Self-organizing neural networks for modeling robust 3D and 4D QSAR: application to dihydrofolate reductase inhibitors

Jaroslaw Polanski; Andrzej Bak; Rafal Gieleciak; Tomasz Magdziarz

doi:10.3390/91201148

Self-organizing neural networks for modeling robust 3D and 4D QSAR: application to dihydrofolate reductase inhibitors

Molecules. 2004 Dec 31;9(12):1148-59. doi: 10.3390/91201148.

Authors

Jaroslaw Polanski¹, Andrzej Bak, Rafal Gieleciak, Tomasz Magdziarz

Affiliation

¹ Department of Organic Chemistry, Institute of Chemistry, University of Silesia, PL-40-006 Katowice Poland. polanski@us.edu.pl

Abstract

We have used SOM and grid 3D and 4D QSAR schemes for modeling the activity of a series of dihydrofolate reductase inhibitors. Careful analysis of the performance and external predictivities proves that this method can provide an efficient inhibition model.

Publication types

Comparative Study
Research Support, Non-U.S. Gov't

MeSH terms

Drug Design
Enzyme Inhibitors / chemistry*
Folic Acid Antagonists / chemistry*
Least-Squares Analysis
Models, Chemical*
Models, Molecular*
Neural Networks, Computer*
Quantitative Structure-Activity Relationship*
Software
Tetrahydrofolate Dehydrogenase / metabolism*

Substances

Enzyme Inhibitors
Folic Acid Antagonists
Tetrahydrofolate Dehydrogenase