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Predicting the Anti-Inflammatory Activity of Novel 5-Phenylsulfamoyl-2-(2-Nitroxy) (Acetoxy) Benzoic Acid Derivatives using 2D and 3D-QSAR (kNN-MFA) Analysis


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1 Department of Pharmaceutical Chemistry, Bhujbal Knowledge City, MET’S IOP, Adgaon, Nashik-422003, India
     

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The quantitative structure–activity relationship (QSAR) analyses were carried out for a series of new side chain modified 5-phenylsulfamoyl-2-(2-nitroxy) (acetoxy) benzoic acid derivatives to find out the structural requirements of their anti-inflammatory activities. The statistically significant best 2D QSAR models for anti-inflammatory activity having correlation coefficient (r2) = 0.897 and cross validated squared correlation coefficient (q2) = 0.701 with external predictive ability (pred_r2) = 0.390 were developed by multiple linear regression coupled with genetic algorithm (GA–MLR) and stepwise (SW–MLR) forward algorithm, respectively. The results of the present study may be useful on the designing of more potent analogues as antimalarial agents.

Keywords

QSAR, 5-Phenylsulfamoyl-2-(2-Nitroxy) (Acetoxy) Benzoic Acid, Anti-Inflammatory, MLR, Genetic Algorithm.
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  • Predicting the Anti-Inflammatory Activity of Novel 5-Phenylsulfamoyl-2-(2-Nitroxy) (Acetoxy) Benzoic Acid Derivatives using 2D and 3D-QSAR (kNN-MFA) Analysis

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Authors

Kiran Madhawai
Department of Pharmaceutical Chemistry, Bhujbal Knowledge City, MET’S IOP, Adgaon, Nashik-422003, India
Dinesh Rishipathak
Department of Pharmaceutical Chemistry, Bhujbal Knowledge City, MET’S IOP, Adgaon, Nashik-422003, India
Santosh Chhajed
Department of Pharmaceutical Chemistry, Bhujbal Knowledge City, MET’S IOP, Adgaon, Nashik-422003, India
Sanjay Kshirsagar
Department of Pharmaceutical Chemistry, Bhujbal Knowledge City, MET’S IOP, Adgaon, Nashik-422003, India

Abstract


The quantitative structure–activity relationship (QSAR) analyses were carried out for a series of new side chain modified 5-phenylsulfamoyl-2-(2-nitroxy) (acetoxy) benzoic acid derivatives to find out the structural requirements of their anti-inflammatory activities. The statistically significant best 2D QSAR models for anti-inflammatory activity having correlation coefficient (r2) = 0.897 and cross validated squared correlation coefficient (q2) = 0.701 with external predictive ability (pred_r2) = 0.390 were developed by multiple linear regression coupled with genetic algorithm (GA–MLR) and stepwise (SW–MLR) forward algorithm, respectively. The results of the present study may be useful on the designing of more potent analogues as antimalarial agents.

Keywords


QSAR, 5-Phenylsulfamoyl-2-(2-Nitroxy) (Acetoxy) Benzoic Acid, Anti-Inflammatory, MLR, Genetic Algorithm.

References