Pharmacophore filtering and 3D-QSAR in the discovery of new JAK2 inhibitors

Department of Bioinformatics, Alagappa University, Karaikudi 630003, Tamil Nadu, India.
Journal of molecular graphics & modelling (Impact Factor: 2.02). 07/2011; 30:186-97. DOI: 10.1016/j.jmgm.2011.07.004
Source: PubMed

ABSTRACT Janus kinase 2 (JAK2) plays a crucial role in the patho-mechanism of cardiovascular pathologies, myeloproliferative disorders and many other diseases. Thus, effective JAK2 kinase inhibitors may be of significant therapeutic importance. In this study, a pharmacophore mapping studies were undertaken for a series of phenylaminopyrimidines derivatives. A five point pharmacophore with two hydrogen bond donors (D), two hydrogen bond acceptors (A) and one aromatic ring (R) as pharmacophoric features were developed. The pharmacophore hypothesis yielded a statistically significant 3D-QSAR model, with a correlation coefficient of R²=0.970 for training set compounds. The model generated showed excellent predictive power, with a correlation coefficient of Q²=0.822. The external validation indicated that our QSAR models possessed high predictive powers with r²(0) value of 0.999 and r²(m) value of 0.637 respectively. The model was then employed as 3D search query to screen against public compound libraries (Asinex, TOSLab, Maybride and Binding database) in-order to identify a new scaffold. We have identified thirteen distinct drug-like molecules binding to the JAK2. Interestingly, some of the compounds show activity against JAK2 by PASS biological activity prediction. Hence, these molecules could be potential selective inhibitors of JAK2 that can be experimentally validated and their backbone structural scaffold could serve as building blocks in designing drug-like molecules for JAK2.

  • [Show abstract] [Hide abstract]
    ABSTRACT: SIRT1 is a NAD+-dependent deacetylase that involved in various important metabolic pathways. Combined ligand and structure-based approach was utilized for identification of SIRT1 activators. Pharmacophore models were developed using DISCOtech and refined with GASP module of Sybyl X software. Pharmacophore models were composed of two hydrogen bond acceptor (HBA) atoms, two hydrogen bond donor (HBD) sites and one hydrophobic (HY) feature. The pharmacophore models were validated through receiver operating characteristic (ROC) and Güner–Henry (GH) scoring methods. Model-2 was selected as best model among the model 1–3, based on ROC and GH score value, and found reliable in identification of SIRT1 activators. Model-2 (3D search query) was searched against Zinc database. Several compounds with different chemical scaffold were retrieved as hits. Currently, there is no experimental SIRT1 3D structure available, therefore, we modeled SIRT1 protein structure using homology modeling. Compounds with Qfit value of more than 86 were selected for docking study into the SIRT1 homology model to explore the binding mode of retrieved hits in the active allosteric site. Finally, in silico ADMET prediction study was performed with two best docked compounds. Combination of ligand and structure-based modeling methods identified active hits, which may be good lead compounds to develop novel SIRT1 activators.
    Chemico-Biological Interactions 01/2015; 228. DOI:10.1016/j.cbi.2015.01.001 · 2.98 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Tankyrase 1 and 2 (TNKS) are promising and attractive therapeutic targets in anticancer drug development. Herein, we report the findings of structure and ligand based virtual screening for novel TNKS1 inhibitors using iterative rounds of in silico studies and subsequent biological evaluation methods. Upon screening of three compound databases, a final set of five molecules were selected for experimental validation. In order to prove our in silico findings, tankyrase activity was assessed by a calorimetric assay with identified five lead molecules. Out of five, C1 (7309981) showed significant inhibition of TNKS1 enzyme. Further, toxicity of the final hit compounds were measured using cytotoxicity experiments and inhibition of cell growth is more pronounced in C1 followed by C5 and C3 (7309981>7245236>7275738). The morphological assessment, DNA damage and chromatin condensation and fragmentation results are also confirms that C1 has enhanced activity against MCF-7 cells.
    Molecular BioSystems 07/2014; 10(10). DOI:10.1039/C4MB00309H · 3.18 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The Janus-associated kinase 2 (JAK2) V617F mutation is believed to play a critical role in the pathogenesis of polycythemia vera, essential thrombocythemia, and idiopathic myelofibrosis. The discovery of activating mutations associated with inhibition of cascade of events mediated by JAK2 target became an attractive approach for the treatment of myeloproliferative disorder. In this study, we performed a ligand-based pharmacophore modeling to explore the important chemical features of JAK2 inhibitors. The top ten hypotheses were generated based on 47 known inhibitors of JAK2 using PHASE module of Schrodinger software. The best pharmacophore hypothesis was found to be AADDR.212 which consists of two acceptors, two donors and one ring aromatic group. The selected model was validated by survival score, selectivity, and GH score. Two types of validation studies were done which includes potency validation by virtual screening against set of decoys, and selectivity validation by screening against set of inhibitors of JAK1, JAK2, JAK3, and Tyk2 (all tyrosine kinase family proteins). The selected model was utilized as a 3D query to screen against ZINC natural and chemical database, and subsequently the screened compounds were filtered by applying the Lipinski’s rule of five, ADME properties and molecular docking. Finally, fifteen compounds were obtained as novel virtual hits to inhibit the JAK2 enzyme
    Medicinal Chemistry Research 08/2014; 24(4). DOI:10.1007/s00044-014-1223-6 · 1.61 Impact Factor