Shuffling multivariate adaptive regression splines as a predictive method for modeling of novel pyridylmethylthio deriva
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Med Chem Res (2013) 22:2645–2653 DOI 10.1007/s00044-012-0266-9
ORIGINAL RESEARCH
Shuffling multivariate adaptive regression splines as a predictive method for modeling of novel pyridylmethylthio derivatives as VEGFR2 inhibitors M. Asadollahi-Baboli • A. Mani-Varnosfaderani
Received: 4 April 2012 / Accepted: 28 September 2012 / Published online: 9 October 2012 Ó Springer Science+Business Media New York 2012
Abstract The vascular endothelial growth factor receptor (VEGFR2) is an attractive target for the development of novel anticancer agents. Molecular docking and quantitative structure–activity relationship (QSAR) were used to investigate how inhibitors’ chemical structures relate to the inhibitory activities. The molecular docking studies show that at least one hydrogen bond with LYS866 residue is one of the essential requirements for the optimum binding of a series of 42 pyridylmethylthio inhibitors. The obtained QSAR model indicates that the inhibitory activity can be described by solvent-accessible molecular surface area, topological electronic indices, local dipole index, steric interaction, and hydrogen bonding energies between the receptor and the inhibitors. Furthermore, several validation methods were used to evaluate the predictive capacity of the generated models. The satisfactory results (R2L25 %O = 0.819, Q2LOO = 0.838, R2p = 0.866, RMSELOO = 0.315, and RMSEL25 %O = 0.337) suggest that the models exhibited considerable predictive power which can be used in prediction of activity of new pyridylmethylthio inhibitors. Also the docking analysis showed that the interaction of the inhibitors with residues ALA879, ASP(1044, 1026), LEU880, PHE843, and LYS866 plays an important role in the activities of the inhibitors.
M. Asadollahi-Baboli (&) Department of Science, Babol University of Technology, PO Box 47148-71167, Babol, Mazandaran, Iran e-mail: [email protected] A. Mani-Varnosfaderani Department of Chemistry and Biochemistry, University of Berne, Freiestrasse 3, 3012 Berne, Switzerland
Keywords Molecular docking simulation Vascular endothelial growth factor receptor Shuffling multivariate adaptive regression splines Least squares support vector regression Pyridylmethylthio derivatives
Introduction Angiogenesis, the process of blood vessel sprouting, generating new capillaries from existing vasculature, is a normal process for organ development during embryogenesis, wound healing, and menstrual cycle. On the other hand, it has been shown that angiogenesis is a rate-limiting step in tumor development. That is, tumors cannot grow beyond 2–3 mm in the absence of new vasculatures (Risau, 1997). This is because tumors need new blood capillaries to create their own nutrient supply, to remove metabolic wastes, and to facilitate metastasis of tumor cells to other sites (Risau, 1997). In addition, abnormal regulation of angiogenesis has been found to be involved in the pathogenesis of several disorders including inflammation, rheumatoid arthritis, ocular neovascularization, and psoriasis (Walsh and
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