A field based 3D QSAR model of novel anti-microtubule agent noscapine and its derivatives

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Year 2012 Vol 1 Issue 4
Document Type : ORIGINAL ARTICLE
¹Seneha Santoshi ²Pradeep Kumar Naik*
¹Department of Biotechnology and Bioinformatics, Jaypee University of Information Technology, Waknaghat, Solan-173234, Himachal Pradesh, India
²Department of Biotechnology and Bioinformatics, Jaypee University of Information Technology, Waknaghat, Solan-173234, Himachal Pradesh, India
Abstract
Noscapinoids are a new class of microtubule binding compounds which show great promise as chemotherapeutic agents for the treatment of human cancers. To investigate the structural determinants of noscapinoids responsible for anti-cancer activity in order to design more potent derivatives, attempts were made to developed a 3D QSAR model based on “field point” descriptors using Forge V10 software(Cresset group)

We have used 53 structurally diverse noscapinoids in a single panel and experimentally determined their IC50 value using human acute lymphoblastic leukemia cells (IC50 values vary from 1.2 to 56.0 µM). Molecular models of these compounds were built,energy minimized and geometry optimized. The data set was randomly divided into 43 training and 10 test set molecules. Amino noscapine was considered as template molecule for the calculation of hydrophobic, steric, electrostatic and volume field points. These field based descriptors were used to align the training set molecules with the template molecule.A Partial Least Square (PLS) model was built based on field points using sphere exclusion algorithm.
A statistically significant model (Rtrain 2 = 0.884; R2 LOO = 0.875) was obtained with the field point descriptors. The robustness of the QSAR model was characterized by the values of the internal leave-one-out cross-validated regression coefficient (R2 LOO) for the training set and Rtest 2 for the test set. The overall root mean square error (RMSE) between the experimental and predicted IC50 value was 1.75 and Rtest 2 = 0.713, revealing good predictability of the QSAR model. The 3D QSAR model developed in this study shall aid further design of novel potent noscapine derivatives.
Keywords
: Noscapnoids, anti-cancer activity, 3D QSAR, molecular fields.
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