Abstract
Aurora kinases belong to family of highly conserved serine/threonine protein kinases that are involved in diverse cell cycle events and play a major role in regulation of cell division. Abnormal expression of Aurora kinases may lead to cancer; hence, these are considered as a potential target in cancer treatment. In this research article, we identified three novel Aurora A inhibitors using modern computational tools. A four-point common 3D pharmacophore hypothesis of Aurora A (AurA) inhibitors was developed using a diverse set of 55 thienopyrimidine derivatives. A three-dimensional quantitative structure–activity relationship (3D-QSAR) study was carried out using atom-based alignment of diverse set of 55 molecules to evaluate the structure– activity relationships. Docking and 3D-QSAR studies were performed with the 3D structure of AurA to evaluate the generated pharmacophore. The pharmacophore model and 3D-QSAR results complemented the results of our docking study. The pharmacophore hypothesis, which yields the best results, was used to screen the Zinc ‘clean drug-like’ database. Various database filters such as 3D-arrangement of pharmacophoric features, predicted activity and binding interaction score were used to retrieve hits having potential AurA inhibition activity.
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This work was supported by the Council of Scientific and Industrial Research- Unit for Research and Development of Information Products. S.R.C thanks the Centre for Development of Advanced Computing (CDAC) Bioinformatics Resource and Application Facility, Pune for computational facility.
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Chavan, S.R., Dash, R.C., Alam, M.S. et al. Identification of new novel scaffold for Aurora A inhibition by pharmacophore modeling and virtual screening. Mol Divers 18, 853–863 (2014). https://doi.org/10.1007/s11030-014-9535-5
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DOI: https://doi.org/10.1007/s11030-014-9535-5