VenomPred 2.0: A Novel In Silico Platform for an Extended and Human Interpretable Toxicological Profiling of Small Molecules.

The application of artificial intelligence and machine learning (ML) methods is becoming increasingly popular in computational toxicology and drug design; it is considered as a promising solution for assessing the safety profile of compounds, particularly in lead optimization and ADMET studies, and to meet the principles of the 3Rs, which calls for the replacement, reduction, and refinement of animal testing. In this context, we herein present the development of VenomPred 2.0 (http://www.mmvsl.it/wp/venompred2/), the new and improved version of our free of charge web tool for toxicological predictions, which now represents a powerful web-based platform for multifaceted and human-interpretable in silico toxicity profiling of chemicals. VenomPred 2.0 presents an extended set of toxicity endpoints (androgenicity, skin irritation, eye irritation, and acute oral toxicity, in addition to the already available carcinogenicity, mutagenicity, hepatotoxicity, and estrogenicity) that can be evaluated through an exhaustive consensus prediction strategy based on multiple ML models. Moreover, we also implemented a new utility based on the Shapley Additive exPlanations (SHAP) method that allows human interpretable toxicological profiling of small molecules, highlighting the features that strongly contribute to the toxicological predictions in order to derive structural toxicophores.

Glycoconjugate coumarins exploiting metabolism-enhanced fluorescence and preferential uptake: New optical tools for tumor cell staining.

The possibility to visually discriminate cells based on their metabolism and capability to uptake exogenous molecules is an important topic with exciting fallback on translational and precision medicine. To this end, probes that combine several complementary features are necessary. The ideal probe is selectively uptaken and activated in tumor cells compared with control ones and is not fluorescent in the extracellular medium. Fluorogenic compounds that combine enzyme-activated pH sensitivity and good cell uptake can be an ideal solution, provided that the sensed enzymes are dysregulated in tumor cells. Here, we present synthesis and in vitro evaluation of a new class of glyco-coumarin based probes that merge all these features. These probes show uptake ratio in tumor vs. control cells up to 3:1, with a cell to background ratio upon administration of the probe up to 5:1. These features make this new family of fluorogenic targeted probes a promising tool in life science.

Watermelon: setup and validation of an in silico fragment-based approach.

We present a new computational approach, named Watermelon, designed for the development of pharmacophore models based on receptor structures. The methodology involves the sampling of potential hotspots for ligand interactions within a protein target's binding site, utilising molecular fragments as probes. By employing docking and molecular dynamics (MD) simulations, the most significant interactions formed by these probes within distinct regions of the binding site are identified. These interactions are subsequently transformed into pharmacophore features that delineates key anchoring sites for potential ligands. The reliability of the approach was experimentally validated using the monoacylglycerol lipase (MAGL) enzyme. The generated pharmacophore model captured features representing ligand-MAGL interactions observed in various X-ray co-crystal structures and was employed to screen a database of commercially available compounds, in combination with consensus docking and MD simulations. The screening successfully identified two new MAGL inhibitors with micromolar potency, thus confirming the reliability of the Watermelon approach.

The Benzoylpiperidine Fragment as a Privileged Structure in Medicinal Chemistry: A Comprehensive Review.

The phenyl(piperidin-4-yl)methanone fragment (here referred to as the benzoylpiperidine fragment) is a privileged structure in the development of new drugs considering its presence in many bioactive small molecules with both therapeutic (such as anti-cancer, anti-psychotic, anti-thrombotic, anti-arrhythmic, anti-tubercular, anti-parasitic, anti-diabetic, and neuroprotective agents) and diagnostic properties. The benzoylpiperidine fragment is metabolically stable, and it is also considered a potential bioisostere of the piperazine ring, thus making it a feasible and reliable chemical frame to be exploited in drug design. Herein, we discuss the main therapeutic and diagnostic agents presenting the benzoylpiperidine motif in their structure, covering articles reported in the literature since 2000. A specific section is focused on the synthetic strategies adopted to obtain this versatile chemical portion.

Historical perspective of tumor glycolysis: A century with Otto Warburg.

Tumors have long been known to rewire their metabolism to endorse their proliferation, growth, survival, and invasiveness. One of the common characteristics of these alterations is the enhanced glucose uptake and its subsequent transformation into lactic acid by means of glycolysis, regardless the availability of oxygen or the mitochondria effectiveness. This phenomenon is called the "Warburg effect", which has turned into a century of age now, since its first disclosure by German physiologist Otto Heinrich Warburg. Since then, this peculiar metabolic switch in tumors has been addressed by extensive studies covering several areas of research. In this historical perspective, we aim at illustrating the evolution of these studies over time and their implication in various fields of science.

Identification of New GSK3ß Inhibitors through a Consensus Machine Learning-Based Virtual Screening.

Glycogen synthase kinase-3 beta (GSK3ß) is a serine/threonine kinase that plays key roles in glycogen metabolism, Wnt/ß-catenin signaling cascade, synaptic modulation, and multiple autophagy-related signaling pathways. GSK3ß is an attractive target for drug discovery since its aberrant activity is involved in the development of neurodegenerative diseases such as Alzheimer's and Parkinson's disease. In the present study, multiple machine learning models aimed at identifying novel GSK3ß inhibitors were developed and evaluated for their predictive reliability. The most powerful models were combined in a consensus approach, which was used to screen about 2 million commercial compounds. Our consensus machine learning-based virtual screening led to the identification of compounds G1 and G4, which showed inhibitory activity against GSK3ß in the low-micromolar and sub-micromolar range, respectively. These results demonstrated the reliability of our virtual screening approach. Moreover, docking and molecular dynamics simulation studies were employed for predicting reliable binding modes for G1 and G4, which represent two valuable starting points for future hit-to-lead and lead optimization studies.

Metabolic Effects of New Glucose Transporter (GLUT-1) and Lactate Dehydrogenase-A (LDH-A) Inhibitors against Chemoresistant Malignant Mesothelioma.

Malignant mesothelioma (MM) is a highly aggressive and resistant tumor. The prognostic role of key effectors of glycolytic metabolism in MM prompted our studies on the cytotoxicity of new inhibitors of glucose transporter type 1 (GLUT-1) and lactate dehydrogenase-A (LDH-A) in relation to ATP/NAD+ metabolism, glycolysis and mitochondrial respiration. The antiproliferative activity of GLUT-1 (PGL13, PGL14) and LDH-A (NHI-1, NHI-2) inhibitors, alone and in combination, were tested with the sulforhodamine-B assay in peritoneal (MESO-II, STO) and pleural (NCI-H2052 and NCI-H28) MM and non-cancerous (HMEC-1) cells. Effects on energy metabolism were measured by both analysis of nucleotides using RP-HPLC and evaluation of glycolysis and respiration parameters using a Seahorse Analyzer system. All compounds reduced the growth of MM cells in the µmolar range. Interestingly, in H2052 cells, PGL14 decreased ATP concentration from 37 to 23 and NAD+ from 6.5 to 2.3 nmol/mg protein. NHI-2 reduced the ATP/ADP ratio by 76%. The metabolic effects of the inhibitors were stronger in pleural MM and in combination, while in HMEC-1 ATP reduction was 10% lower compared to that of the H2052 cells, and we observed a minor influence on mitochondrial respiration. To conclude, both inhibitors showed cytotoxicity in MM cells, associated with a decrease in ATP and NAD+, and were synergistic in the cells with the highest metabolic modulation. This underlines cellular energy metabolism as a potential target for combined treatments in selected cases of MM.

New PIN1 inhibitors identified through a pharmacophore-driven, hierarchical consensus docking strategy.

PIN1 is considered as a therapeutic target for a wide variety of tumours. However, most of known inhibitors are devoid of cellular activity despite their good enzyme inhibitory profile. Hence, the lack of effective compounds for the clinic makes the identification of novel PIN1 inhibitors a hot topic in the medicinal chemistry field. In this work, we reported a virtual screening study for the identification of new promising PIN1 inhibitors. A receptor-based procedure was applied to screen different chemical databases of commercial compounds. Based on the whole workflow, two compounds were selected and biologically evaluated. Both ligands, compounds VS1 and VS2, showed a good enzyme inhibitory activity and VS2 also demonstrated a promising antitumoral activity in ovarian cancer cells. These results confirmed the reliability of our in silico protocol and provided a structurally novel ligand as a valuable starting point for the development of new PIN1 inhibitors.

Machine Learning-Based Virtual Screening for the Identification of Cdk5 Inhibitors.

Cyclin-dependent kinase 5 (Cdk5) is an atypical proline-directed serine/threonine protein kinase well-characterized for its role in the central nervous system rather than in the cell cycle. Indeed, its dysregulation has been strongly implicated in the progression of synaptic dysfunction and neurodegenerative diseases, such as Alzheimer's disease (AD) and Parkinson's disease (PD), and also in the development and progression of a variety of cancers. For this reason, Cdk5 is considered as a promising target for drug design, and the discovery of novel small-molecule Cdk5 inhibitors is of great interest in the medicinal chemistry field. In this context, we employed a machine learning-based virtual screening protocol with subsequent molecular docking, molecular dynamics simulations and binding free energy evaluations. Our virtual screening studies resulted in the identification of two novel Cdk5 inhibitors, highlighting an experimental hit rate of 50% and thus validating the reliability of the in silico workflow. Both identified ligands, compounds CPD1 and CPD4, showed a promising enzyme inhibitory activity and CPD1 also demonstrated a remarkable antiproliferative activity in ovarian and colon cancer cells. These ligands represent a valuable starting point for structure-based hit-optimization studies aimed at identifying new potent Cdk5 inhibitors.

Biological Activity of Natural and Synthetic Compounds.

A drug discovery program starts when a disease or clinical condition has no suitable drugs [...].

Sirtuin 1-Activating Compounds: Discovery of a Class of Thiazole-Based Derivatives.

Sirtuin 1 (SIRT1) is a NAD+-dependent deacetylase implicated in various biological and pathological processes, including cancer, diabetes, and cardiovascular diseases. In recent years, SIRT1-activating compounds have been demonstrated to exert cardioprotective effects. Therefore, this enzyme has become a feasible target to treat cardiovascular diseases, and many SIRT1 activators, of a natural or synthetic origin, have been identified. In the present work, we developed thiazole-based SIRT1 activators, which showed remarkably higher SIRT1 activation potencies compared with those of the reference compound resveratrol when tested in enzymatic assays. Thiazole 8, a representative compound of this series, was also subjected to further pharmacological investigations, where it was proven to reduce myocardial damage induced by an in vivo occlusion/reperfusion event, thus confirming its cardioprotective properties. In addition, the cardioprotective effect of compound 8 was significantly higher than that of resveratrol. Molecular modeling studies suggest the binding mode of these derivatives within SIRT1 in the presence of the p53-AMC peptide. These promising results could pave the way to further expand and optimize this chemical class of new and potent SIRT1 activators as potential cardioprotective agents.

The dichotomous role of the glycolytic metabolism pathway in cancer metastasis: Interplay with the complex tumor microenvironment and novel therapeutic strategies.

Cancer metastasis to distant organs is initiated by tumor cells that disseminate from primary heterogeneous tumors. The subsequent growth and survival of tumor metastases depend on different metabolic changes, which constitute one of the enigmatic properties of tumor cells. Aerobic glycolysis, 'the Warburg effect', contributes to tumor energy supply, by oxidizing glucose in a faster manner compared to oxidative phosphorylation, leading to an increased lactate production by lactate dehydrogenase A (LDH-A), which in turn affects the immune response. Surrounding stromal cells contribute to feedback mechanisms further prompting the acquisition of pro-invasive metabolic features. Hence, therapeutic strategies targeting the glycolytic pathway are intensively investigated, with a special interest on their anti-metastatic properties. Various small molecules, such as LDH-A inhibitors, have shown pre-clinical activity against different cancer types, and blocking LDH-A could also help in designing future complimentary therapies. Modulation of specific targets in cells with an altered glycolytic metabolism should indeed result in a milder and distinct toxicity profile, compared to conventional cytotoxic therapy, while a combination treatment with vitamin C leading to increasing reactive oxygen species levels, should further inhibit cancer cell survival and invasion. In this review we describe the impact of metabolic reprogramming in cancer metastasis, the contribution of lactate in this aberrant process and its effect on oncogenic processes. Furthermore, we discuss experimental compounds that target glycolytic metabolism, such as LDH-A inhibitors, and their potential to improve current and experimental therapeutics against metastatic tumors.

Impact of hypoxia on chemoresistance of mesothelioma mediated by the proton-coupled folate transporter, and preclinical activity of new anti-LDH-A compounds.

BACKGROUND: Expression of proton-coupled folate transporter (PCFT) is associated with survival of mesothelioma patients treated with pemetrexed, and is reduced by hypoxia, prompting studies to elucidate their correlation. METHODS: Modulation of glycolytic gene expression was evaluated by PCR arrays in tumour cells and primary cultures growing under hypoxia, in spheroids and after PCFT silencing. Inhibitors of lactate dehydrogenase (LDH-A) were tested in vitro and in vivo. LDH-A expression was determined in tissue microarrays of radically resected malignant pleural mesothelioma (MPM, N = 33) and diffuse peritoneal mesothelioma (DMPM, N = 56) patients. RESULTS: Overexpression of hypoxia marker CAIX was associated with low PCFT expression and decreased MPM cell growth inhibition by pemetrexed. Through integration of PCR arrays in hypoxic cells and spheroids and following PCFT silencing, we identified the upregulation of LDH-A, which correlated with shorter survival of MPM and DMPM patients. Novel LDH-A inhibitors enhanced spheroid disintegration and displayed synergistic effects with pemetrexed in MPM and gemcitabine in DMPM cells. Studies with bioluminescent hypoxic orthotopic and subcutaneous DMPM athymic-mice models revealed the marked antitumour activity of the LDH-A inhibitor NHI-Glc-2, alone or combined with gemcitabine. CONCLUSIONS: This study provides novel insights into hypoxia/PCFT-dependent chemoresistance, unravelling the potential prognostic value of LDH-A, and demonstrating the preclinical activity of LDH-A inhibitors.

Application of MM-PBSA Methods in Virtual Screening.

Computer-aided drug design techniques are today largely applied in medicinal chemistry. In particular, receptor-based virtual screening (VS) studies, in which molecular docking represents the gold standard in silico approach, constitute a powerful strategy for identifying novel hit compounds active against the desired target receptor. Nevertheless, the need for improving the ability of docking in discriminating true active ligands from inactive compounds, thus boosting VS hit rates, is still pressing. In this context, the use of binding free energy evaluation approaches can represent a profitable tool for rescoring ligand-protein complexes predicted by docking based on more reliable estimations of ligand-protein binding affinities than those obtained with simple scoring functions. In the present review, we focused our attention on the Molecular Mechanics-Poisson Boltzman Surface Area (MM-PBSA) method for the calculation of binding free energies and its application in VS studies. We provided examples of successful applications of this method in VS campaigns and evaluation studies in which the reliability of this approach has been assessed, thus providing useful guidelines for employing this approach in VS.

Discovery of Monoacylglycerol Lipase (MAGL) Inhibitors Based on a Pharmacophore-Guided Virtual Screening Study.

Monoacylglycerol lipase (MAGL) is an important enzyme of the endocannabinoid system that catalyzes the degradation of the major endocannabinoid 2-arachidonoylglycerol (2-AG). MAGL is associated with pathological conditions such as pain, inflammation and neurodegenerative diseases like Parkinson's and Alzheimer's disease. Furthermore, elevated levels of MAGL have been found in aggressive breast, ovarian and melanoma cancer cells. Due to its different potential therapeutic implications, MAGL is considered as a promising target for drug design and the discovery of novel small-molecule MAGL inhibitors is of great interest in the medicinal chemistry field. In this context, we developed a pharmacophore-based virtual screening protocol combined with molecular docking and molecular dynamics simulations, which showed a final hit rate of 50% validating the reliability of the in silico workflow and led to the identification of two promising and structurally different reversible MAGL inhibitors, VS1 and VS2. These ligands represent a valuable starting point for structure-based hit-optimization studies aimed at identifying new potent MAGL inhibitors.

Virtual screening identifies a PIN1 inhibitor with possible antiovarian cancer effects.

Peptidyl-prolyl cis-trans isomerase, NIMA-interacting 1 (PIN1) is a peptidyl-prolyl isomerase that binds phospho-Ser/Thr-Pro motifs in proteins and catalyzes the cis-trans isomerization of proline peptide bonds. PIN1 is overexpressed in several cancers including high-grade serous ovarian cancer. Since few therapies are effective against this cancer, PIN1 could be a therapeutic target but effective PIN1 inhibitors are lacking. To identify molecules with in vivo inhibitory effects on PIN1, we used consensus docking to model existing PIN1-ligand X-ray structures and to screen a chemical database for candidate inhibitors. Ten molecules were selected and tested in cellular assays, leading to the identification of VS10 that bound and inhibited PIN1. VS10 treatment reduced the viability of ovarian cancer cell lines by inducing proteasomal PIN1 degradation, without effects on PIN1 transcription, and also reduced the levels of downstream targets ß-catenin, cyclin D1, and pSer473-Akt. VS10 is a selective PIN1 inhibitor that may offer new opportunities for treating PIN1-overexpressing tumors.

First Examples of H2S-Releasing Glycoconjugates: Stereoselective Synthesis and Anticancer Activities.

H2S donors are currently emerging as promising therapeutic agents in a wide variety of pathologies, including tumors. Cancer cells are characterized by an enhanced uptake of sugars, such as glucose. Therefore, novel glycoconjugated H2S donors were synthesized so that high concentrations of H2S can be selectively achieved therein. Dithiolethione portions or isothiocyanate portions were selected for their well-known H2S-releasing properties in the presence of biological substrates. A synthetic procedure employing trichloroacetimidate glycosyl donors was applied to produce, in a stereoselective fashion, C1-glycoconjugates, whereas C6-glycoconjugates were obtained by a Mitsunobu-based transformation. The resulting molecules were then tested for their anticancer effects on human pancreas adenocarcinoma ascites metastasis cell line AsPC-1. The most potent inhibitors of cell viability (6aß and 7b) proved to release H2S inside the AsPC-1 cells and to alter the basal cell cycle.

Computationally driven discovery of phenyl(piperazin-1-yl)methanone derivatives as reversible monoacylglycerol lipase (MAGL) inhibitors.

Monoacylglycerol lipase (MAGL) is an attractive therapeutic target for many pathologies, including neurodegenerative diseases, cancer as well as chronic pain and inflammatory pathologies. The identification of reversible MAGL inhibitors, devoid of the side effects associated to prolonged MAGL inactivation, is a hot topic in medicinal chemistry. In this study, a novel phenyl(piperazin-1-yl)methanone inhibitor of MAGL was identified through a virtual screening protocol based on a fingerprint-driven consensus docking (CD) approach. Molecular modeling and preliminary structure-based hit optimization studies allowed the discovery of derivative 4, which showed an efficient reversible MAGL inhibition (IC50 = 6.1 µM) and a promising antiproliferative activity on breast and ovarian cancer cell lines (IC50 of 31-72 µM), thus representing a lead for the development of new and more potent reversible MAGL inhibitors. Moreover, the obtained results confirmed the reliability of the fingerprint-driven CD approach herein developed.

Synthesis and Biological Evaluation of New Glycoconjugated LDH Inhibitors as Anticancer Agents.

Conjugation of known biologically active molecules to carbohydrate frameworks represents a valuable option for the preparation of hybrid, structurally-related families of compounds with the aim of modulating their biological response. Therefore, we present here a study on the preparation of d-galacto, d-manno, d-gluco, and d-lactose glycoconjugates of an established N-hydroxyindole-based (NHI) inhibitor of lactated dehydrogenase (LDH). Structural variations involved the sugar stereochemistry and size as well as the anchoring point of the NHI on the carbohydrate frame (either C-1 or C-6). In the case of the galactose anomeric glycoconjugate (C-1), intriguing solvent-dependent effects were observed in the glycosylation stereochemical outcome. The biological activity of the deprotected glycoconjugates in contrasting lactate formation and cancer cell proliferation are described.

Effect of Tumor Relevant Acidic Environment in the Interaction of a N-hydroxyindole-2-Carboxylic Derivative with the Phospholipid Bilayer.

PURPOSE: The inhibitors of the human isoform 5 of lactate dehydrogenase (hLDH5) have attracted growing interest as efficient anti-cancer agents. In the present paper, the interactions between an efficient hLDH5 inhibitor (N-hydroxyindole-2-carboxylic derivative) and lipid bilayers based on dipalmitoylphosphatidylcholine (DPPC) were investigated. Additionally, since interstitial acidification plays a key role in tumor pathogenesis and tumor drug therapy, the effect of acidic pH was assessed and correlated to DPPC/drug interaction. METHODS: Four different techniques were used: differential scanning calorimetry, dynamic light scattering, UV-VIS second derivative spectrometry and attenuated total reflection Fourier transformed infrared spectroscopy. RESULTS: All techniques concur in highlighting a structural change of lipid assembly, susceptible both to pH change and to the presence of the antitumor compound. Lipid vesicles appeared more compact at the lower pH, since the thermal pre-transition from the lamellar gel phase to the ripple gel phase was absent at pH 7.4 and the infrared analysis revealed a stronger acyl chain packing as well as a different hydration degree. Drug interaction was mainly detected in the lipid region including the ester linkages and the first portion of the acyl chains. Furthermore, a lower drug partitioning was recorded at pH 6.6. CONCLUSIONS: The investigated antitumor agent possesses a stable negative charge at the investigated pH values, thus the lower interaction at the acidic pH is mainly ascribable to an environmental effect on lipid assembly. Therefore, drug efficacy under tumor acid conditions may be hampered by the observed lipid membrane constraints, and suggest for the development of suitable prodrugs.