Topological Distance Based 3D Descriptors for Use in QSAR and Diversity Analysis
- Author(s)
- Christian Klein, Dominik Kaiser, Gerhard Ecker
- Abstract
In topoplogical autocorrelation approaches molecular descriptors are calculated by summing up properties located at given topological distances. Since the relationship between topological and Euclidean distance contains 3D structural information, in the present paper a modified version of an autocorrelation approach is proposed to include this type of information. Steric, electronic, and indicator-variable-type descriptors are calculated and used in QSAR studies with three different data sets. The results demonstrate that the descriptors can be efficiently used in cluster- and QSAR analysis. The models obtained are highly predictive and comparable to those obtained by other commonly used 3D-QSAR methods.
- Organisation(s)
- External organisation(s)
- Universität Wien
- Journal
- Journal of Chemical Information and Computer Sciences
- Volume
- 44
- Pages
- 200-209
- No. of pages
- 10
- ISSN
- 0095-2338
- DOI
- https://doi.org/10.1021/ci0256236
- Publication date
- 2004
- Peer reviewed
- Yes
- Austrian Fields of Science 2012
- 3012 Pharmacy, Pharmacology, Toxicology
- Portal url
- https://ucris.univie.ac.at/portal/en/publications/topological-distance-based-3d-descriptors-for-use-in-qsar-and-diversity-analysis(34155af0-cfe7-414c-94cd-ab3a9b5c679d).html