Optimal neighbor selection in molecular similarity: comparison of arbitrary versus tailored prediction spaces

SAR and QSAR in Environmental Research
B D Gute, S C Basak

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 (p(vap)) 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.

References

Aug 1, 1976·Journal of Pharmaceutical Sciences·L B KierL H Hall
Aug 1, 1990·Pharmaceutical Research·L B Kier, L H Hall
Sep 1, 1995·Toxicology Letters·S C BasakG D Grunwald
Jan 1, 1995·SAR and QSAR in Environmental Research·S C Basak, G D Grunwald
Aug 24, 2000·Journal of Chemical Information and Computer Sciences·S C BasakB D Gute
May 1, 2001·SAR and QSAR in Environmental Research·B D GuteS C Basak
Jun 21, 2001·Journal of Chemical Information and Computer Sciences·D M HawkinsX Shi
Jan 5, 2002·Journal of Molecular Graphics & Modelling·B D Gute, S C Basak
Jan 1, 1947·Journal of the American Chemical Society·H WIENER
Oct 5, 2010·Current Computer-aided Drug Design·Subhash C BasakGregory D Grunwald

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Citations

Oct 20, 2006·SAR and QSAR in Environmental Research·S C BasakB D Gute
May 29, 2013·SAR and QSAR in Environmental Research·C Li, L M Colosi
Sep 28, 2010·European Journal of Medicinal Chemistry·Andrei I KhlebnikovMark T Quinn

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