Quantitative Structure-Activity Relationship Analysis of the Anticonvulsant Activity of Some Benzylacetamides Based on Genetic Algorithm-Based Multiple Linear Regression

A Najafi,Ss Ardakani,M Marjani

doi:10.4314/tjpr.v10i4.14

Abstract

Purpose: To develop the quantitative structure-activity relationship (QSAR) for predicting the anticonvulsant activity of α-substituted acetamido-N-benzylacetamide derivatives.Methods: AM1 semiempirical quantum chemical calculation method was used to find the optimum 3D geometry of the studied molecules. Two types of molecular descriptors, including the 2D autocorrelation and GETAWAY descriptors, were used to derive a quantitative relation between anticonvulsant activity and structural properties. The relevant molecular descriptors were selected by genetic algorithm-based multiple linear regression (GA-MLR) approach.Results: The high value of the correlation coefficient, R2 (0.900), indicate that the model was satisfactory.Conclusion: The proposed model has good stability, robustness and predictability when verified by internal and external validation.Keywords: Anticonvulsant, Benzylacetamides, 2D Autocorrelation, Quantitative structure-activity relationships, Multiple linear regression.

Highlights

Epilepsy, a common neurological disorder characterized by recurrent spontaneous seizures arising from excessive electrical activity in some portion of the brain, is a worldwide public health problem which affects approximately 1 % of the population [1]
We aimed to develop quantitative structure-activity relationship (QSAR) equations for the anticonvulsant activity of a series of α- substituted acetamido-N-benzylacetamide drugs
These workers used 2D and 3D QSAR on these molecules and observed that the molar refractivity (MR) of the substituents was the major factor controlling the binding of the ligands to their receptors

Summary

Introduction

A common neurological disorder characterized by recurrent spontaneous seizures arising from excessive electrical activity in some portion of the brain, is a worldwide public health problem which affects approximately 1 % of the population [1]. The field of epilepsy has received a great deal of attention from research investigators in the hope of discovering new drugs that are more effective and have minimal adverse effects. Though several new anticonvulsants have been introduced, some types of epilepsies are still not adequately controlled with the current therapy. Adverse reactions and lack of efficacy for certain types of epilepsies are some of the limitations of existing medications [2]. Antiepileptic drugs exert their action by different mechanisms. They include an enhancement of the GABA-ergic neurotransmission, effects on neuronal voltage-gated sodium and/or calcium channels [3]

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