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Molecules 2004, 9(12), 1034-1052; doi:10.3390/91201034

Application of ‘Inductive’ QSAR Descriptors for Quantification of Antibacterial Activity of Cationic Polypeptides

1
Division of Infectious Diseases, Faculty of Medicine, University of British Columbia, 2733 Heather Street, Vancouver, BC, V5Z 3J5, Canada
2
BC Cancer Research Centre, 601 West 10th Avenue, Vancouver, BC, V5Z 4E6, Canada
*
Author to whom correspondence should be addressed.
Received: 25 May 2004 / Accepted: 14 June 2004 / Published: 31 December 2004
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Abstract

On the basis of the inductive QSAR descriptors we have created a neural network-based solution enabling quantification of antibacterial activity in the series of 101 synthetic cationic polypeptides (CAMEL-s). The developed QSAR model allowed 80% correct categorical classification of antibacterial potencies of the CAMEL-s both in the training and the validation sets. The accuracy of the activity predictions demonstrates that a narrow set of 3D sensitive ‘inductive’ descriptors can adequately describe the aspects of intra- and intermolecular interactions that are relevant for antibacterial activity of the cationic polypeptides. The developed approach can be further expanded for the larger sets of biologically active peptides and can serve as a useful quantitative tool for rational antibiotic design and discovery. View Full-Text
Keywords: QSAR; inductive descriptors; antibacterial peptides; antibiotics. QSAR; inductive descriptors; antibacterial peptides; antibiotics.
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Cherkasov, A.; Jankovic, B. Application of ‘Inductive’ QSAR Descriptors for Quantification of Antibacterial Activity of Cationic Polypeptides. Molecules 2004, 9, 1034-1052.

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