Quantum and Structural Molecular Fragment models used to predict anti-inflammatory activity

Abstract

In this paper, we predict the anti-inflammatory activity of a series of 26 structures of N-arylanthranilic acid. So, Quantitatve Structure-Activity Relationship (QSAR) method remains the focus of many studies aimed at modeling and prediction of physicochemical properties or biological activities of molecule. Two models was used: quantum model and Structural Molecular Fragment (SMF) model. In the first model, semi-empirical (AM1) approach was used to calculate the quantum chemical descriptors using GAUSSIAN 09 package and the others chemical descriptors were calculated with chemaxon package. In the second model, Structural Molecular Fragment were generated by I.S.I.D.A (In Silico Design and Data Analysis). Our two models were built by using a Multiple Linear Regression Analysis (MLR).The concluded QSAR models reflected that the drugs activity was mainly attributed to quantum chemical descriptors with the statistical analysis of multiple R-squared equal to 0.9898 v.s 0.9077 for the Structural Molecular Fragment developed in I.S.I.D.A. Keywords: N-arylanthranilic acids, anti-inflammatory activity, quantum descriptors, Structural Molecular Fragment.