Table of Contents
Organic Chemistry International
Volume 2010 (2010), Article ID 545087, 17 pages
Research Article

A Comparative Study of Two Quantum Chemical Descriptors in Predicting Toxicity of Aliphatic Compounds towards Tetrahymena pyriformis

1Department of Chemistry, University of Kashmir, Srinagar, Kashmir 190006, India
2Department of Chemistry and Center for Theoretical Studies, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721 302, India

Received 9 September 2010; Revised 16 November 2010; Accepted 15 December 2010

Academic Editor: Pierre Esteves

Copyright © 2010 Altaf Hussain Pandith et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Quantum chemical parameters such as LUMO energy, HOMO energy, ionization energy (I), electron affinity (A), chemical potential (), hardness () electronegativity (), philicity (), and electrophilicity () of a series of aliphatic compounds are calculated at the B3LYP/6-31G(d) level of theory. Quantitative structure-activity relationship (QSAR) models are developed for predicting the toxicity () of 13 classes of aliphatic compounds, including 171 electron acceptors and 81 electron donors, towards Tetrahymena pyriformis. The multiple linear regression modeling of toxicity of these compounds is performed by using the molecular descriptor log P (1-octanol/water partition coefficient) in conjunction with two other quantum chemical descriptors, electrophilicity () and energy of the lowest unoccupied molecular orbital (). A comparison is made towards the toxicity predicting the ability of electrophilicity () versus as a global chemical reactivity descriptor in addition to log P. The former works marginally better in most cases. There is a slight improvement in the quality of regression by changing the unit of from mg/L to molarity and by removing the racemates and the diastereoisomers from the data set.