Please use this identifier to cite or link to this item: http://ri.uaemex.mx/handle20.500.11799/79879
DC FieldValueLanguage
dc.creatorESVIETA TENORIO BORROTO-
dc.creatorCLAUDIA GIOVANNA PEÑUELAS RIVAS-
dc.creatorJUAN CARLOS VAZQUEZ CHAGOYAN-
dc.creatorNilo Ramón Castañedo Cancio-
dc.creatorFRANCISCO JAVIER PRADO PRADO-
dc.creatorXerardo Garcia-Mera-
dc.creatorHUMBERTO GONZALEZ DIAZ-
dc.date2014-01-05-
dc.date.accessioned2022-04-21T05:17:57Z-
dc.date.available2022-04-21T05:17:57Z-
dc.identifierhttp://hdl.handle.net/20.500.11799/79879-
dc.identifier.urihttp://ri.uaemex.mx/handle20.500.11799/79879-
dc.descriptionModelos matematicos y citometria-
dc.descriptionQuantitative Structure-Activity (mt-QSAR) techniques may become an important tool for prediction of cytotoxicity and High-throughput Screening (HTS) of drugs to rationalize drug discovery process. In this work, we train and validate by the first time mt-QSAR model using TOPS-MODE approach to calculate drug molecular descriptors and Linear Discriminant Analysis (LDA) function. This model correctly classifies 8,258 out of 9,000 (Accuracy = 91.76%) multiplexing assay endpoints of 7903 drugs (including both train and validation series). Each endpoint correspond to one out of 1418 assays, 36 molecular and cellular targets, 46 standard type measures, in two possible organisms (human and mouse). After that, we determined experimentally, by the first time, the values of EC50 = 21.58 μg/mL and Cytotoxicity = 23.6 % for the anti-microbial / antiparasite drug G1 over Balb/C mouse peritoneal macrophages using flow cytometry. In addition, the model predicts for G1 only 7 positive endpoints out 1,251 cytotoxicity assays (0.56% of probability of cytotoxicity in multiple assays). The results obtained complement the toxicological studies of this important drug. This work adds a new tool to the existing pool of few methods useful for multi-target HTS of ChEMBL and other libraries of compounds towards drug discovery.-
dc.descriptionConacyt-
dc.languageeng-
dc.publisherEuropean Journal of Medicinal Chemistry-
dc.relation24;-
dc.rightsinfo:eu-repo/semantics/openAccess-
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0-
dc.source0223-5234-
dc.subjectFlow cytometry-
dc.subjectHigh-throughput model-
dc.subjectDrug immunotoxicity-
dc.subjectMultiplex assay endpoints-
dc.subjectinfo:eu-repo/classification/cti/3-
dc.titleModel for High-Throughput Screening of drug immunotoxicity - study of the antimicrobial G1 over peritoneal macrophages using flow cytometry-
dc.typearticle-
dc.audiencestudents-
dc.audienceresearchers-
item.grantfulltextnone-
item.fulltextNo Fulltext-
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