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
Bibliographical noteFunding Information:
The authors acknowledge the financial support of this research by grant F496200210138 from the United States Air Force Office of Scientific Research. This is contribution number 320 from the Center for Water and the Environment of the Natural Resources Research Institute.