Authors: Isarankura-Na-Ayudhya, Chartchalerm
Naenna, Thanakorn
Nantasenamat, Chanin
Prachayasittikul, Virapong
Tantimongcolwat, Tanawut
Title: Prediction of selectivity index of pentachlorophenol-imprinted polymers
Language (ISO): en
Abstract: A data set comprising of the selectivity index of pentachlorophenol-imprinted polymers against 53 pentachlorophenol and related compounds was obtained from the excellent work of Baggiani et al. Molecular descriptors of the phenol compounds were calculated with E-DRAGON to obtain a total of 1,666 descriptors spanning 20 categories of molecular properties. Multivariate analysis of the data set was performed using multiple linear regression, partial least squares regression, and principal component regression. Partial least squares regression was found to deliver an excellent predictive model and was chosen for further investigation. The descriptor dimension was reduced by the combined use of partial least squares and Unsupervised Forward Selection algorithm. The obtained Quantitative Structure-Property Relationship (QSPR) model based on the smaller subset of the molecular descriptors displayed substantial gain in predictive ability when compared to the model of Baggiani et al. Such QSPR model can help in the computational design of MIPs with predefined selectivity toward template molecules of interest.
Subject Headings: molecularly imprinted polymer
partial least squares regression
Issue Date: 2006-10-16
Appears in Collections:Original Articles

Files in This Item:
File Description SizeFormat 
Prachayasittikul14-06proof.pdfDNB247.48 kBAdobe PDFView/Open

This item is protected by original copyright

All resources in the repository are protected by copyright.