Der Pharma Chemica
Journal for Medicinal Chemistry, Pharmaceutical Chemistry and Computational Chemistry

Abstract

Quantitative Structure Activity Relationship (QSAR) Analysis on Arylbenzofuran Derivatives as Histamine H3 Antagonists

Author(s): Sanmati K. Jain* and Priyanka Sinha

Quantitative structure activity relationship (QSAR) analysis on arylbenzofuran derivatives were performed for their antihistaminic (H3-receptor antagonist activity) using VlifeQSARPro software. Partial least square (PLS) linear regression analysis coupled with stepwise variable selection method was applied to derive QSAR models which were further validated for statistical significance by internal and external validation. Statistically significant QSAR model generated have squared correlation coefficient (r2) 0.8662, cross validated correlation coefficient (q2) 0.6029 and predictive correlation coefficient (pred_r2) 0.3940. The QSAR model indicated that the T_3_N_5 (count of number of triple bonded atoms separated from nitrogen atom by five bond in a molecule), T_C_C_7 [count of number of Carbon atoms (single or double bonded) separated from any other Carbon atom (single or double bonded) by 7 bonds in a molecule] and T_2_3_5 [count of number of double bonded atoms (i.e. any double bonded atom, T_2) separated from any other triple bonded atom by 5 bonds in a molecule] were the important determinants for H3-receptor antagonistic activity.


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