Abstract
Three classes of arbitrary quantitative molecular similarity analysis (QMSA) methods have been computed using atom pairs (APs), topological indices (TIs), and principal components (PCs) derived from topological indices. Tailored QMSA models have been developed from TIs selected through ridge regression. K-nearest neighbor (kNN) based estimation has been applied to all of the methods to estimate normal vapor pressure (pvap) and water solubility (sol) for a set of 194 chemicals. Results show that the tailored QMSA methods are superior to arbitrary similarity methods in estimating both of these properties for the given set of chemicals.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 37-51 |
| Number of pages | 15 |
| Journal | SAR and QSAR in environmental research |
| Volume | 17 |
| Issue number | 1 |
| DOIs | |
| State | Published - Feb 2006 |
Bibliographical note
Funding Information:This manuscript is contribution number 396 from the Center for Water and the Environment of the Natural Resources Research Institute. This material is based on research sponsored by the Air Force Research Laboratory, under agreement number F49620-02-1-0138. The US Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon.
Keywords
- Atom pairs
- Quantitative molecular similarity analysis (QMSA)
- Tailored QMSA
- Topological indices
- kNN