9-Arylimino noscapinoids as potent tubulin binding anticancer agent: chemical synthesis and cellular evaluation against breast tumour cells.

A library of 9-arylimino derivatives of noscapine was developed by coupling of Schiff base containing imine groups. Virtual screening using molecular docking with tubulin revealed three molecules, 12-14 that bind with high affinity. An improved predicted free energy of binding (FEB) of -5.390, -6.506 and -6.679 kcal/mol for the molecules 12-14 was found compared to noscapine (-5.135 kcal/mol). Furthermore, molecular dynamics simulation in combination with Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) revealed robust binding free energy of -166.03, -169.75 and -170.63 kcal/mol for the molecules 12, 13 and 14, respectively. These derivatives were strategically synthesized and experimentally validated for their anticancer activity. Tubulin binding assay revealed substantial binding of molecules 12-14 with purified tubulin. Further, their anticancer activity was demonstrated using two cancer cell lines (MCF-7 and MDAMB-231) and a panel of primary breast tumour cells. All these derivatives inhibited cellular proliferation in all the cancer cells that ranged between 30.1 and 5.8 µM, which is 1.7 to 7.52 fold lower than that of noscapine. Further, these novel derivatives arrest cell cycle in the G2/M-phase followed by induction of apoptosis. Thus, 9-arylimino noscapinoids 12-14 have a great potential to be a novel therapeutic agent for breast cancers.

Combined molecular dynamics and continuum solvent approaches (MM-PBSA/GBSA) to predict noscapinoid binding to γ-tubulin dimer.

γ-tubulin plays crucial role in the nucleation and organization of microtubules during cell division. Recent studies have also indicated its role in the regulation of microtubule dynamics at the plus end of the microtubules. Moreover, γ-tubulin has been found to be over-expressed in many cancer types, such as carcinomas of the breast and glioblastoma multiforme. These studies have led to immense interest in the identification of chemical leads that might interact with γ-tubulin and disrupt its function in order to explore γ-tubulin as potential chemotherapeutic target. Recently a colchicine-interacting cavity was identified at the interface of γ-tubulin dimer that might also interact with other similar compounds. In the same direction we theoretically investigated binding of a class of compounds, noscapinoids (noscapine and its derivatives) at the interface of the γ-tubulin dimer. Molecular interaction of noscapine and two of its derivatives, amino-noscapine and bromo-noscapine, was investigated by molecular docking, molecular dynamics simulation and binding free energy calculation. All noscapinoids displayed stable interaction throughout simulation of 25 ns. The predictive binding free energy (ΔGbind) indicates that noscapinoids bind strongly with the γ-tubulin dimer. However, bromo-noscapine showed the best binding affinity (ΔGbind = -37.6 kcal/mol) followed by noscapine (ΔGbind = -29.85 kcal/mol) and amino-noscapine (ΔGbind = -23.99 kcal/mol) using the MM-PBSA method. Similarly using the MM-GBSA method, bromo-noscapine showed highest binding affinity (ΔGbind = -43.64 kcal/mol) followed by amino-noscapine (ΔGbind = -37.56 kcal/mol) and noscapine (ΔGbind = -34.57 kcal/mol). The results thus generate compelling evidence that these noscapinoids may hold great potential for preclinical and clinical evaluation.

Quantitative structure-activity relationship (QSAR) for insecticides: development of predictive in vivo insecticide activity models.

Quantitative structure-activity relationship (QSAR) analyses were performed independently on data sets belonging to two groups of insecticides, namely the organophosphates and carbamates. Several types of descriptors including topological, spatial, thermodynamic, information content, lead likeness and E-state indices were used to derive quantitative relationships between insecticide activities and structural properties of chemicals. A systematic search approach based on missing value, zero value, simple correlation and multi-collinearity tests as well as the use of a genetic algorithm allowed the optimal selection of the descriptors used to generate the models. The QSAR models developed for both organophosphate and carbamate groups revealed good predictability with r(2) values of 0.949 and 0.838 as well as [image omitted] values of 0.890 and 0.765, respectively. In addition, a linear correlation was observed between the predicted and experimental LD(50) values for the test set data with r(2) of 0.871 and 0.788 for both the organophosphate and carbamate groups, indicating that the prediction accuracy of the QSAR models was acceptable. The models were also tested successfully from external validation criteria. QSAR models developed in this study should help further design of novel potent insecticides.

Application of the linear interaction energy method for rational design of artemisinin analogues as haeme polymerisation inhibitors.

The anti-malarial activity of artemisinin-derived drugs appears to be mediated by an interaction of the drug's endoperoxide bridge with intra-parasitic haeme. The binding affinity of artemisinin analogues with haeme were computed using linear interaction energy with a surface generalised Born (LIE-SGB) continuum solvation model. Low levels of root mean square error (0.348 and 0.415 kcal/mol) as well as significant correlation coefficients (r(2) = 0.868 and 0.892) between the experimental and predicted free energy of binding (FEB) based on molecular dynamics and hybrid Monte Carlo sampling techniques establish the SGB-LIE method as an efficient tool for generating more potent inhibitors of haeme polymerisation inhibition.