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: 1.72). 07/2011; 30:186-97. DOI: 10.1016/j.jmgm.2011.07.004
Source: PubMed


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.

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    • "The survival score of this model was 3.728, and GH score for the same model was recorded as 0.748. Previously, Singh et al. (2011) were developed Pharmacophore-based 3D- QSAR model by using phenylaminopyrimidines derivatives , their results indicated that five features were important for the activity such as two hydrogen bond donors, two hydrogen bond acceptors, and one aromatic ring groups. In our work, the generated pharmacophore model shows similar features; additionally the model was validated based on the selectivity issues. "
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