Abstract
The bioactivities of a series of 2-amino-6-arylsulfonylbenzonitriles and their thio- and sulfinyl congeners have been previously modeled by using the MIA-QSAR approach and the PLS regression method [10]. The present work reports the significant improvement in the prediction ability of the Multivariate Image Analysis applied to Quantitative Structure-Activity Relationship (MIA -QSAR) model by applying Parallel Factor Analysis (PARAFAC) and Artificial Neural Network (ANN) directly to the three-way array built. This perspective represents an important advance for the accurate prediction of potential drug candidates.
Original language | English (US) |
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Pages (from-to) | 1092-1097 |
Number of pages | 6 |
Journal | QSAR and Combinatorial Science |
Volume | 27 |
Issue number | 9 |
DOIs | |
State | Published - Sep 2008 |
Keywords
- ANN
- Anti-HIV-1 compounds
- MIA-QSAR
- PARAFAC
ASJC Scopus subject areas
- Drug Discovery
- Computer Science Applications
- Organic Chemistry