By M. C. Sharma, Smita Sharma, D. V. Kohli, S. C. Chaturvedi
A Quantitative Structure Activity Relationship study on a Series of 17 molecules of (benzimidazole compounds) with antimicrobial activity analogues was made using combination of various physicochemical descriptors. (Thermodynamic, electronic and spatial). Several statistical expressions for 2D QSAR & 3D QSAR were developed using stepwise partial least square (PLS) regression analysis and K-Nearest neighboring molecular field analysis (K-NN-MFA) respectively. The best Quantitative Structure Activity Relationship models were further cross validated. The study revealed that the alignment independent descriptors contributed positive and path count contributed negatively in 2D-QSAR analysis and Electrostatic descriptor contributed positive and steric descriptor contributed negatively in 3D QSAR analysis. 2D-QSAR model developed using partial least square regression approach. Negative logarithmic value of (–PMIC) was taken as dependent variable and T_N_N_4, T_2_C_1, T_T_C_4, T_T_S_7 T_2_C_1, ChiV3, T_O_O_7 was taken as independent varable. The analysis resulted in the following 2D-equation suggest that, BA = [-1.2083 (± 9.17986)] + T_O_O_7 1 [0.152608(± 0.336984)] + T_2_C_1 [0.1510 (± 0.000191822)] + T_T_C_4 [-1.8960 (± 0.504224)] n=11, r2 = 0.9717, q2 = 0.8367, F test = 60.0062, pred_r2 = 0.6547, a lipophillic group, which is less bulkier at Ar, is important for guiding the design of a new molecule.3D-QSAR model developed using K-nearest neighbour method (training set =11 and test set = 6). Out of several model were developed. The best model derived by the method have cross-validated coefficient q2 value is 0.7926, Predict r2 value is 0.8919, k Nearest Neighbor is 2, Degree of freedom = 6. The steric and electrostatic descriptors at the grid points, E_442, S_473, S_135, S_190 plays important role for design of new molecule. QSAR analysis of series of benzimidazole compounds informed that electronegative and less bulky group increases the biological activity.
Key Words : 2D-QSAR (PLS), 3D-QSAR (k-NN-MFA), E. coli.
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