Pattern recognition methods investigation of ellipticines structure-activity relationships

dc.creatorde Melo, LC
dc.creatorBraga, SF
dc.creatorBarone, PMVB
dc.date2007
dc.dateMAR
dc.date2014-11-16T14:47:47Z
dc.date2015-11-26T17:25:25Z
dc.date2014-11-16T14:47:47Z
dc.date2015-11-26T17:25:25Z
dc.date.accessioned2018-03-29T00:12:39Z
dc.date.available2018-03-29T00:12:39Z
dc.identifierJournal Of Molecular Graphics & Modelling. Elsevier Science Inc, v. 25, n. 6, n. 912, n. 920, 2007.
dc.identifier1093-3263
dc.identifierWOS:000245802900018
dc.identifier10.1016/j.jmgm.2006.09.002
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/59160
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/59160
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/59160
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1284310
dc.descriptionEllipticine is a molecule derived from the natural extract Ochrosia elliptica. This molecule and its derivatives are highly cytotoxic to malignant cultured cells. The relatively simple structure of ellipticine has prompted chemists to design various structural modifications in order to obtain either more active derivatives or information on the structural moieties required for pharmacological activities. In the present work we report theoretical structure-activity relationship studies for 40 ellipticine derivatives using pattern-recognition methods such as electronics indices methodology (EIM), principal component analysis (PCA) and hierarchical clustering analysis (HCA) with molecular descriptors obtained from semiempirical parametric method 3 (PM3) calculations. By applying selected molecular descriptors it was possible to classify active and inactive compounds with accuracy up to 92% and also to suggest the activity of new untested molecules. These descriptors have been only recently discussed in the literature as new possible universal parameters for defining the biological activity of several classes of compounds. (c) 2006 Elsevier Inc. All rights reserved.
dc.description25
dc.description6
dc.description912
dc.description920
dc.languageen
dc.publisherElsevier Science Inc
dc.publisherNew York
dc.publisherEUA
dc.relationJournal Of Molecular Graphics & Modelling
dc.relationJ. Mol. Graph.
dc.rightsfechado
dc.rightshttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dc.sourceWeb of Science
dc.subjectellipticine
dc.subjectelectronic indices methodology
dc.subjecthierarchical clustering analysis
dc.subjectolivacine
dc.subjectprincipal component analysis
dc.subjectsemiempirical methods
dc.subjectstructure-activity relationships
dc.subjectPolycyclic Aromatic-hydrocarbons
dc.subjectIdentify Carcinogenic Activity
dc.subjectDrug-dna Interactions
dc.subjectElectronic Indexes
dc.subjectCytotoxic Activity
dc.subjectAntitumor Agents
dc.subjectNeural-network
dc.subjectDerivatives
dc.subjectSeries
dc.subjectBinding
dc.titlePattern recognition methods investigation of ellipticines structure-activity relationships
dc.typeArtículos de revistas


Este ítem pertenece a la siguiente institución