title: Retrieval of Enterobacteriaceae drug targets using singular value decomposition.
abstract: BACKGROUND
  The identification of potential drug target proteins in bacteria is important in pharmaceutical research for the development of new antibiotics to combat bacterial agents that cause diseases.
  
  
  RESULTS
  A new model that combines the singular value decomposition (SVD) technique with biological filters composed of a set of protein properties associated with bacterial drug targets and similarity to protein-coding essential genes of Escherichia coli (strain K12) has been created to predict potential antibiotic drug targets in the Enterobacteriaceae family. This model identified 99 potential drug target proteins in the studied family, which exhibit eight different functions and are protein-coding essential genes or similar to protein-coding essential genes of E.coli (strain K12), indicating that the disruption of the activities of these proteins is critical for cells. Proteins from bacteria with described drug resistance were found among the retrieved candidates. These candidates have no similarity to the human proteome, therefore exhibiting the advantage of causing no adverse effects or at least no known adverse effects on humans.
  
  
  BACKGROUND
  rita_silverio@hotmail.com.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Institute of Biological Sciences and Department of Computer Science, Federal University of Minas Gerais, Belo Horizonte, MG 31270-901, Brazil and Centro Universitário de Belo Horizonte/UNI-BH, Belo Horizonte, MG 30455-610, Brazil.
authors.forename: Rita
authors.initials: R
authors.lastname: Silvério-Machado
authors.affiliation: Institute of Biological Sciences and Department of Computer Science, Federal University of Minas Gerais, Belo Horizonte, MG 31270-901, Brazil and Centro Universitário de Belo Horizonte/UNI-BH, Belo Horizonte, MG 30455-610, Brazil.
authors.forename: Bráulio R G M
authors.initials: BR
authors.lastname: Couto
authors.affiliation: Institute of Biological Sciences and Department of Computer Science, Federal University of Minas Gerais, Belo Horizonte, MG 31270-901, Brazil and Centro Universitário de Belo Horizonte/UNI-BH, Belo Horizonte, MG 30455-610, Brazil.
authors.forename: Marcos A
authors.initials: MA
authors.lastname: Dos Santos
mesh_terms: D000465:Algorithms; D000900:Anti-Bacterial Agents / Q000494:pharmacology*; D001426:Bacterial Proteins / Q000235:genetics* / Q000378:metabolism; D016503:Drug Delivery Systems; D024881:Drug Resistance, Bacterial / Q000235:genetics*; D004755:Enterobacteriaceae / Q000187:drug effects / Q000235:genetics*; D004926:Escherichia coli / Q000187:drug effects / Q000235:genetics*; D006801:Humans
chemical_list: D000900:Anti-Bacterial Agents; D001426:Bacterial Proteins