New nimesulide derivatives with amide/sulfonamide moieties: Selective COX-2 inhibition and antitumor effects.

Seventeen new amide/sulfonamide containing nimesulide derivatives were synthesized and characterized by several spectroscopic techniques and primarily investigated for their inhibitory potential on COX enzymes and other pro-inflammatory factors. Experimental analyses showed that among seventeen compounds, N8 and N10 have remarkable potency and selectivity for the COX-2 enzyme over COX-1 at very low doses as compared to nimesulide. Moreover, both N8 and N10 selectively reduced the Lipopolysaccharide (LPS)-stimulated COX-2 mRNA expression level while the COX-1 level remained stable. Both PGE2 release and nitric oxide production in macrophage cells were significantly suppressed by the N8 and N10 treatment groups. In silico ADME/Tox, molecular docking and molecular dynamics (MD) simulations were also conducted. Additionally, all compounds were also screened in a panel of cancer cell lines for their antiproliferative properties by MTT and SRB assays. Compound N17 exhibited a considerable antiproliferative effect on the colon (IC50: 9.24 µM) and breast (IC50: 11.35 µM) cancer cell lines. N17 exposure for 48 h decreased expression of anti-apoptotic protein BCL-2 and increased the expression of apoptogenic BAX. Besides, the BAX/BCL-2 ratio was increased with visible ultrastructural changes and apoptotic bodies under scanning electron microscopy. In order to investigate the structural and dynamical properties of selected hits on the target structures, multiscale molecular modeling studies are also conducted. Our combined in silico and in vitro results suggest that N8 and N10 could be further developed as potential nonsteroidal anti-inflammatory drugs (NSAIDs), while cytotoxic N17 might be studied as a potential lead compound that could be developed as an anticancer agent.

Bis benzothiophene Schiff bases: synthesis and in silico-guided biological activity studies.

Since benzo [ b ] thiophene scaffold is one of the privileged structures in drug discovery as this core exhibitsactivities for different biological problems, in this study bis (benzo[ b ]thiophene-2-yl) alkyl methanimine derivatives (1-9) were synthesized by reacting benzo[ b ]thiophene-2-carbaldehyde with diamines. All newly compounds were characterized by IR, 1H NMR and 13C NMR spectroscopic methods. Synthesized compounds were investigated using binary QSARbased models on therapeutic activity prediction of synthesized compounds and they showed high predicted activities in following diseases: bacterial, angina, allergy, depression and obesity. Thus, they were then tested for their antimicrobial and antileishmanial activities as a result of this theoretical study. Compound 1(N, N'- (propane-1,3-diyl) bis (1-(benzo [ b ] thiophene-2-yl)) methanimine) was found the most active compound in both diseases. Thus, its molecular docking studies were also carried out.

Physics-driven identification of clinically approved and investigation drugs against human neutrophil serine protease 4 (NSP4): A virtual drug repurposing study.

Neutrophils synthesize four immune associated serine proteases: Cathepsin G (CTSG), Elastase (ELANE), Proteinase 3 (PRTN3) and Neutrophil Serine Protease 4 (NSP4). While previously considered to be immune modulators, overexpression of neutrophil serine proteases correlates with various disease conditions. Therefore, identifying novel small molecules that can potentially control or inhibit the proteolytic activity of these proteases is crucial to revert or temper the aggravated disease phenotype. To the best of our knowledge, although there is limited data for inhibitors of other neutrophil protease members, there is no previous clinical study of a synthetic small molecule inhibitor targeting NSP4. In this study, an integrated molecular modeling algorithm was performed within a virtual drug repurposing study to identify novel inhibitors for NSP4, using clinically approved and investigation drugs library (∼8000 compounds). Based on our rigorous filtration, we found that following molecules Becatecarin, Iogulamide, Delprostenate and Iralukast are predicted to block the activity of NSP4 by interacting with core catalytic residues. The selected ligands were energetically more favorable compared to the reference molecule. The result of this study identifies promising molecules as potential lead candidates.

Integrating Ligand and Target-Driven Based Virtual Screening Approaches With in vitro Human Cell Line Models and Time-Resolved Fluorescence Resonance Energy Transfer Assay to Identify Novel Hit Compounds Against BCL-2.

Antiapoptotic members of B-cell leukemia/lymphoma-2 (BCL-2) family proteins are one of the overexpressed proteins in cancer cells that are oncogenic targets. As such, targeting of BCL-2 family proteins raises hopes for new therapeutic discoveries. Thus, we used multistep screening and filtering approaches that combine structure and ligand-based drug design to identify new, effective BCL-2 inhibitors from a small molecule database (Specs SC), which includes more than 210,000 compounds. This database is first filtered based on binary "cancer-QSAR" model constructed with 886 training and 167 test set compounds and common 26 toxicity quantitative structure-activity relationships (QSAR) models. Predicted non-toxic compounds are considered for target-driven studies. Here, we applied two different approaches to filter and select hit compounds for further in vitro biological assays and human cell line experiments. In the first approach, a molecular docking and filtering approach is used to rank compounds based on their docking scores and only a few top-ranked molecules are selected for further long (100-ns) molecular dynamics (MD) simulations and in vitro tests. While docking algorithms are promising in predicting binding poses, they can be less prone to precisely predict ranking of compounds leading to decrease in the success rate of in silico studies. Hence, in the second approach, top-docking poses of each compound filtered through QSAR studies are subjected to initially short (1 ns) MD simulations and their binding energies are calculated via molecular mechanics generalized Born surface area (MM/GBSA) method. Then, the compounds are ranked based on their average MM/GBSA energy values to select hit molecules for further long MD simulations and in vitro studies. Additionally, we have applied text-mining approaches to identify molecules that contain "indol" phrase as many of the approved drugs contain indole and indol derivatives. Around 2700 compounds are filtered based on "cancer-QSAR" model and are then docked into BCL-2. Short MD simulations are performed for the top-docking poses for each compound in complex with BCL-2. The complexes are again ranked based on their MM/GBSA values to select hit molecules for further long MD simulations and in vitro studies. In total, seven molecules are subjected to biological activity tests in various human cancer cell lines as well as Time-Resolved Fluorescence Resonance Energy Transfer (TR-FRET) assay. Inhibitory concentrations are evaluated, and biological activities and apoptotic potentials are assessed by cell culture studies. Four molecules are found to be limiting the proliferation capacity of cancer cells while increasing the apoptotic cell fractions.

Combinatorial peptide library screening for discovery of diverse α-glucosidase inhibitors using molecular dynamics simulations and binary QSAR models.

Human α-glucosidase is an enzyme involved in the catalytic cleavage of the glucoside bond and involved in numerous functionalities of the organism, as well as in the insurgence of diabetes mellitus 2 and obesity. Thus, developing chemicals that inhibit this enzyme is a promising approach for the treatment of several pathologies. Small peptides such as di- and tri-peptides may be in natural organism as well as in the GI tract in high concentration, coming from the digestive process of meat, wheat and milk proteins. In this work, we reported the first tentative hierarchical structure-based virtual screening of peptides for human α-glucosidase. The goal of this work is to discover novel and diverse lead compounds that my act as inhibitors of α-glucosidase such as small peptides by performing a computer aided virtual screening and to find novel scaffolds for further development. Thus, in order to select novel candidates with original structure we performed molecular dynamics (MD) simulations among the 12 top-ranked peptides taking as comparison the MD simulations performed on crystallographic inhibitor acarbose. The compounds with the lower RMSD variability during the MD, were reserved for in vitro biological assay. The selected 4 promising structures were prepared on solid phase peptide synthesis and used for the inhibitory assay, among them compound 2 showed good inhibitory activity, which validated our method as an original strategy to discover novel peptide inhibitors. Moreover, pharmacokinetic profile predictions of these 4 peptides were also carried out with binary QSAR models using MetaCore/MetaDrug applications.

Novel tumor necrosis factor-α (TNF-α) inhibitors from small molecule library screening for their therapeutic activity profiles against rheumatoid arthritis using target-driven approaches and binary QSAR models.

Tumor necrosis factor alpha (TNF-α) is a multifunctional cytokine that acts as a central biological mediator for critical immune functions, including inflammation, infection, and antitumor responses. It plays pivotal role in autoimmune diseases like rheumatoid arthritis (RA). The synthetic antibodies etanercept, infliximab, and adalimumab are approved drugs for the treatment of inflammatory diseases bind to TNF-α directly, preventing its association with the tumor necrosis factor receptor (TNFR). These biologics causes serious side effects such as triggering an autoimmune anti-antibody response or the weakening of the body's immune defenses. Therefore, alternative small-molecule based therapies for TNF-α inhibition is a hot topic both in academia and industry. Most of small-molecule inhibitors reported in the literature target TNF-α, indirectly. In this study, combined in silico approaches have been applied to better understand the important direct interactions between TNF-α and small inhibitors. Our effort executed with the extensive literature review to select the compounds that inhibit TNF-α. High-throughput structure-based and ligand-based virtual screening methods are applied to identify TNF-α inhibitors from 3 different small molecule databases (∼256.000 molecules from Otava drug-like green chemical collection, ∼ 500.000 molecules from Otava Tangible database, ∼2.500.000 Enamine small molecule database) and ∼240.000 molecules from ZINC natural products libraries. Moreover, therapeutic activity prediction, as well as pharmacokinetic and toxicity profiles are also investigated using MetaCore/MetaDrug platform which is based on a manually curated database of molecular interactions, molecular pathways, gene-disease associations, chemical metabolism and toxicity information, uses binary QSAR models. Particular therapeutic activity and toxic effect predictions are based on the ChemTree ability to correlate structural descriptors to that property using recursive partitioning algorithm. Molecular Dynamics (MD) simulations were also performed for selected hits to investigate their detailed structural and dynamical analysis beyond docking studies. As a result, at least one hit from each database were identified as novel TNF-α inhibitors after comprehensive virtual screening, multiple docking, e-Pharmacophore modeling (structure-based pharmacophore modeling), MD simulations, and MetaCore/MetaDrug analysis. Identified hits show predicted promising anti-arthritic activity and no toxicity. Communicated by Ramaswamy H. Sarma.

Proposing Novel MAO-B Hit Inhibitors Using Multidimensional Molecular Modeling Approaches and Application of Binary QSAR Models for Prediction of Their Therapeutic Activity, Pharmacokinetic and Toxicity Properties.

Monoamine oxidase (MAO) enzymes MAO-A and MAO-B play a critical role in the metabolism of monoamine neurotransmitters. Hence, MAO inhibitors are very important for the treatment of several neurodegenerative diseases such as Parkinson's disease (PD), Alzheimer's disease (AD), and amyotrophic lateral sclerosis (ALS). In this study, 256 750 molecules from Otava Green Chemical Collection were virtually screened for their binding activities as MAO-B inhibitors. Two hit molecules were identified after applying different filters such as high docking scores and selectivity to MAO-B, desired pharmacokinetic profile predictions with binary quantitative structure-activity relationship (QSAR) models. Therapeutic activity prediction as well as pharmacokinetic and toxicity profiles were investigated using MetaCore/MetaDrug platform which is based on a manually curated database of molecular interactions, molecular pathways, gene-disease associations, chemical metabolism, and toxicity information. Particular therapeutic activity and toxic effect predictions are based on the ChemTree ability to correlate structural descriptors to that property using recursive partitioning algorithm. Molecular dynamics (MD) simulations were also performed to make more detailed assessments beyond docking studies. All these calculations were made not only to determine if studied molecules possess the potential to be a MAO-B inhibitor but also to find out whether they carry MAO-B selectivity versus MAO-A. The evaluation of docking results and pharmacokinetic profile predictions together with the MD simulations enabled us to identify one hit molecule (ligand 1, Otava ID: 3463218) which displayed higher selectivity toward MAO-B than a positive control selegiline which is a commercially used drug for PD therapeutic purposes.

Integration of multi-scale molecular modeling approaches with experiments for the in silico guided design and discovery of novel hERG-Neutral antihypertensive oxazalone and imidazolone derivatives and analysis of their potential restrictive effects on cell proliferation.

AT1 antagonists is the most recent drug class of molecules against hypertension and they mediate their actions through blocking detrimental effects of angiotensin II (A-II) when acts on type I (AT1) A-II receptor. The effects of AT1 antagonists are not limited to cardiovascular diseases. AT1 receptor blockers may be used as potential anti-cancer agents - due to the inhibition of cell proliferation stimulated by A-II. Therefore, AT1 receptors and the A-II biosynthesis mechanisms are targets for the development of new synthetic drugs and therapeutic treatment of various cardiovascular and other diseases. In this work, multi-scale molecular modeling approaches were performed and it is found that oxazolone and imidazolone derivatives reveal similar/better interaction energy profiles compared to the FDA approved sartan molecules at the binding site of the AT1 receptor. In silico-guided designed hit molecules were then synthesized and tested for their binding affinities to human AT1 receptor in radioligand binding studies, using [125I-Sar1-Ile8] AngII. Among the compounds tested, 19d and 9j molecules bound to receptor in a dose response manner and with relatively high affinities. Next, cytotoxicity and wound healing assays were performed for these hit molecules. Since hit molecule 19d led to deceleration of cell motility in all three cell lines (NIH3T3, A549, and H358) tested in this study, this molecule is investigated in further tests. In two cell lines (HUVEC and MCF-7) tested, 19d induced G2/M cell cycle arrest in a concentration dependent manner. Adherent cells detached from the plates and underwent cell death possibly due to apoptosis at 19d concentrations that induced cell cycle arrest.