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Quantitative structure–property prediction of ion‐molecule rate constants for proton transfer reaction between H 3 O + and volatile organic compound
Author(s) -
Fatemi Mohammad Hossein,
Moghaddam Masoomeh Raei
Publication year - 2012
Publication title -
journal of mass spectrometry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.475
H-Index - 121
eISSN - 1096-9888
pISSN - 1076-5174
DOI - 10.1002/jms.3000
Subject(s) - chemistry , quantitative structure–activity relationship , multilinear map , molecule , molecular descriptor , linear regression , reaction rate constant , proton , mean squared error , ion , computational chemistry , stereochemistry , organic chemistry , statistics , kinetics , mathematics , physics , quantum mechanics , pure mathematics
A quantitative structure–property relationship (QSPR) study based on multiple linear regression (MLR) and artificial neural network (ANN) techniques was carried out to investigate the ion‐molecules rate constants for proton transfer reaction between hydronuim ion (H 3 O + ) and some important volatile organic compounds (VOCs). A collection of 50 VOCs was chosen as data set that was randomly divided into three groups, training, internal and external test sets consist of 40, 5 and 5 molecules, respectively. A total of five independent variables selected by stepwise multilinear regression are electronic, geometric, topological type descriptors. The ANN model was developed by using the five descriptors appearing in the MLR model as inputs. Among developed models, the best QSPR model was the ANN model that produced a reasonable level of mean square error MSE train = 0.021, MSE external = 0.186, MSE internal = 0.110. The rate constants calculated by this model are in very good agreement with experimental values. The result of this study reveals the applicability of QSPR approaches in prediction of ion‐molecules rate constants for proton transfer reaction of VOCs from their molecular structural descriptors. Copyright © 2012 John Wiley & Sons, Ltd.