Design and Synthesis of Quinazolinone-Triazole Hybrids as Potent Anti-Tubercular Agents.

A straightforward and convenient methodology has been developed for the reaction of 2-aminobenzamide and carbonyls affording 2,3-dihydroquinazolin-4(1H)-ones using aqueous solution of [C12Py][FeCl3Br]. The developed methodology was applied for the synthesis of 25 quinazolinone-triazole hybrids followed by evaluation of their in vitro anti-tubercular (TB) activity. The results revealed that 8 quinazolinone-triazole hybrids displayed promising activity having MIC values of 0.78-12.5 µg/mL. The compound 3if with MIC 0.78 µg/mL was found to be the lead nominee among the series, better than Ethambutol, a first line anti-TB drug and comparable with Rifampicin. The active compounds with MIC values ≤ 6.25 µg/mL were subjected to in vitro cytotoxicity and found nontoxic. In drug-drug interaction, compounds 3ia and 3ii interacted synergistically with all the three anti-TB drugs, INH, RFM, and EMB. Other 3 compounds interacted either in synergistic or additive manners. Important information on the binding interaction of the target compounds with the active sites of 1DQY Antigen 85C from Mycobacterium tuberculosis and Enoyl acyl carrier protein reductase (InhA) enzymes was obtained from molecular docking studies. Screening of the drug-likeness properties and bioactivity score indicates that synthesized molecules could be projected as potential drug candidates. Based on the current study, quinazolinone-triazole hybrids framework can be useful in drug development for TB.

A Simple Work-Up-free, Solvent-free Approach to Novel Amino Acid Linked 1,4-Disubstituted 1,2,3-Triazoles as Potent Antituberculosis Agents.

An efficient, green strategy for synthesis of 1,4-disubstituted-1,2,3-triazole has been developed using 1,8-diazabicyclo[5.4.0]undec-7-ene (DBU) acetate ionic liquid (200 µL) under a solvent- and external base-free condition. This protocol is further applied for the synthesis of novel amino acid containing 1,2,3-triazole molecules, which were then evaluated for potential antitubercular and antibacterial activities. Cytotoxicity assay of the compounds was also performed. In silico analysis of the promising compounds selected through experimental analysis was thereafter performed for visualizing molecular interactions and predicting binding affinities between our synthesized molecules, which exhibited good activity in experimental studies and the DprE1 target protein of Mycobacterium tuberculosis. Durg-likeness studies also show potential of the synthesized molecules as drug candidates.

Identification of novel human renin inhibitors through a combined approach of pharmacophore modelling, molecular DFT analysis and in silico screening.

Renin is an aspartyl protease of the renin-angiotensin system (RAS) and the first enzyme of the biochemical pathway for the generation of angiotensin II - a potent vasoconstrictor involved in the maintenance of cardiovascular homeostasis and the regulation of blood pressure. High enzymatic specificity of renin and its involvement in the catalysis of the rate-limiting step of the RAS hormone system qualify it as a good target for inhibition of hypertension and other associated diseases. Ligand-based pharmacophore model (Hypo1) was generated from a training set of 24 compounds with renin inhibitory activity. The best hypothesis consisted of one Hydrogen Bond Acceptor (HBA), three Hydrophobic Aliphatic (HY-Al) and one Ring Aromatic (AR) features. This well-validated pharmacophore hypothesis (correlation coefficient 0.95) was further utilized as a 3D query to screen database compounds, which included structures from two natural product repositories. These screened compounds were further analyzed for drug-likeness and ADMET studies. The compounds which satisfied the qualifying criteria were then subjected to molecular docking and Density Functional Theory (DFT) analysis in order to discern their atomic level interactions at the active site of the 3D structure of rennin. The pharmacophore-based modelling that has been used to generate the novel findings of the present study would be an avant-garde approach towards the development of potent inhibitors of renin.

Novel butyrylcholinesterase inhibitors through pharmacophore modeling, virtual screening and DFT-based approaches along-with design of bioisosterism-based analogues.

Ligand and structure-based pharmacophore models were used to identify the important chemical features of butyrylcholinesterase (BChE) inhibitors. A training set of 16 known structurally diverse compounds with a wide range of inhibitory activity against BChE was used to develop a quantitative ligand-based pharmacophore (Hypo1) model to identify novel BChE inhibitors in virtual screening databases. A structure-based pharmacophore hypothesis (Phar1) was also developed with the ligand-binding site of BChE in consideration. Further, the models were validated using test set, Fisher's Randomization and Leave-one-out validation methods. Well-validated pharmacophore hypotheses were further used as 3D queries in virtual screening and 430 compounds were finally selected for molecular docking analysis. Subsequently, ADMET, DFT and chemical similarity search were employed to narrow down on seven compounds as potential drug candidates. Analogues of the best hit were further developed through a bioisosterism-guided approach to further generate a library of potential BChE inhibitors.

3D pharmacophore-based virtual screening, docking and density functional theory approach towards the discovery of novel human epidermal growth factor receptor-2 (HER2) inhibitors.

Human epidermal growth factor receptor 2 (HER2) is one of the four members of the epidermal growth factor receptor (EGFR) family and is expressed to facilitate cellular proliferation across various tissue types. Therapies targeting HER2, which is a transmembrane glycoprotein with tyrosine kinase activity, offer promising prospects especially in breast and gastric/gastroesophageal cancer patients. Persistence of both primary and acquired resistance to various routine drugs/antibodies is a disappointing outcome in the treatment of many HER2 positive cancer patients and is a challenge that requires formulation of new and improved strategies to overcome the same. Identification of novel HER2 inhibitors with improved therapeutics index was performed with a highly correlating (r=0.975) ligand-based pharmacophore model (Hypo1) in this study. Hypo1 was generated from a training set of 22 compounds with HER2 inhibitory activity and this well-validated hypothesis was subsequently used as a 3D query to screen compounds in a total of four databases of which two were natural product databases. Further, these compounds were analyzed for compliance with Veber's drug-likeness rule and optimum ADMET parameters. The selected compounds were then subjected to molecular docking and Density Functional Theory (DFT) analysis to discern their molecular interactions at the active site of HER2. The findings thus presented would be an important starting point towards the development of novel HER2 inhibitors using well-validated computational techniques.

An In Silico Approach for Identification of Potential Anti-Mycobacterial Targets of Vasicine and Related Chemical Compounds.

Tuberculosis (TB) is known to mankind as one of the most pervasive and persistent of diseases since the early days of civilization. The growing resistance of the causative pathogen Mycobacterium tuberculosis to the standard drug regimen for TB poses further difficulty in its treatment and control. Screening of novel plant-derived compounds with promising anti-tubercular activity has been cited as a prospective route for new anti-tubercular drug discovery and design. Justicia adhatoda L. is a perennial evergreen shrub which is widely mentioned in scientific literature on account of its potent anti-mycobacterial properties. In the present study, we have employed a series of computational methodologies to reveal the probable molecular interactions of vasicine, the principal alkaloid of Justicia adhatoda L., and two of its close natural derivatives- vasicinone and deoxyvasicine, with certain biological targets in M. tuberculosis. Targets were identified from literature and through a reverse Pharmacophore-based approach. Subsequent comparative molecular docking to identify the best ligand-target interactions revealed Antigen 85C of M. tuberculosis as the most potent biological target of vasicine on the basis of optimum molecular docking values. A chemogenomics approach was also employed to validate the molecular interactions between the same class of chemical compounds as vasicine and Antigen 85C. Further, a library of structural analogs of vasicine was created by bioiosterism-based drug design to identify structural analogs with better inhibitory potential against Antigen 85C.