Artificial neural network applied to the discrimination of antibacterial activity by topological methods

A new topological method that makes it possible to discriminate the active and inactive molecules on the basis of their chemical structures is applied in the present study to the antibacterial agents. This method uses neural networks in which training algorithms are used as well as different concept...

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Bibliographic Details
Published in:Journal of molecular structure. Theochem 2000-06, Vol.504 (1), p.249-259
Main Authors: Tomás-Vert, F., Pérez-Giménez, F., Salabert-Salvador, Ma.T., Garcı&#x0301, a-March, F.J., Jaén-Oltra, J.
Format: Article
Language:English
Subjects:
Antibacterial agents
Neural networks
Quantitative structure–activity relationship
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Summary:A new topological method that makes it possible to discriminate the active and inactive molecules on the basis of their chemical structures is applied in the present study to the antibacterial agents. This method uses neural networks in which training algorithms are used as well as different concepts and methods of artificial intelligence with a suitable set of topological descriptors. It is possible to obtain a QSAR interpretation of the information contained in the network after the training has been carried out.
ISSN:0166-1280
1872-7999
DOI:10.1016/S0166-1280(00)00366-3