QSAR on aryl-piperazine derivatives with activity on malaria

In this work we offer linear regression models on a set of aryl-piperazine derivatives that are obtained by exploring a pool containing 1497 Dragon molecular descriptors, in order to establish the best relationships linking the molecular structure characteristics to their exhibited potencies against...

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Detalles Bibliográficos
Autores: Ibezim, Emmanuel, Duchowicz, Pablo Román, Ortiz, Erlinda del Valle, Castro, Eduardo Alberto
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2012
País:Argentina
Institución:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositorio:CONICET Digital (CONICET)
Idioma:inglés
OAI Identifier:oai:ri.conicet.gov.ar:11336/82984
Acceso en línea:http://hdl.handle.net/11336/82984
Access Level:acceso abierto
Palabra clave:Artemisinin
Aryl-Piperazines
Molecular Descriptors
Qsar Theory
Replacement Method
https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
Descripción
Sumario:In this work we offer linear regression models on a set of aryl-piperazine derivatives that are obtained by exploring a pool containing 1497 Dragon molecular descriptors, in order to establish the best relationships linking the molecular structure characteristics to their exhibited potencies against chloroquine resistant and chloroquine sensitive strains of Plasmodium falciparum parasite. The adjustment of the training molecular set together with the performance achieved during the internal and external validation processes leads to predictive QSAR models. In addition, we derive alternative linear models based on the Coral methodology, which lead to satisfactory results. We apply the final equations to predict the activity on some unknown compounds having non-observed activities.