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dc.contributor.authorShayanfar, A
dc.contributor.authorSoltani, S
dc.contributor.authorJouyban, A
dc.date.accessioned2018-08-26T06:15:25Z
dc.date.available2018-08-26T06:15:25Z
dc.date.issued2011
dc.identifier.urihttp://dspace.tbzmed.ac.ir:8080/xmlui/handle/123456789/43105
dc.description.abstractTwo simple multiple linear regression models were proposed to calculate the logarithm of the blood to brain concentration ratio (log BB) of drugs or drug-like compounds. The drugs were classified into two groups according to their ionization state in blood, and the significant parameters were selected using the train sets for each group. For un-ionizable compounds, the logarithm of distribution coefficient in octanol-water in pH 7.4 (log D(7.4)) and molecular weight are the significant parameters, whereas for ionizable compounds, log D(7.4) and number of hydrogen bond acceptor are significant parameters. The developed models were validated and their prediction capabilities checked using an external dataset of 25 compounds. In addition to the acceptable prediction errors, comparison of the external data analysis results with previously proposed models confirmed superior prediction capability of newly developed models.
dc.language.isoEnglish
dc.relation.ispartofBiological & pharmaceutical bulletin
dc.subjectBiological Transport
dc.subjectBlood-Brain Barrier
dc.subjectCentral Nervous System Agents
dc.subjectDrug Discovery
dc.subjectHydrogen Bonding
dc.subjectHydrogen-Ion Concentration
dc.subjectIons
dc.subjectLinear Models
dc.subjectModels, Biological
dc.subjectMolecular Weight
dc.subjectOctanols
dc.subjectReproducibility of Results
dc.subjectWater
dc.titlePrediction of blood-brain distribution: effect of ionization.
dc.typearticle
dc.citation.volume34
dc.citation.issue2
dc.citation.spage266
dc.citation.epage71
dc.citation.indexPubmed


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