2012Medicinal ChemistryRequires access

A QSAR Analysis of 2-phenoxy-N-substituted Acetamide Analogues as Hypoxia-Inducible Factor-1(HIF-1) Inhibitors: A Rational Approach to Anticancer Drug Design

Malleshappa N. Noolvi, Harun Patel, Sarita Kamboj

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Abstract

A set of thirty one substituted 2-phenoxy-N-phenylacetamide derivatives with HIF-1 inhibitory activities was subjected to 2D and 3D Quantitative Structure Activity Relationship (QSAR) studies using various combinations of descriptors. 2D-QSAR was performed using Multiple Linear Regression (MLR), Principal Component Regression (PCR) and Partial Least Squares Regression (PLS) methods. Among these three methods Multiple Linear Regression (MLR) led to the statistically significant best 2D-QSAR Model-I having correlation coefficient r(2) = 0.9469 and cross validated squared correlation coefficient q(2) = 0.8933 with external predictive ability of pred_r(2) = 0.7128 with the descriptors like SssNHE-index, slogp, T_O_N_1 and T_2_Cl_1. 3D-QSAR study was performed using the simulated annealing variable selection procedures k-nearest neighbor molecular field analysis approach. 3D-QSAR shows interesting results in terms of internal and external predictability. Molecular field analysis was applied for the generation of steric, hydrophobic and electrostatic descriptors based on aligned structures which shows good correlative and predictive capabilities in terms of q(2) = 0.9672 and pred_r(2) = 0.8480. Hence the model proposed in this work provides important structural insight in designing novel derivatives with specific HIF-1 inhibitory activity.

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What this paper is about

A set of thirty one substituted 2-phenoxy-N-phenylacetamide derivatives with HIF-1 inhibitory activities was subjected to 2D and 3D Quantitative Structure Activity Relationship (QSAR) studies using various combinations of descriptors. 2D-QSAR was performed using Multiple Linear Regression (MLR), Principal Component Regression (PCR) and Partial Least Squares Regression (PLS) methods. Among these three methods Multiple Linear Regression (MLR) led to the statistically significant best 2D-QSAR Model-I having correlation coefficient r(2) = 0.9469 and cross validated squared correlation coefficient q(2) = 0.8933 with external predictive ability of pred_r(2) = 0.7128 with the descriptors like SssNHE-index, slogp, T_O_N_1 and T_2_Cl_1. 3D-QSAR study was performed using the simulated annealing variable selection procedures k-nearest neighbor molecular field analysis approach. 3D-QSAR shows interesting results in terms of internal and external predictability. Molecular field analysis was applied for the generation of steric, hydrophobic and electrostatic descriptors based on aligned structures which shows good correlative and predictive capabilities in terms of q(2) = 0.9672 and pred_r(2) = 0.8480. Hence the model proposed in this work provides important structural insight in designing novel derivatives with specific HIF-1 inhibitory activity.

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Available abstract

A set of thirty one substituted 2-phenoxy-N-phenylacetamide derivatives with HIF-1 inhibitory activities was subjected to 2D and 3D Quantitative Structure Activity Relationship (QSAR) studies using various combinations of descriptors. 2D-QSAR was performed using Multiple Linear Regression (MLR), Principal Component Regression (PCR) and Partial Least Squares Regression (PLS) methods. Among these three methods Multiple Linear Regression (MLR) led to the statistically significant best 2D-QSAR Model-I having correlation coefficient r(2) = 0.9469 and cross validated squared correlation coefficient q(2) = 0.8933 with external predictive ability of pred_r(2) = 0.7128 with the descriptors like SssNHE-index, slogp, T_O_N_1 and T_2_Cl_1. 3D-QSAR study was performed using the simulated annealing variable selection procedures k-nearest neighbor molecular field analysis approach. 3D-QSAR shows interesting results in terms of internal and external predictability. Molecular field analysis was applied for the generation of steric, hydrophobic and electrostatic descriptors based on aligned structures which shows good correlative and predictive capabilities in terms of q(2) = 0.9672 and pred_r(2) = 0.8480. Hence the model proposed in this work provides important structural insight in designing novel derivatives with specific HIF-1 inhibitory activity.

Key concepts: Quantitative structure–activity relationship, Partial least squares regression, Linear regression, Principal component regression, Principal component analysis, Chemistry, Regression analysis, Mathematics

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A QSAR Analysis of 2-phenoxy-N-substituted Acetamide Analogues as Hypoxia-Inducible Factor-1(HIF-1) Inhibitors: A Rational Approach to Anticancer Drug Design — Research Paper | ScholarLens