Classification and Prediction of Tripeptides Inhibiting HIV-1 Tat/TAR-RNA Interaction Using a Self-Organizing Map

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.

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