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- W4308773419 endingPage "1383" @default.
- W4308773419 startingPage "1383" @default.
- W4308773419 abstract "The preclinical drug discovery stage often requires a large amount of costly and time-consuming experiments using huge sets of chemical compounds. In the last few decades, this process has undergone significant improvements by the introduction of quantitative structure-activity relationship (QSAR) modelling that uses a certain percentage of experimental data to predict the biological activity/property of compounds with similar structural skeleton and/or containing a particular functional group(s). The use of machine learning tools along with it has made life even easier for pharmaceutical researchers. Here, we discuss the toxicity of certain sets of bioactive compounds towards Pimephales promelas and Tetrahymena pyriformis in terms of the global conceptual density functional theory (CDFT)-based descriptor, electrophilicity index (ω). We have compared the results with those obtained by using the commonly used hydrophobicity parameter, logP (where P is the n-octanol/water partition coefficient), considering the greater ease of computing the ω descriptor. The Human African trypanosomiasis (HAT) curing activity of 32 pyridyl benzamide derivatives is also studied against Tryphanosoma brucei. In this review article, we summarize these multiple linear regression (MLR)-based QSAR studies in terms of electrophilicity (ω, ω2) and hydrophobicity (logP, (logP)2) parameters." @default.
- W4308773419 created "2022-11-15" @default.
- W4308773419 creator A5012200457 @default.
- W4308773419 creator A5022861683 @default.
- W4308773419 creator A5069414175 @default.
- W4308773419 date "2022-11-10" @default.
- W4308773419 modified "2023-10-01" @default.
- W4308773419 title "Quantitative Structure–Toxicity Relationship in Bioactive Molecules from a Conceptual DFT Perspective" @default.
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