Abstract
A self-organizing map (SOM) was used for identification of synthetic tripeptides to HIV-1 TAR-RNA. This virtual screening strategy identified a phenanthrene-Arg-Arg sequence with an IC50 value of 5 μM. The SOM technique was shown to be applicable to RNA-ligand finding following an entirely ligand-based approach.
Keywords: Neural network, Peptide, SOM, Kohonen network, Virtual screening, Docking
Letters in Drug Design & Discovery
Title: Classification and Prediction of Tripeptides Inhibiting HIV-1 Tat/TAR-RNA Interaction Using a Self-Organizing Map
Volume: 4 Issue: 6
Author(s): A. Givehchi, V. Ludwig, O. Boden, A. Krebs, U. Scheffer, M. Gobel and G. Schneider
Affiliation:
Keywords: Neural network, Peptide, SOM, Kohonen network, Virtual screening, Docking
Abstract: A self-organizing map (SOM) was used for identification of synthetic tripeptides to HIV-1 TAR-RNA. This virtual screening strategy identified a phenanthrene-Arg-Arg sequence with an IC50 value of 5 μM. The SOM technique was shown to be applicable to RNA-ligand finding following an entirely ligand-based approach.
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Cite this article as:
A. Givehchi , V. Ludwig , O. Boden , A. Krebs , U. Scheffer , M. Gobel and G. Schneider , Classification and Prediction of Tripeptides Inhibiting HIV-1 Tat/TAR-RNA Interaction Using a Self-Organizing Map, Letters in Drug Design & Discovery 2007; 4 (6) . https://dx.doi.org/10.2174/157018007781387791
DOI https://dx.doi.org/10.2174/157018007781387791 |
Print ISSN 1570-1808 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-628X |
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