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- W2049278837 abstract "QSAR studies have been performed on some PPAR-γ agonists using TATA-BioSuite software to identify the essential structural and physico-chemical features for their PPAR-γ agonistic activity. The 23 compounds were divided into training set of 18 and test set of five compounds using k-nearest neighbor (kNN) clustering. The steric, electronic and topological descriptors were found to have an important role in governing the variation in agonistic activity. The predicted activities by the developed models were in good accordance with the observed activities." @default.
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- W2049278837 date "2008-01-01" @default.
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- W2049278837 title "QSAR analysis of PPAR-γ agonists as anti-diabetic agents" @default.
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- W2049278837 doi "https://doi.org/10.1016/j.ejmech.2007.03.004" @default.
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