Narasimhan, B.; Ansari, A.M.; Singh, N.; Mourya, V.; Dhakee, A.S. A QSAR Approach for the Prediction of Stability of Benzoglycolamide Ester Prodrugs. Chem. Pharm. Bull. 2006, 54, 1067–1071.

QsarDB Repository

Narasimhan, B.; Ansari, A.M.; Singh, N.; Mourya, V.; Dhakee, A.S. A QSAR Approach for the Prediction of Stability of Benzoglycolamide Ester Prodrugs. Chem. Pharm. Bull. 2006, 54, 1067–1071.

QDB archive DOI: 10.15152/QDB.149   DOWNLOAD

QsarDB content

Property logK: Hydrolytic rate constant as logK

Tab4.model3: Model for benzoglycolamide ester prodrugs

Regression model (regression)

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NameTypen

R2

σ

Training settraining370.8240.124

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When using this QDB archive, please cite (see details) it together with the original article:

  • Piir, G. Data for: A QSAR Approach for the Prediction of Stability of Benzoglycolamide Ester Prodrugs. QsarDB repository, QDB.149. 2015. https://doi.org/10.15152/QDB.149

  • Narasimhan, B.; Ansari, A. M.; Singh, N.; Mourya, V.; Dhakee, A. S. A QSAR Approach for the Prediction of Stability of Benzoglycolamide Ester Prodrugs. Chem. Pharm. Bull. 2006, 54, 1067–1071. https://doi.org/10.1248/cpb.54.1067

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Title: Narasimhan, B.; Ansari, A.M.; Singh, N.; Mourya, V.; Dhakee, A.S. A QSAR Approach for the Prediction of Stability of Benzoglycolamide Ester Prodrugs. Chem. Pharm. Bull. 2006, 54, 1067–1071.
Abstract:A method consisting of quantitative structure–activity relationship (QSAR) (MLR) was developed to predict the hydrolytic rate constant of 37 benzoglycolamide ester prodrugs. The regression method was used as a calibration model for calculating the hydrolytic rate constant and investigating their linear characteristics. The QSAR study indicated the importance of the descriptors charge on amide nitrogen (AN), lipophilic parameter (log P) and nucleophilic frontal density (NUFD) in contribution to the ester hydrolysis with the correlation coefficient value of 0.908 for the developed MLR model. The models were validated by leave one out (LOO) technique as well as by the calculation of statistical parameters for the developed MLR models.
URI:http://hdl.handle.net/10967/149
http://dx.doi.org/10.15152/QDB.149
Date:2015-04-01


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