A field based 3D QSAR model of novel anti-microtubule agent noscapine and its derivatives
Seneha Santoshi, Pradeep Kumar Naik · International Journal of Fundamental and Applied Sciences (IJFAS) · 2022
BACKGROUD & OBJECTIVE: Noscapinoids are a new class of microtubule binding compounds which show greatpromise as chemotherapeutic agents for the treatment of human cancers. To investigate the structural determinants ofnoscapinoids responsible for anti-cancer activity in order to design more potent derivatives, attempts were made todeveloped a 3D QSAR model based on “field point” descriptors using Forge V10 software(Cresset group).METHODOLOGY: We have used 53 structurally diverse noscapinoids in a single panel and experimentally determinedtheir IC50 value using human acute lymphoblastic leukemia cells (IC50 values vary from 1.2 to 56.0 μM). Molecularmodels of these compounds were built,energy minimized and geometry optimized. The data set was randomly dividedinto 43 training and 10 test set molecules. Amino noscapine was considered as template molecule for the calculation ofhydrophobic, steric, electrostatic and volume field points. These field based descriptors were used to align the training setmolecules with the template molecule.A Partial Least Square (PLS) model was built based on field points using sphereexclusion algorithm. RESULTS:A statistically significant model (Rtrain2 = 0.884; R2LOO = 0.875) was obtained with thefield point descriptors. The robustness of the QSAR model was characterized by the values of the internal leave-one-outcross-validated regression coefficient (R2LOO) for the training set and Rtest2 for the test set. The overall root mean squareerror (RMSE) between the experimental and predicted IC50 value was 1.75 and Rtest2 = 0.713, revealing goodpredictability of the QSAR model. The 3D QSAR model developed in this study shall aid further design of novel potentnoscapine derivatives.