Multi-way analysis of quantum topological molecular similarity descriptors for modeling acidity constant of some phenolic compounds.

Chem Biol Drug Des 2007 Nov;70(5):413-23

Department of Chemistry, Isfahan University of Technology, Isfahan 84154, Iran.

Three-way analyses of quantum topological molecular similarity descriptors were used for quantitative structure property relationship modeling of the acidity constant of some phenol derivatives. A three-way data was built for different molecules by constructing a data matrix for each molecule. The matrix was produced by considering different bonds in each molecule and different descriptors in each bond. The three-way models parallel factor analysis and N-way partial least squares, and two-way models including partial least squares were used for modeling structure-acidity relationships. Comparison of the results showed that the three-way arrays produced more predictive models with lower over-fitting. The bilinear partial least square model resulted in a biased estimation of acidity constant of prediction set with average relative error of prediction of 1.87%, whereas that obtained by parallel factor analysis and N-way partial least squares was near to zero (i.e. -0.41 and -0.33, respectively). Additionally, the three-way methods allowed investigating the significant impact of different bonds and different descriptors using leverages of the parallel factor analysis loadings.

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http://dx.doi.org/10.1111/j.1747-0285.2007.00585.xDOI Listing
November 2007

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