New Quinolinyl–1,3,4–Oxadiazoles: Synthesis, In Vitro Antibacterial, Antifungal and Antituberculosis Studies
Author(s): Rahul V. Patel, Premlata Kumari and Kishor H. Chikhalia
Affiliation: Department of Applied Chemistry, S. V. National Institute of Technology, Surat–395007, Gujarat, India.
In order to generate hybrid antimicrobial remedies with novel mode of action, two series of quinoline based 1,3,4-oxadiazole derivatives condensed with N-aryl/benzothiazolyl acetamides were synthesized and the MIC values of the compounds towards eight reference bacterial strains (S. aureus, B. cereus, E. coli, P. aeruginosa, K. pneumoniae, S. typhi, P. vulgaris, S. flexneri), four fungi (A. niger, A. fumigatus, A. clavatus, C. albicans) and Mycobacterium tuberculosis H37Rv were assayed in vitro. Quinoline–6–carboxlic acid was treated with thionyl chloride in refluxing methanol to obtain the corresponding ester derivative to be hydrazinolyzed by 99% hydrazine hydrate in ethanol to produce carbohydrazide intermediate. The carbohydrazide precursor underwent cyclization by carbon disulfide and ethanolic KOH to construct 5–quinolinyl–6–yl–1,3,4–oxadiazol–2–thiol. Substituted 2–chloro–N–phenyl(benzothiazolyl)aceta-mide derivatives were then condensed to 1,3,4-oxadiazole nucleus via sulphur linkage to yield the desired products. Target products bearing N–benzothiazolyl–2–chloroacetamides displayed good inhibitory potential. The biological screening identified that many final analogues exhibited a significant inhibition of the growth of microorganisms at 3.12-25 μg/mL of MIC, which were comparable to control drugs. The influence of the presence of various functional groups to the phenyl/benzothiazolyl ring on activity profiles was investigated. The proposed structures of the newly prepared products were confirmed with the aid of IR, 1H NMR, 13C NMR spectroscopy and elemental analysis. These results may provide new insights in the design of a novel pool of bioactive templates.
A Combination of 3D-QSAR Modeling and Molecular Docking Approach for the Discovery of Potential HIF Prolyl Hydroxylase Inhibitors
Author(s): Mahesh Kumar Teli and Rajanikant Golgodu Krishnamurthy
Affiliation: School of Biotechnology Coordinator, Bioinformatics Centre National Institute of Technology Calicut Calicut – 673601, Kerala, India.
Suppression of HIF prolyl hydroxylase (PHD) activity by small molecule inhibitors leads to the stabilization of HIF and offers a potential therapeutic option for treating ischemic disorders. In this study, pharmacophore based QSAR modeling, virtual screening and molecular docking approaches were concurrently used to identify target-specific PHD inhibitors with better ADME properties and to readily minimize false positives and false negatives. A 3D-QSAR based method was used to generate a pharmacophore hypothesis (AAAN). The obtained 3D-QSAR model has an excellent correlation coefficient value (r2 = 0.99), Fisher ratio (F = 386) and exhibited good predictive power (q2 = 0.64). The hypothesis was validated and utilized for chemical database screening and the retrieved compounds were subjected to molecular docking for further refinement. Quantitative AAAN hypothesis comprised three H-bond accepter and one negative ionizable group feature and it give good predictive ability because all the QSAR information it was providing matched with the active site information. The hypothesis was validated and used as a 3D query for database screening. After manual selection, molecular docking and further refinement, based on the molecular interactions of inhibitors with the essential amino acids residues, 12 candidates with good ADME and blood brain barrier permeability values were selected as potential PHD inhibitors.
Modeling of LIM-Kinase 2 Inhibitory Activity of Pyrrolopyrimidine Analogues: Useful in Treatment of Ocular Hypertension and Glaucoma
Author(s): Gagandip Singh, Manish K. Gupta, Viney Kumar and Yenamandra S. Prabhakar
Affiliation: Molecular Modeling and Pharmacoinformatics Lab, Department of Pharmaceutical Chemistry, ISF College of Pharmacy, Moga-142001, India.
The LIM-Kinase 2 (LIMK2) inhibitory activity of a series of pyrrolopyrimidine analogs has been analyzed through combinatorial protocol in multiple linear regressions (CP-MLR) and partial least square (PLS) using different descriptors obtained from DRAGON software. The empirical, topological and charge descriptors have led to statistically significant QSAR models and showed good external predictivity as reflected in test set R2 values (0.782 to 0.888). The obtained structure-activity correlations underlined the significance of bulkiness and molecular polarizability in improving the activity. The topological descriptors suggested that open chain or branched substituents are favorable while cyclic /ring substituents are unfavorable for the activity. The descriptors identified in the study showed that pyrrolopyrimidine scaffold holds scope for modulating LIMK2 inhibitory activity. The study gives a direction for further exploration of chemical space of pyrrolopyrimidine analogs as LIMK2 inhibitors.
Variable Selection Based QSAR Modeling on Bisphenylbenzimidazole as Inhibitor of HIV-1 Reverse Transcriptase
Author(s): Surendra Kumar and Meena Tiwari
Affiliation: Computer Aided Drug Design Lab, Department of Pharmacy, Shri G. S. Institute of Technology and Science, 23, Park Road, Indore-452003, (M.P.), India.
The emergence of mutant virus in drug therapy for HIV-1 infection has steadily risen in the last decade. Inhibition of reverse transcriptase enzyme has emerged as a novel target for the treatment of HIV infection. The aim to decipher the structural features that interact with receptor, we report a quantitative structure activity relationship (QSAR) study on a dataset of thirty seven compounds belonging to bisphenylbenzimidazoles (BPBIs) as reverse transcriptase inhibitors using enhanced replacement method (ERM), stepwise multiple linear regression (Stepwise-MLR) and genetic function approximation (GFA) method for selecting a subset of relevant descriptors, developing the best multiple linear regression model and defining the QSAR model applicability domain boundaries. The enhanced replacement method was found to give better results r2=0.8542, Q2(loo) = 0.7917, r2pred = 0.7812) at five variables as compared to stepwise MLR and GFA method, evidenced by internal and external validation parameters. The modified r2 (r2m) of the training set, test set and whole data set were calculated and are in agreement with the enhanced replacement method. The results of QSAR study rationalize the structural requirement for optimum binding of ligands. The developed QSAR model shows that hydrophobicity, flexibility, three dimensional surface area, volume and shape of molecule are important parameters to be considered for designing new compounds and to decipher reverse transcriptase enzyme inhibition activity of these compounds at molecular level. The applicability domain was defined to find the similar analogs with better prediction power.