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Please use this identifier to cite or link to this item: http://www.erepo.iihr.ernet.in/handle/123456789/256

Title: Quantitative structure-fungitoxicity relationships of some monohydric alcohols
Authors: Eugene Sebastian, J. Nidiry
Keywords: Monohydric alcohols
fungitoxicity
Colletotrichum gloeosporioides
quantitative structure−activity relationships
calculated partition coefficient
relative molecular connectivity
class of alcohol
double bonds
Issue Date: Aug-2003
Publisher: ACS publications
Citation: Eugene Sebastian J Nidiry. 2003. Quantitative structure-fungitoxicity relationships of some monohydric alcohols. J Agric Food Chem. 51 (18):5337-5743.
Abstract: The fungitoxicity data of some monohydric alcohols on the mycelial growth inhibition of Colletotrichum gloeosporioides were subjected to quantitative structure-activity relationship (QSAR) studies. The very large variation in the median effective concentrations ranging from >24000 mg/L [pEC(50)(mol/L)= 0.11] in the case of methanol to <100 mg/L [pEC(50)(mol/L)= 3.27] in the case of citronellol was found to depend mainly on changes in calculated partition coefficients (CLogP) of the compounds. The other three factors that affected the variation in fungitoxicity are the number of hydrogen atoms on the carbon bearing the hydroxyl group (N(H)), which determines the class of the alcohol to be primary, secondary, or tertiary, the number of double bonds (N(=)), and the branching of the alkyl moiety. Because many compounds in the set under study belonged to homologous series, there was a collinearity between CLogP values and Kier's molecular connectivity values (chi), which are usually used as branching indices. The problem of collinearity between CLogP values and branching indices was overcome by taking the relative molecular connectivity (chi(rel)), which is defined as the ratio of molecular connectivity of the alcohol under consideration to the molecular connectivity of the corresponding straight-chain primary alcohol with the same number of carbon atoms. Apart from the excellent correlations obtained in the equations, the credibility of the QSAR model could also be demonstrated by its application to published data taken from the literature.
URI: http://hdl.handle.net/123456789/256
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