Comparative QSAR Analysis of Bacterial-, Fungalplant- and Human Metabolites
Karakoc E, Sahinalp SC, Cherkasov A
School of Computing Science, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada.
Division of Infectious Diseases, Faculty of Medicine, University of British Columbia,
2733, Heather street, Vancouver, BC, V5Z 3J5, Canada
Pac Symp Biocomput. 2007;:133-144.
Several QSAR models have been developed using a linear optimization approach that
enabled distinguishing metabolic substances isolated from human-, bacterial-, plant- and
fungal- cells. Seven binary classifiers based on a k-Nearest Neighbors method have been
created using a variety of ‘inductive’ and traditional QSAR descriptors that allowed up
to 95% accurate recognition of the studied groups of chemical substances.
The conducted comparative QSAR analysis based on the above mentioned linear
optimization approach helped to identify the extent of overlaps between the groups of
compounds, such as cross-recognition of fungal and bacterial metabolites and
association between fungal and plant substances. Human metabolites exhibited very
different QSAR behavior in chemical space and demonstrated no significant overlap
with bacterial-, fungal-, and plant-derived molecules.
When the developed QSAR models were applied to collections of conventional human
therapeutics and antimicrobials, it was observed that the first group of substances
demonstrate the strongest association with human metabolites, while the second group
exhibit tendency of ‘bacterial metabolite – like’ behavior. We speculate that the
established ‘drugs - human metabolites’ and ‘antimicrobials – bacterial metabolites’
associations result from strict bioavailability requirements imposed on conventional
therapeutic substances, which further support their metabolite-like properties.
It is anticipated that the study may bring additional insight into QSAR determinants for
human-, bacterial-, fungal- and plant metabolites and may help rationalizing design and
discovery of novel bioactive substances with improved, metabolite-like properties.