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QSPR Study on the Estimation of Solubility of Drug‐like Organic Compounds: A Case of Barbiturates
Author(s) -
Louis Bruno,
Singh Jyoti,
Shaik Basheerulla,
Agrawal Vijay K.,
Khadikar Padmakar V.
Publication year - 2009
Publication title -
chemical biology and drug design
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.59
H-Index - 77
eISSN - 1747-0285
pISSN - 1747-0277
DOI - 10.1111/j.1747-0285.2009.00844.x
Subject(s) - quantitative structure–activity relationship , topological index , molecular descriptor , linear regression , solubility , regression analysis , biological system , regression , cross validation , parametric statistics , valence (chemistry) , chemistry , data mining , mathematics , computational chemistry , computer science , statistics , organic chemistry , stereochemistry , biology
The paper describes a method for the estimation of solubility (log S ) of a series of 45 barbiturates employing 26 molecular descriptors. The molecular descriptors used being distance‐based topological indices, information indices, valence connectivity index, shape indices, first‐order Randic index. In addition, an indicator parameter was also used. The regression analysis has shown that an R 2 value of 0.885 was obtained in multi‐parametric regression analysis. The results are discussed critically using a variety of statistical parameters. The predictive powers of the models were discussed by using the method of cross‐validation. We observed that results obtained using spss and ncss software are identical.