R) is a G-protein-coupled receptor that, together with Cannabinoid type 1 receptor (CB1R), endogenous cannabinoids and enzymes responsible for their synthesis and degradation, forms the EndoCannabinoid System (ECS). In the last decade, several studies have shown that CB2R is overexpressed in activated central nervous system (CNS) microglia cells, in disorders based on an inflammatory state, such as neurodegenerative diseases, neuropathic pain, and cancer. For this reason, the anti-inflammatory and immune-modulatory potentials of CB2R ligands are emerging as a novel therapeutic approach. The design of selective ligands is however hampered by the high sequence homology of transmembrane domains of CB1R and CB2R. Based on a recent three-arm pharmacophore hypothesis and latest CB2R crystal structures, we designed, synthesized, and evaluated a series of new N-adamantyl-anthranil amide derivatives as CB2R selective ligands. Interestingly, this new class of compounds displayed a high affinity for human CB2R along with an excellent selectivity respect to CB1R. In this respect, compounds exhibiting the best pharmacodynamic profile in terms of CB2R affinity were also evaluated for the functional behavior and molecular docking simulations provided a sound rationale by highlighting the relevance of the arm 1 substitution to prompt CB2R action. Moreover, the modulation of the pro- and anti-inflammatory cytokines production was also investigated to exert the ability of the best compounds to modulate the inflammatory cascade.

Artificial intelligence-driven identification of morin analogues acting as CaV1.2 channel blockers: Synthesis and biological evaluation

Morin is a vasorelaxant flavonoid, whose activity is ascribable to Ca_V1.2 channel blockade that, however, is weak as compared to that of clinically used therapeutic agents. A conventional strategy to circumvent this drawback is to synthesize new derivatives differently decorated and, in this context, morin-derivatives able to interact with Ca_V1.2 channels were found by employing the potential of PLATO in target fishing and reverse screening. Three different derivatives (5a-c) were selected as promising tools, synthesized, and investigated in in vitro functional studies using rat aorta rings and rat tail artery myocytes. 5a-c were found more effective vasorelaxant agents than the naturally occurring parent compound and antagonized both electro- and pharmaco-mechanical coupling in an endothelium-independent manner. 5a, the series' most potent, reduced also Ca²⁺ mobilization from intracellular store sites. Furthermore, 5a≈5c > 5b inhibited Ba²⁺ current through Ca_V1.2 channels. However, compound 5a caused also a concentration-dependent inhibition of K_Ca1.1 channel currents.

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.

An Integrated Machine Learning Model To Spot Peptide Binding Pockets in 3D Protein Screening

The prediction of peptide-protein binding sites is of utmost importance to tackle the onset of severe neurodegenerative diseases and cancer. In this work, we detail a novel machine learning model based on Linear Discriminant Analysis (LDA) demonstrating to be highly predictive in detecting the putative protein binding regions of small peptides. Starting from 439 high-quality pockets derived from peptide-protein crystallographic complexes, three sets of well-established peptide-binding regions were first selected through a Partitioning Around Medoids (PAM) clustering algorithm based on morphological and energetic 3D GRID-MIF molecular descriptors. Next, the best combination between all the putative interacting peptide pockets and related GRID-MIF scores was automatically explored by using the LDA-based protocol implemented in BioGPS. This approach proved successful to recognize the actual interacting peptide regions (that is, AUC = 0.86 and partial ROC enrichment at 5% of 0.48) from all the other pockets of the protein. Validated on two external collections sets, including 445 and 347 crystallographic peptide-protein complexes, our LDA-based model could be effective to further run peptide-protein virtual screening campaigns.

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.

252 SHORT-TERM ANTI-REMODELING EFFECTS OF GLIFLOZINS IN DIABETIC PATIENTS WITH REDUCED EJECTION FRACTION: AN EXPLAINABLE ARTIFICIAL INTELLIGENCE APPROACH

Background

Sodium glucose cotransporter type 2 inhibitors (SGLT2i), also called gliflozins, are playing an emerging role for the treatment of heart failure with reduced left ventricle ejection fraction (HFrEF). However, the direct effects of SGLT2i on left and right ventricular remodeling and function have not been completely clarified. We therefore aimed to assess clinical response to gliflozins focusing on echocardiographic evaluation and identify any predictive factors with a machine learning approach.

Methods

Based on Random Forest, a robust and consolidated machine learning approach, we carried out a single subject analysis to evaluate to which extent patients treated with gliflozins can effectively be distinguished from patients undergoing non-gliflozins treatments. Besides, we carried out an eXplainability analysis using Shapley values to outline the clinical parameters which mostly took advantage by gliflozins. Finally, machine learning experiments were designed to highlight the presence of specific clinical patterns undermining the gliflozins effectiveness.

Results

5-fold cross-validation analyses showed that gliflozin treatment was identified with a 0.70 ± 0.03% accuracy; the most important parameters supporting such accuracy were Right Ventricle S’ Velocity (RV S’), Left Ventricle End Systolic Diameter (LVESD) and E/e’ ratio. Low Tricuspid Annular Plane Systolic Excursion (TAPSE) values along with high LVESD and End Diastolic Volume (EDV) values are likely to impair the gliflozin effectiveness.

Conclusions

Treatment with gliflozins resulted in an improvement of several echocardiographic parameters related to biventricular function and left ventricle remodeling. Several clinical parameters, as simple echocardiographic parameters, may accurately predict the cardiovascular response to gliflozins treatment.

A twenty-year journey exploring coumarin-based derivatives as bioactive molecules

The coumarin core (i.e., 1-benzopyran-2 (2H)-one) is a structural motif highly recurrent in both natural products and bioactive molecules. Indeed, depending on the substituents and branching positions around the byciclic core, coumarin-containing compounds have shown diverse pharmacological activities, ranging from anticoagulant activities to anti-inflammatory, antimicrobial, anti-HIV and antitumor effects. In this survey, we have reported the main scientific results of the 20-years investigation on the coumarin core, exploited by the research group headed by Prof. Angelo Carotti (Bari, Italy) either as a scaffold or a pharmacophore moiety in designing novel biologically active small molecules.

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 (K_i) 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 K_i 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.

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.

Getting Insights into Structural and Energetic Properties of Reciprocal Peptide-Protein Interactions

Peptide-protein interactions play a key role for many cellular and metabolic processes involved in the onset of largely spread diseases such as cancer and neurodegenerative pathologies. Despite the progress in the structural characterization of peptide-protein interfaces, the in-depth knowledge of the molecular details behind their interactions is still a daunting task. Here, we present the first comprehensive in silico morphological and energetic study of peptide binding sites by focusing on both peptide and protein standpoints. Starting from the PixelDB database, a nonredundant benchmark collection of high-quality 3D crystallographic structures of peptide-protein complexes, a classification analysis of the most representative categories based on the nature of each cocrystallized peptide has been carried out. Several interpretable geometrical and energetic descriptors have been computed both from peptide and target protein sides in the attempt to unveil physicochemical and structural causative correlations. Finally, we investigated the most frequent peptide-protein residue pairs at the binding interface and made extensive energetic analyses, based on GRID MIFs, with the aim to study the peptide affinity-enhancing interactions to be further exploited in rational drug design strategies.

17β-Hydroxysteroid Dehydrogenase Type 1 Inhibition: A Potential Treatment Option for Non-Small Cell Lung Cancer

In the face of the clinical challenge posed by non-small cell lung cancer (NSCLC), the present need for new therapeutic approaches is genuine. Up to now, no proof existed that 17β-hydroxysteroid dehydrogenase type 1 (17β-HSD1) is a viable target for treating this disease. Synthesis of a rationally designed library of 2,5-disubstituted furan derivatives followed by biological screening led to the discovery of 17β-HSD1 inhibitor 1, capable of fully inhibiting human NSCLC Calu-1 cell proliferation. Its pharmacological profile renders it eligible for further in vivo studies. The very high selectivity of 1 over 17β-HSD2 was investigated, revealing a rational approach for the design of selective inhibitors. 17β-HSD1 and 1 hold promise in fighting NSCLC.

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 CC2 most potently inhibited MAO-B with an IC₅₀ value of 0.51 μM, followed by CC1 (IC₅₀ = 0.69 μM), with a selectivity index (SI) of >78.4 and >58.0, respectively, over MAO-A. However, none of the compounds effectively inhibited MAO-A, AChE, and BChE, except for CC2 and CC3 inhibiting BChE with IC₅₀ values of 7.00 (SI > 5.73 over AChE) and 11.8 μM, respectively. CC1 and CC2 were found to be reversible and competitive inhibitors of MAO-B, with K _i values of 0.50 ± 0.06 and 0.53 ± 0.04 μM, respectively, and CC2 was also a reversible and competitive inhibitor of BChE, with a K _i value of 2.84 ± 0.09 μM. The parallel artificial membrane permeability assay (PAMPA) method showed that lead candidates can cross the blood-brain barrier (BBB). The in vitro toxicity analysis on the Vero cell line (Normal African green monkey kidney epithelial cells) by MTT confirmed that both CC1 and CC2 were nontoxic up to 100 μg/mL, which is almost equivalent to 100 times of their effective concentration used in biological studies. In addition, CC1 and CC2 attenuated H₂O₂-induced cellular damage via their reactive oxygen species (ROS) scavenging effect. These results suggest that CC1 and CC2 are selective and competitive inhibitors of MAO-B, and that CC2 is a selective and competitive inhibitor of BChE. Molecular docking studies of lead compounds provided the possible type of interactions in the targeted enzymes. Based on the findings, both compounds, CC1 and CC2, can be considered plausible drug candidates against neurodegenerative disorders.

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 ΔpIC₅₀, 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. Several large internal and external validation studies were carried out to demonstrate the robustness and the predictive potential of the herein proposed method. Additional comparative studies, carried out on two freely available and well-known ligand-target prediction platforms, demonstrated the reliability of our proposed approach for accurate ligand-target matching. Moreover, two applicative cases were also discussed to practically describe how to use our predictive algorithm, which is freely available as a user-friendly web platform. The user can screen single or multiple queries at a time and retrieve the output as a terse html table or as a json file including all of the information concerning the explored similarities to obtain a deeper understanding of the results. High-throughput virtual reverse screening campaigns, allowing for a given query compound the quick detection of the potential drug target from a large collection of them, can be carried out in batch on demand.

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 (NEA1–NEA5), and evaluated for their inhibitory profiles of monoamine oxidases (MAOs) and β-site amyloid precursor protein cleaving enzyme 1 (β-secretase, BACE1). Compounds NEA3 and NEA1 exhibited a more potent MAO-B inhibition (IC₅₀ value = 0.0092 and 0.016 µM, respectively) than the standards (IC₅₀ value = 0.11 and 0.14 µM, respectively, for lazabemide and pargyline). Moreover, NEA3 and NEA1 showed greater selectivity index (SI) values toward MAO-B over MAO-A (SI of >1652.2 and >2500.0, respectively). The inhibition and kinetics studies suggested that NEA3 and NEA1 are reversible and competitive inhibitors with K_i values of 0.013 ± 0.005 and 0.0049 ± 0.0002 µM, respectively, for MAO-B. In addition, both NEA3 and NEA1 showed efficient BACE1 inhibitions with IC₅₀ values of 8.02 ± 0.13 and 8.21 ± 0.03 µM better than the standard quercetin value (13.40 ± 0.04 µM). The parallel artificial membrane permeability assay (PAMPA) method demonstrated that all the synthesized derivatives can cross the blood–brain barrier (BBB) successfully. Docking analyses were performed by employing an induced-fit docking approach in the GLIDE module of Schrodinger, and the results were in agreement with their in vitro inhibitory activities. The present study resulted in the discovery of potent dual inhibitors toward MAO-B and BACE1, and these lead compounds can be fruitfully explored for the generation of newer, clinically active agents for the treatment of neurodegenerative disorders.

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 IC₅₀ values in the low micromolar range. The sulfonate analogues 1b–c and 1j exhibited good in vitro antiproliferative activity on the MCF7 cell line, evidenced by MTT and LDH release assays. Structure–activity relationships suggested that electronic and lipophilic properties could have a different role in promoting the biological response for sulfonates and sulfonamides, respectively. Docking studies disclosed the main interactions at a molecular level of detail behind the observed inhibition of the more active compounds whose chemical stability has been evaluated with nano-liquid chromatography. Finally, 1b–c and 1j were highlighted as sulfonates to be further developed as novel and original aromatase inhibitors.

Synthesis and biological evaluation of 3,5-diaryl-pyrazole derivatives as potential antiprostate cancer agents

Prostate cancer is the most frequently diagnosed tumor in men and the second leading cause of cancer-associated mortality in most developed countries. 3,5-Diaryl substituted pyrazole derivatives (20-28) were prepared starting from related chalcones and biologically evaluated for in vitro growth inhibition activity against PC3 and DU145 human prostate cancer cell lines. Compounds 23, 26, and 28 were found to be more potent as compared to the other halogen-substituted derivatives. Especially, the 2-bromo-substituted pyrazole derivative (26) was found to be more potent against PC3 and DU145 cells. Epidermal growth factor receptor (EGFR) and vascular endothelial growth factor receptor 2 (VEGFR2) are known to be expressed in DU145 and PC3 cancer cells. The binding mode of the most selective compound 26 toward EGFR and VEGFR2 was investigated by employing docking simulations based on GLIDE standard precision (-5.912 and -6.949 kcal/mol, respectively).

Synthesis, structure-activity relationships and molecular docking studies of phenyldiazenyl sulfonamides as aromatase inhibitors

The exploration of innovative aromatase inhibitors represents an important approach for the identification of new therapeutic treatments of breast cancer. In this respect, a series of phenyldiazenyl sulfonamides was designed, synthesized and tested. Compounds 3b, 3f and 5f showed an aromatase inhibition in the micromolar range and were evaluated in vitro on the human breast cancer cell line MCF7 by MTT assay, cytotoxicity assay (LDH release), cell cycle analysis and apoptosis, revealing a dose-dependent inhibition profile. In particular, 3f displayed the best reduction in terms of metabolic activity and an anti-proliferative effect on MCF7 cells, being blocked in the G1/S phase checkpoint. Moreover, computational studies were carried out to better understand at a molecular level of detail the rationale behind the effective binding to the active site of aromatase of the more active inhibitor 3f. The obtained results allow to consider this compound as an interesting lead for the development of a new class of non-steroidal aromatase inhibitors.

Piperazine-substituted chalcones: a new class of MAO-B, AChE, and BACE-1 inhibitors for the treatment of neurological disorders

Eleven piperazine-containing 1,3-diphenylprop-2-en-1-one derivatives (PC1-PC11) were evaluated for their inhibitory activities against monoamine oxidases (MAOs), cholinesterases (ChEs), and β-site amyloid precursor protein cleaving enzyme 1 (BACE-1) with a view toward developing new treatments for neurological disorders. Compounds PC10 and PC11 remarkably inhibited MAO-B with IC₅₀ values of 0.65 and 0.71 μM, respectively. Ten of the eleven compounds weakly inhibited AChE and BChE with > 50% of residual activities at 10 μM, although PC4 inhibited AChE by 56.6% (IC₅₀ = 8.77 μM). Compound PC3 effectively inhibited BACE-1 (IC₅₀ = 6.72 μM), and PC10 and PC11 moderately inhibited BACE-1 (IC₅₀ =14.9 and 15.3 μM, respectively). Reversibility and kinetic studies showed that PC10 and PC11 were reversible and competitive inhibitors of MAO-B with K_i values of 0.63 ± 0.13 and 0.53 ± 0.068 μM, respectively. ADME predictions for lead compounds revealed that PC10 and PC11 have central nervous system (CNS) drug-likeness. Molecular docking simulations showed that fluorine atom and trifluoromethyl group on PC10 and PC11, respectively, interacted with the substrate cavity of the MAO-B active site. Our results suggested that PC10 and PC11 can be considered potential candidates for the treatment of neurological disorders such as Alzheimer's disease and Parkinson's disease.

A Comprehensive Review of Monoamine Oxidase-A Inhibitors in their Syntheses and Potencies

BACKGROUND

Monoamine oxidases (MAOs) play a crucial role during the development of various neurodegenerative disorders. There are two MAO isozymes, MAO-A and MAO-B. MAO-A is a flavoenzyme, which binds to the outer mitochondrial membrane and catalyzes the oxidative transformations of neurotransmitters like serotonin, norepinephrine, and dopamine.

MATERIALS AND METHODS

Focus on synthetic studies has culminated in the preparation of many MAOA inhibitors, and advancements in combinatorial and parallel synthesis have accelerated the developments of synthetic schemes. Here, we provided an overview of the synthetic protocols employed to prepare different classes of MAO-A inhibitors. We classified these inhibitors according to their molecular scaffolds and the synthetic methods used.

RESULTS

Various synthetic and natural derivatives from a different class of MAO-A inhibitors were reported.

CONCLUSION

The review provides a valuable tool for the development of a new class of various selective MAO-A inhibitors for the treatment of depression and other anxiety disorders.

Morpholine-based chalcones as dual-acting monoamine oxidase-B and acetylcholinesterase inhibitors: synthesis and biochemical investigations

Nine compounds (MO1–MO9) containing the morpholine moiety were assessed for their inhibitory activities against monoamine oxidases (MAOs) and acetylcholinesterase (AChE). Most of the compounds potently inhibited MAO-B; MO1 most potently inhibited with an IC₅₀ value of 0.030 µM, followed by MO7 (0.25 µM). MO5 most potently inhibited AChE (IC₅₀ = 6.1 µM), followed by MO9 (IC₅₀ = 12.01 µM) and MO7 most potently inhibited MAO-A (IC₅₀ = 7.1 µM). MO1 was a reversible mixed-type inhibitor of MAO-B (K_i = 0.018 µM); MO5 reversibly competitively inhibited AChE (K_i = 2.52 µM); and MO9 reversibly noncompetitively inhibited AChE (K_i = 7.04 µM). MO1, MO5 and MO9 crossed the blood–brain barrier, and were non-toxic to normal VERO cells. These results show that MO1 is a selective inhibitor of MAO-B and that MO5 is a dual-acting inhibitor of AChE and MAO-B, and that both should be considered candidates for the treatment of Alzheimer’s disease.

Anticancer potential of novel α,β-unsaturated γ-lactam derivatives targeting the PI3K/AKT signaling pathway

Six recently synthesized alkyl (Z)-2-(2-oxopyrrolidin-3-ylidene)acetates were evaluated for their potential as cytotoxic and anticancer agents. All compounds were tested in the ERα positive MCF-7, triple negative MDA-MB-231, and Her2⁺ SKBR-3 breast cancer cell lines. The most lipophilic derivatives, bearing the 4-isopropylphenyl (2) or 4-tert-butylphenyl (3) group at the γ-lactam nitrogen, proved to be cytotoxic against all the cancer cell lines tested (IC₅₀ values ranging from 18 to 63 μM), exerting their greatest activity in SKBR-3 cells, with IC₅₀ values of 33 and 18 μM, respectively. Biological studies showed that the cytotoxic effects of 2 and 3 are accompanied by apoptotic death in breast cancer cells, and both compounds showed no significant toxicity on healthy cells (e.g., MCF-10A) and red blood cells. An in-depth mechanistic study based on molecular biology, immunoblotting analysis and in silico docking calculations suggested that α,β-unsaturated γ-lactam derivatives could interfere with the functioning of PI3K and PDK-1, two key enzymes in the PI3K/AKT signaling pathway, whose overactivation is related to the regulation of cell growth and survival in several malignancies.

Trimethoxylated Halogenated Chalcones as Dual Inhibitors of MAO-B and BACE-1 for the Treatment of Neurodegenerative Disorders

Six halogenated trimethoxy chalcone derivatives (CH1-CH6) were synthesized and spectrally characterized. The compounds were further evaluated for their inhibitory potential against monoamine oxidases (MAOs) and β-secretase (BACE-1). Six compounds inhibited MAO-B more effectively than MAO-A, and the 2',3',4'-methoxy moiety in CH4-CH6 was more effective for MAO-B inhibition than the 2',4',6'-methoxy moiety in CH1-CH3. Compound CH5 most potently inhibited MAO-B, with an IC₅₀ value of 0.46 µM, followed by CH4 (IC₅₀ = 0.84 µM). In 2',3',4'-methoxy derivatives (CH4-CH6), the order of inhibition was -Br in CH5 > -Cl in CH4 > -F in CH6 at the para-position in ring B of chalcone. CH4 and CH5 were selective for MAO-B, with selectivity index (SI) values of 15.1 and 31.3, respectively, over MAO-A. CH4 and CH5 moderately inhibited BACE-1 with IC₅₀ values of 13.6 and 19.8 µM, respectively. When CH4 and CH5 were assessed for their cell viability studies on the normal African Green Monkey kidney cell line (VERO) using MTT assays, it was noted that both compounds were found to be safe, and only a slightly toxic effect was observed in concentrations above 200 µg/mL. CH4 and CH5 decreased reactive oxygen species (ROS) levels of VERO cells treated with H₂O₂, indicating both compounds retained protective effects on the cells by antioxidant activities. All compounds showed high blood brain barrier permeabilities analyzed by a parallel artificial membrane permeability assay (PAMPA). Molecular docking and ADME prediction of the lead compounds provided more insights into the rationale behind the binding and the CNS drug likeness. From non-test mutagenicity and cardiotoxicity studies, CH4 and CH5 were non-mutagenic and non-/weak-cardiotoxic. These results suggest that CH4 and CH5 could be considered candidates for the cure of neurological dysfunctions.

Trimethoxy Crown Chalcones as Multifunctional Class of Monoamine Oxidase Enzyme Inhibitors

BACKGROUND

Chalcones with methoxy substituents 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 an MAO-A inhibition constant value equal to 3.47±0.09 μM and with a selectivity of 0.008. Thus, it was comparable to that of moclobemide, a well known potent hMAO-A inhibitor (SI=0.010). Compound (2E)-3-(4-bromophenyl)-1-(3,4,5-trimethoxyphenyl)prop-2-en-1-one (TMh) showed good MAO-B inhibition, with an 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.

CATMoS: Collaborative Acute Toxicity Modeling Suite

BACKGROUND

Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management. However, it is cost- and time-prohibitive to evaluate all new and existing chemicals using traditional rodent acute toxicity tests. In silico models built using existing data facilitate rapid acute toxicity predictions without using animals.

OBJECTIVES

The U.S. Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) Acute Toxicity Workgroup organized an international collaboration to develop in silico models for predicting acute oral toxicity based on five different end points: Lethal Dose 50 (LD50 value, U.S. Environmental Protection Agency hazard (four) categories, Globally Harmonized System for Classification and Labeling hazard (five) categories, very toxic chemicals [LD50 (LD50≤50mg/kg)], and nontoxic chemicals (LD50>2,000mg/kg).

METHODS

An acute oral toxicity data inventory for 11,992 chemicals was compiled, split into training and evaluation sets, and made available to 35 participating international research groups that submitted a total of 139 predictive models. Predictions that fell within the applicability domains of the submitted models were evaluated using external validation sets. These were then combined into consensus models to leverage strengths of individual approaches.

RESULTS

The resulting consensus predictions, which leverage the collective strengths of each individual model, form the Collaborative Acute Toxicity Modeling Suite (CATMoS). CATMoS demonstrated high performance in terms of accuracy and robustness when compared with in vivo results.

DISCUSSION

CATMoS is being evaluated by regulatory agencies for its utility and applicability as a potential replacement for in vivo rat acute oral toxicity studies. CATMoS predictions for more than 800,000 chemicals have been made available via the National Toxicology Program's Integrated Chemical Environment tools and data sets (ice.ntp.niehs.nih.gov). The models are also implemented in a free, standalone, open-source tool, OPERA, which allows predictions of new and untested chemicals to be made. https://doi.org/10.1289/EHP8495.

Away from Flatness: Unprecedented Nitrogen-Bridged Cyclopenta[a]indene Derivatives as Novel Anti-Alzheimer Multitarget Agents

Nature-inspired, bridged polycyclic molecules share low similarity with currently available drugs, containing preferentially planar and/or achiral moieties. This "Escape from Flatland" scenario, aimed at exploring pharmacological properties of atypical molecular scaffolds, finds interest in synthetic routes leading to tridimensional-shaped molecules. Herein we report on the synthesis of N-bridged cyclopenta[a]indene derivatives, achieved through microwave-assisted thermal rearrangement of allene 3-benzazecines with high diastereoselectivity. The biological evaluation disclosed selective inhibition of human acetylcholinesterase or butyrylcholinesterase, depending on the substitution around the molecular core, which was rationalized by means of docking simulations. The most potent BChE inhibitor 31 was effective in neuroprotection from glutamatergic excitotoxicity and displayed low intrinsic cytotoxicity and good brain penetration. Overall, compound 31 and its close congeners 34 and 35 acted as multitarget agents addressing different biological events involved in neurodegeneration, particularly in the progression of Alzheimer's disease.

Design, synthesis and biological evaluation of imidazole and triazole-based carbamates as novel aromatase inhibitors

In the search for novel aromatase inhibitors, a series of triazole and imidazole-based carbamate derivatives were designed and synthesized. Final compounds were thus evaluated against human aromatase by in vitro kinetic experiments in a fluorimetric assay in comparison with letrozole. The effect of most active derivatives 13a and 15c was then evaluated in vitro on the human breast cancer cell line MCF7 by MTT assay, cytotoxicity assay (LDH release) and cell cycle analysis, revealing a dose-dependent inhibition profile of cell viability and low micromolar IC₅₀ values. In addition, docking simulations were also carried out to elucidate at a molecular level of detail the binding modes adopted to target human aromatase.

Pharmacophore Modeling and 3D-QSAR Study of Indole and Isatin Derivatives as Antiamyloidogenic Agents Targeting Alzheimer's Disease

Thirty-six novel indole-containing compounds, mainly 3-(2-phenylhydrazono) isatins and structurally related 1H-indole-3-carbaldehyde derivatives, were synthesized and assayed as inhibitors of beta amyloid (Aβ) aggregation, a hallmark of pathophysiology of Alzheimer’s disease. The newly synthesized molecules spanned their IC₅₀ values from sub- to two-digit micromolar range, bearing further information into structure-activity relationships. Some of the new compounds showed interesting multitarget activity, by inhibiting monoamine oxidases A and B. A cell-based assay in tau overexpressing bacterial cells disclosed a promising additional activity of some derivatives against tau aggregation. The accumulated data of either about ninety published and thirty-six newly synthesized molecules were used to generate a pharmacophore hypothesis of antiamyloidogenic activity exerted in a wide range of potencies, satisfactorily discriminating the ‘active’ compounds from the ‘inactive’ (poorly active) ones. An atom-based 3D-QSAR model was also derived for about 80% of ‘active’ compounds, i.e., those achieving finite IC₅₀ values lower than 100 μM. The 3D-QSAR model (encompassing 4 PLS factors), featuring acceptable predictive statistics either in the training set (n = 45, q² = 0.596) and in the external test set (n = 14, r²_ext = 0.695), usefully complemented the pharmacophore model by identifying the physicochemical features mainly correlated with the Aβ anti-aggregating potency of the indole and isatin derivatives studied herein.