New similarity-based algorithm and its application to classification of anticonvulsant compounds

A similarity-based algorithm based on a previously developed model is applied in the classification of two sets of anticonvulsant and non-anticonvulsant drugs. Each set is composed of a) anticonvulsant compounds that have shown moderate to high activity in the Maximal Electroshock Seizure (MES) test...

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Detalles Bibliográficos
Autores principales: Talevi, Alan, Prieto, Julián José, Bruno Blanch, Luis Enrique, Castro, Eduardo Alberto
Formato: Articulo
Lenguaje:Inglés
Publicado: 2007
Materias:
Ciencias Exactas
Química
Física
Anticonvulsant
Molecular topology
Atom pairs
MES test
Chemical substructure
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/124004
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-124004
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Exactas
Química
Física
Anticonvulsant
Molecular topology
Atom pairs
MES test
Chemical substructure
spellingShingle Ciencias Exactas
Química
Física
Anticonvulsant
Molecular topology
Atom pairs
MES test
Chemical substructure
Talevi, Alan
Prieto, Julián José
Bruno Blanch, Luis Enrique
Castro, Eduardo Alberto
New similarity-based algorithm and its application to classification of anticonvulsant compounds
topic_facet Ciencias Exactas
Química
Física
Anticonvulsant
Molecular topology
Atom pairs
MES test
Chemical substructure
description A similarity-based algorithm based on a previously developed model is applied in the classification of two sets of anticonvulsant and non-anticonvulsant drugs. Each set is composed of a) anticonvulsant compounds that have shown moderate to high activity in the Maximal Electroshock Seizure (MES) test and b) drugs with other biological activities or poor activity in the MES test. The results from the analysis of variance (ANOVA) indicate that the proposed algorithm is able to differentiate anticonvulsant from non-anticonvulsant drugs. The proposed model may then be useful in the identification of new anticonvulsant agents through virtual screening of large virtual libraries of chemical structures.
format Articulo
Articulo
author Talevi, Alan
Prieto, Julián José
Bruno Blanch, Luis Enrique
Castro, Eduardo Alberto
author_facet Talevi, Alan
Prieto, Julián José
Bruno Blanch, Luis Enrique
Castro, Eduardo Alberto
author_sort Talevi, Alan
title New similarity-based algorithm and its application to classification of anticonvulsant compounds
title_short New similarity-based algorithm and its application to classification of anticonvulsant compounds
title_full New similarity-based algorithm and its application to classification of anticonvulsant compounds
title_fullStr New similarity-based algorithm and its application to classification of anticonvulsant compounds
title_full_unstemmed New similarity-based algorithm and its application to classification of anticonvulsant compounds
title_sort new similarity-based algorithm and its application to classification of anticonvulsant compounds
publishDate 2007
url http://sedici.unlp.edu.ar/handle/10915/124004
work_keys_str_mv AT talevialan newsimilaritybasedalgorithmanditsapplicationtoclassificationofanticonvulsantcompounds
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AT brunoblanchluisenrique newsimilaritybasedalgorithmanditsapplicationtoclassificationofanticonvulsantcompounds
AT castroeduardoalberto newsimilaritybasedalgorithmanditsapplicationtoclassificationofanticonvulsantcompounds
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