## Abstract Quantitative structureβactivity relationships (QSAR) for prediction of binding affinities (pEC50, i.e., minus decimal logarithm of the 50% effective concentration) of 20 fullerene derivatives inhibitors of the HIVβ1 PR (human immunodeficiency virus type 1 protease) have been developed b
β¦ LIBER β¦
Large-scale QSAR study of aromatase inhibitors using SMILES-based descriptors
β Scribed by Worachartcheewan, Apilak; Mandi, Prasit; Prachayasittikul, Virapong; Toropova, Alla P.; Toropov, Andrey A.; Nantasenamat, Chanin
- Book ID
- 125858943
- Publisher
- Elsevier Science
- Year
- 2014
- Tongue
- English
- Weight
- 1009 KB
- Volume
- 138
- Category
- Article
- ISSN
- 0169-7439
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## Abstract Quantitative Structure Activity Relationship (QSAR) is a well known cheminformatic tool for the discovery of novel biologically active compounds. However, when large and heterogeneous datasets are mined, it is not possible to derive a QSAR equation able to predict in a satisfactory mann