Quantitative molecular similarity analysis (QMSA) methods for property estimation: a comparison of property-based, arbitrary, and tailored similarity spaces.
Three classes of arbitrary quantitative molecular similarity analysis (QMSA) methods have been computed using atom pairs, topological indices, and physicochemical properties. Tailored QMSA models have been developed using a selected number of TIs chosen by ridge regression. The methods have been applied to the K-nearest neighbor based estimation of log P of two sets of chemicals. Results show that the property-based and tailored QMSA methods are superior to the arbitrary similarity methods in estimating log P of both sets of chemicals
Basak
S C
SC
Natural Resources Research Institute, University of Minnesota at Duluth, 5013 Miller Trunk Hwy., Duluth, MN 55811, USA. sbasak@nrri.umn.edu
Gute
B D
BD
Mills
D
D
D055598:Chemical Phenomena; D002627:Chemistry, Physical; D004785:Environmental Pollutants / Q000009:adverse effects*; D005544:Forecasting; D008962:Models, Theoretical; D018570:Risk Assessment; D013329:Structure-Activity Relationship
D004785:Environmental Pollutants