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Chemotext: A Publicly Available Web Server for Mining Drug-Target-Disease Relationships in PubMed.
Capuzzi, Stephen J; Thornton, Thomas E; Liu, Kammy; Baker, Nancy; Lam, Wai In; O'Banion, Colin P; Muratov, Eugene N; Pozefsky, Diane; Tropsha, Alexander.
Afiliação
  • Capuzzi SJ; Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina , Chapel Hill, North Carolina 27599, United States.
  • Thornton TE; Department of Computer Science, University of North Carolina , Chapel Hill, North Carolina 27599, United States.
  • Liu K; Department of Computer Science, University of North Carolina , Chapel Hill, North Carolina 27599, United States.
  • Baker N; Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina , Chapel Hill, North Carolina 27599, United States.
  • Lam WI; Department of Computer Science, University of North Carolina , Chapel Hill, North Carolina 27599, United States.
  • O'Banion CP; Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina , Chapel Hill, North Carolina 27599, United States.
  • Muratov EN; Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina , Chapel Hill, North Carolina 27599, United States.
  • Pozefsky D; Department of Chemical Technology, Odessa National Polytechnic University , Odessa, 65000, Ukraine.
  • Tropsha A; Department of Computer Science, University of North Carolina , Chapel Hill, North Carolina 27599, United States.
J Chem Inf Model ; 58(2): 212-218, 2018 02 26.
Article em En | MEDLINE | ID: mdl-29300482
Elucidation of the mechanistic relationships between drugs, their targets, and diseases is at the core of modern drug discovery research. Thousands of studies relevant to the drug-target-disease (DTD) triangle have been published and annotated in the Medline/PubMed database. Mining this database affords rapid identification of all published studies that confirm connections between vertices of this triangle or enable new inferences of such connections. To this end, we describe the development of Chemotext, a publicly available Web server that mines the entire compendium of published literature in PubMed annotated by Medline Subject Heading (MeSH) terms. The goal of Chemotext is to identify all known DTD relationships and infer missing links between vertices of the DTD triangle. As a proof-of-concept, we show that Chemotext could be instrumental in generating new drug repurposing hypotheses or annotating clinical outcomes pathways for known drugs. The Chemotext Web server is freely available at http://chemotext.mml.unc.edu .
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sistemas de Liberação de Medicamentos / Internet / PubMed / Medical Subject Headings / Tratamento Farmacológico / Mineração de Dados / Bases de Dados de Compostos Químicos Limite: Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sistemas de Liberação de Medicamentos / Internet / PubMed / Medical Subject Headings / Tratamento Farmacológico / Mineração de Dados / Bases de Dados de Compostos Químicos Limite: Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article