Discovery of new chemotypes of dual 5-HT2A/D2 receptor antagonists with a strategy of drug design methodologies.

Aim: Through the application of structure- and ligand-based methods, the authors aimed to create an integrative approach to developing a computational protocol for the rational drug design of potent dual 5-HT2A/D2 receptor antagonists without off-target activities on H1 receptors. Materials & methods: Molecular dynamics and virtual docking methods were used to identify key interactions of the structurally diverse antagonists in the binding sites of the studied targets, and to generate their bioactive conformations for further 3D-quantitative structure-activity relationship modeling. Results & conclusion: Toward the goal of finding multi-potent drugs with a more effective and safer profile, the obtained results led to the design of a new set of dual antagonists and opened a new perspective on the therapy for complex brain diseases.

Application of in vitro PAMPA technique and in silico computational methods for blood-brain barrier permeability prediction of novel CNS drug candidates.

Permeability assessment of small molecules through the blood-brain barrier (BBB) plays a significant role in the development of effective central nervous system (CNS) drug candidates. Since in vivo methods for BBB permeability estimation require a lot of time and resources, in silico and in vitro approaches are becoming increasingly popular nowadays for faster and more economical predictions in early phases of drug discovery. In this work, through application of in vitro parallel artificial membrane permeability assay (PAMPA-BBB) and in silico computational methods we aimed to examine the passive permeability of eighteen compounds, which affect serotonin and dopamine levels in the CNS. The data set was consisted of novel six human dopamine transporter (hDAT) substrates that were previously identified as the most promising lead compounds for further optimisation to achieve neuroprotective effect, twelve approved CNS drugs, and their related compounds. Firstly, PAMPA methods was used to experimentally determine effective BBB permeability (Pe) for all studied compounds and obtained results were further submitted for quantitative structure permeability relationship (QSPR) analysis. QSPR models were built by using three different statistical methods: stepwise multiple linear regression (MLR), partial least square (PLS), and support-vector machine (SVM), while their predictive capability was tested through internal and external validation. Obtained statistical parameters (MLR- R2pred=-0.10; PLS- R2pred=0.64, r2m=0.69, r/2m=0.44; SVM- R2pred=0.57, r2m=0.72, r/2m=0.55) indicated that the SVM model is superior over others. The most important molecular descriptors (H0p and SolvEMt_3D) were identified and used to propose structural modifications of the examined compounds in order to improve their BBB permeability. Moreover, steered molecular dynamics (SMD) simulation was employed to comprehensively investigate the permeability pathway of compounds through a lipid bilayer. Taken together, the created QSPR model could be used as a reliable and fast pre-screening tool for BBB permeability prediction of structurally related CNS compounds, while performed MD simulations provide a good foundation for future in silico examination.

Synthesis and Biological Activity of a Cytostatic Inhibitor of MLLr Leukemia Targeting the DOT1L Protein.

Histone methyltransferase DOT1L catalyzes mono-, di- and trimethylation of histone 3 at lysine residue 79 (H3K79) and hypermethylation of H3K79 has been linked to the development of acute leukemias characterized by the MLL (mixed-lineage leukemia) rearrangements (MLLr cells). The inhibition of H3K79 methylation inhibits MLLr cells proliferation, and an inhibitor specific for DOT1L, pinometostat, was in clinical trials (Phase Ib/II). However, the compound showed poor pharmacological properties. Thus, there is a need to find new potent inhibitors of DOT1L for the treatment of rearranged leukemias. Here we present the design, synthesis, and biological evaluation of a small molecule that inhibits in the nM level the enzymatic activity of hDOT1L, H3K79 methylation in MLLr cells with comparable potency to pinometostat, associated with improved metabolic stability and a characteristic cytostatic effect.

Benzofuranyl-2-imidazoles as imidazoline I2 receptor ligands for Alzheimer's disease.

Recent findings unveil the pharmacological modulation of imidazoline I2 receptors (I2-IR) as a novel strategy to face unmet medical neurodegenerative diseases. In this work, we report the chemical characterization, three-dimensional quantitative structure-activity relationship (3D-QSAR) and ADMET in silico of a family of benzofuranyl-2-imidazoles that exhibit affinity against human brain I2-IR and most of them have been predicted to be brain permeable. Acute treatment in mice with 2-(2-benzofuranyl)-2-imidazole, known as LSL60101 (garsevil), showed non-warning properties in the ADMET studies and an optimal pharmacokinetic profile. Moreover, LSL60101 induced hypothermia in mice while decreased pro-apoptotic FADD protein in the hippocampus. In vivo studies in the familial Alzheimer's disease 5xFAD murine model with the representative compound, revealed significant decreases in the protein expression levels of antioxidant enzymes superoxide dismutase and glutathione peroxidase in hippocampus. Overall, LSL60101 plays a neuroprotective role by reducing apoptosis and modulating oxidative stress.

An Integrative in silico Drug Repurposing Approach for Identification of Potential Inhibitors of SARS-CoV-2 Main Protease.

Considering the urgent need for novel therapeutics in ongoing COVID-19 pandemic, drug repurposing approach might offer rapid solutions comparing to de novo drug design. In this study, we designed an integrative in silico drug repurposing approach for rapid selection of potential candidates against SARS-CoV-2 Main Protease (Mpro ). To screen FDA-approved drugs, we implemented structure-based molecular modelling techniques, physiologically-based pharmacokinetic (PBPK) modelling of drugs disposition and data mining analysis of drug-gene-COVID-19 association. Through presented approach, we selected the most promising FDA approved drugs for further COVID-19 drug development campaigns and analysed them in context of available experimental data. To the best of our knowledge, this is unique in silico study which integrates structure-based molecular modeling of Mpro inhibitors with predictions of their tissue disposition, drug-gene-COVID-19 associations and prediction of pleiotropic effects of selected candidates.

In silico identification of novel 5-HT2A antagonists supported with ligand- and target-based drug design methodologies.

A wide range of neuropsychological disorders is caused by serotonin 5-HT2A receptor (5-HT2AR) malfunction. Therefore, this receptor had been frequently used as target in CNS drug research. To design novel potent 5-HT2AR antagonists, we have combined ligand-based and target-based approaches. This study was performed on wide range of structurally diverse antagonists that were divided into three different clusters: clozapine, ziprasidone, and ChEMBL240876 derivatives. By performing the 50 ns long molecular dynamic simulations with each cluster representative in complex with 5-HT2A receptor, we have obtained virtually bioactive conformations of the ligands and three different antagonist-bound, inactive, conformations of the 5-HT2AR. These three 5-HT2AR conformations were further used for docking studies and generation of the bioactive conformations of the data set ligands in each cluster. Subsequently, selected conformers were used for 3D-Quantitative Structure Activity Relationship (3D-QSAR) modelling and pharmacophore analysis. The reliability and predictive power of the created model was assessed using an external test set compounds and showed reasonable external predictability. Statistically significant variables were used to define the most important structural features required for 5-HT2A antagonistic activity. Conclusions obtained from performed ligand-based (3D-QSAR) and target-based (molecular docking and molecular dynamics) methods were compiled and used as guidelines for rational drug design of novel 5-HT2AR antagonists.Communicated by Ramaswamy H. Sarma.

Bicyclic α-Iminophosphonates as High Affinity Imidazoline I2 Receptor Ligands for Alzheimer's Disease.

Imidazoline I2 receptors (I2-IR), widely distributed in the CNS and altered in patients that suffer from neurodegenerative disorders, are orphans from a structural point of view, and new I2-IR ligands are urgently required for improving their pharmacological characterization. We report the synthesis and three-dimensional quantitative structure-activity relationship (3D-QSAR) studies of a new family of bicyclic α-iminophosphonates endowed with relevant affinities for human brain I2-IR. Acute treatment in mice with a selected compound significantly decreased Fas-associated protein with death domain (FADD) in the hippocampus, a key signaling mediator of neuroprotective actions. Additionally, in vivo studies in the familial Alzheimer's disease 5xFAD murine model revealed beneficial effects in behavior and cognition. These results are supported by changes in molecular pathways related to cognitive decline and Alzheimer's disease. Therefore, bicyclic α-iminophosphonates are tools that may open new therapeutic avenues for I2-IR, particularly for unmet neurodegenerative conditions.

Deciphering Imidazoline Off-targets by Fishing in the Class A of GPCR field.

Based on the finding that a central antihypertensive agent with high affinity for I1-type imidazoline receptors - rilmenidine, shows cytotoxic effects on cultured cancer cell lines, it has been suggested that imidazoline receptors agonists might have a therapeutic potential in the cancer therapy. Nevertheless, potential rilmenidine side effects caused by activation of α-adrenoceptors, or other associated receptors and enzymes, might hinder its therapeutic benefits. Considering that human α-adrenoceptors belong to the rhodopsin-like class A of G-protein-coupled receptors (GPCRs) it is reasonable to assume that imidazolines might have the affinity for other receptors from the same class. Therefore, to investigate possible off-target effects of imidazoline ligands we have prepared a reverse docking protocol on class A GPCRs, using imidazoline ligands and their decoys. To verify our in silico results, three ligands with high scores and three ligands with low scores were tested for antagonistic activity on α2 - adrenoceptors.

Human dopamine transporter: the first implementation of a combined in silico/in vitro approach revealing the substrate and inhibitor specificities.

Parkinson's disease (PD) is characterized by the loss of dopamine-generating neurons in the substantia nigra and corpus striatum. Current treatments alleviate PD symptoms rather than exerting neuroprotective effect on dopaminergic neurons. New drugs targeting the dopaminergic neurons by specific uptake through the human dopamine transporter (hDAT) could represent a viable strategy for establishing selective neuroprotection. Molecules able to increase the bioactive amount of extracellular dopamine, thereby enhancing and compensating a loss of dopaminergic neurotransmission, and to exert neuroprotective response because of their accumulation in the cytoplasm, are required. By means of homology modeling, molecular docking, and molecular dynamics simulations, we have generated 3D structure models of hDAT in complex with substrate and inhibitors. Our results clearly reveal differences in binding affinity of these compounds to the hDAT in the open and closed conformations, critical for future drug design. The established in silico approach allowed the identification of promising substrate compounds that were subsequently analyzed for their efficiency in inhibiting hDAT-dependent fluorescent substrate uptake, through in vitro live cell imaging experiments. Taken together, our work presents the first implementation of a combined in silico/in vitro approach enabling the selection of promising dopaminergic neuron-specific substrates.

In silico Methods for Design of Kinase Inhibitors as Anticancer Drugs.

Rational drug design implies usage of molecular modeling techniques such as pharmacophore modeling, molecular dynamics, virtual screening, and molecular docking to explain the activity of biomolecules, define molecular determinants for interaction with the drug target, and design more efficient drug candidates. Kinases play an essential role in cell function and therefore are extensively studied targets in drug design and discovery. Kinase inhibitors are clinically very important and widely used antineoplastic drugs. In this review, computational methods used in rational drug design of kinase inhibitors are discussed and compared, considering some representative case studies.

Synthesis, Molecular Docking and Anticancer Activity of Diflunisal Derivatives as Cyclooxygenase Enzyme Inhibitors.

Cyclooxygenase enzymes play a vital role in inflammatory pathways in the human body. Apart from their relation with inflammation, the additional involvement of COX-2 enzyme with cancer activity was recently discovered. In some cancer types the level of COX-2 enzyme is increased indicating that this enzyme could be a suitable target for cancer therapy. Based on these findings, we have synthesized some new diflunisal thiosemicarbazides and 1,2,4-triazoles and tested them against androgen-independent prostate adenocarcinoma (PC-3), colon carcinoma (HCT-116), human breast cancer (T47D), breast carcinoma (MCF7) and human embryonic kidney (HEK-293) cell lines. Specifically, the diflunisal and thiosemicarbazide functionality are combined during the synthesis of original compounds anticipating a potency enhancement. Compounds 6, 10, 15 and 16 did not show cytotoxic effects for the HEK293 cell line. Among them, compounds 15 and 16 demonstrated anticancer activity for the breast cancer cell line T47D, whereas compounds 6 and 10 which are thiosemicarbazide derivatives displayed anti-tumourigenic activity against the PC-3 cell line, consistent with the literature. However, no activity was observed for the HCT-116 cancer cell line with the tested thiosemicarbazide derivatives. Only compound 16 displayed activity against the HCT-116 cell line. Therefore, it was speculated that the diflunisal and thiosemicarbazide functionalities potentiate anticancer activity on prostate cancer and the thiosemicarbazide functionality decreases the anticancer activity of diflunisal on colon cancer cell lines. In order to gain insight into the anticancer activity and COX-2 inhibition, molecular docking studies were carried out for COX-1 and COX-2 enzymes utilizing the newly synthesized compounds 15, and 16. Both 15 and 16 showed high selectivity and affinity toward COX-2 isozyme over COX-1, which is in agreement with the experimental results.

Synthesis, anticancer activity, and molecular modeling of etodolac-thioether derivatives as potent methionine aminopeptidase (type II) inhibitors.

A series of (R,S)-1-{[5-(substituted)sulfanyl-4-substituted-4H-1,2,4-triazole-3-yl]methyl}-1,8-diethyl-1,3,4,9-tetrahydropyrano[3,4-b]indoles (5a-v) were designed and synthesized using a five-step synthetic protocol that involves substituted benzyl chlorides and (R,S)-5-[(1,8-diethyl-1,3,4,9-tetrahydropyrano[3,4-b]indole-1-yl)methyl]-4-substituted-2,4-dihydro-3H-1,2,4-triazole-3-thiones in the final step. The synthesized derivatives were evaluated for cytotoxicity and anticancer activity in vitro using the MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) colorimetric method against VERO, HEPG2 (human hepatocellular liver carcinoma), SKOV3 (ovarian carcinoma), MCF7 (human breast adenocarcinoma), PC3 and DU145 (prostate carcinoma) cells at 10-5 M (10 µM) for 24 h. Compounds 5d and 5h showed the best biological potency against the SKOV3 cancer cell line (IC50 = 7.22 and 5.10 µM, respectively) and did not display cytotoxicity toward VERO cells compared to etodolac. Compounds 5k, 5s, and 5v showed the most potent biological activity against the PC3 cancer cell line (IC50 = 8.18, 3.10, and 4.00 µM, respectively) and did not display cytotoxicity. Moreover, these compounds were evaluated for caspase-3, -9, and -8 protein expression and activation in the apoptosis pathway for 6, 12, and 24 h, which play a key role in the treatment of cancer. In this study, we also investigated the apoptotic mechanism and molecular modeling of compounds 5k and 5v on the methionine aminopeptidase (type II) enzyme active site in order to get insights into the binding mode and energy.

Drug Design for CNS Diseases: Polypharmacological Profiling of Compounds Using Cheminformatic, 3D-QSAR and Virtual Screening Methodologies.

HIGHLIGHTS Many CNS targets are being explored for multi-target drug designNew databases and cheminformatic methods enable prediction of primary pharmaceutical target and off-targets of compoundsQSAR, virtual screening and docking methods increase the potential of rational drug design The diverse cerebral mechanisms implicated in Central Nervous System (CNS) diseases together with the heterogeneous and overlapping nature of phenotypes indicated that multitarget strategies may be appropriate for the improved treatment of complex brain diseases. Understanding how the neurotransmitter systems interact is also important in optimizing therapeutic strategies. Pharmacological intervention on one target will often influence another one, such as the well-established serotonin-dopamine interaction or the dopamine-glutamate interaction. It is now accepted that drug action can involve plural targets and that polypharmacological interaction with multiple targets, to address disease in more subtle and effective ways, is a key concept for development of novel drug candidates against complex CNS diseases. A multi-target therapeutic strategy for Alzheimer's disease resulted in the development of very effective Multi-Target Designed Ligands (MTDL) that act on both the cholinergic and monoaminergic systems, and also retard the progression of neurodegeneration by inhibiting amyloid aggregation. Many compounds already in databases have been investigated as ligands for multiple targets in drug-discovery programs. A probabilistic method, the Parzen-Rosenblatt Window approach, was used to build a "predictor" model using data collected from the ChEMBL database. The model can be used to predict both the primary pharmaceutical target and off-targets of a compound based on its structure. Several multi-target ligands were selected for further study, as compounds with possible additional beneficial pharmacological activities. Based on all these findings, it is concluded that multipotent ligands targeting AChE/MAO-A/MAO-B and also D1-R/D2-R/5-HT2A -R/H3-R are promising novel drug candidates with improved efficacy and beneficial neuroleptic and procognitive activities in treatment of Alzheimer's and related neurodegenerative diseases. Structural information for drug targets permits docking and virtual screening and exploration of the molecular determinants of binding, hence facilitating the design of multi-targeted drugs. The crystal structures and models of enzymes of the monoaminergic and cholinergic systems have been used to investigate the structural origins of target selectivity and to identify molecular determinants, in order to design MTDLs.

Synthesis and Screening of Human Monoamine Oxidase-A Inhibitor Effect of New 2-Pyrazoline and Hydrazone Derivatives.

A group of 3,5-diaryl-2-pyrazoline and hydrazone derivatives was prepared via the reaction of various chalcones with hydrazide compounds in ethanol. Twenty original compounds were synthesized. Ten of these original compounds have a pyrazoline structure, nine of these original compounds have a hydrazone structure, and one of these original compounds has a chalcone structure. Structural elucidation of the compounds was performed by IR, (1)H NMR, (13)C NMR, mass spectral data, and elemental analyses. These compounds were tested for their inhibitory activities toward the A and B isoforms of human monoamine oxidase (MAO). Except for 3k and 6c, all compounds were found to be competitive, reversible, and selective inhibitors for either one of the isoforms (hMAO-A or MAO-B). Compounds 3k and 6c were found to be competitive, reversible, but non-selective MAO inhibitors. Compound 6h showed hMAO-B inhibitory activity whereas the others potently inhibited hMAO-A. Compound 5c showed higher selectivity than the standard drug moclobemide. According to the experimental K(i) values, compounds 6i, 6d, and 6a exhibited the highest inhibitory activity toward hMAO-A. The AutoDock 4.2 program was employed to perform automated molecular docking. The calculated results obtained computationally were in good agreement with the experimental values.