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Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets.
Vinayagam, Arunachalam; Gibson, Travis E; Lee, Ho-Joon; Yilmazel, Bahar; Roesel, Charles; Hu, Yanhui; Kwon, Young; Sharma, Amitabh; Liu, Yang-Yu; Perrimon, Norbert; Barabási, Albert-László.
Afiliação
  • Vinayagam A; Department of Genetics, Harvard Medical School, Boston, MA 02115; vinu@genetics.med.harvard.edu yyl@channing.harvard.edu perrimon@receptor.med.harvard.edu alb@neu.edu.
  • Gibson TE; Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115;
  • Lee HJ; Department of Systems Biology, Harvard Medical School, Boston, MA 02115;
  • Yilmazel B; Drosophila RNAi Screening Center, Department of Genetics, Harvard Medical School, Boston, MA 02115; Bioinformatics Program, Northeastern University, Boston, MA 02115;
  • Roesel C; Drosophila RNAi Screening Center, Department of Genetics, Harvard Medical School, Boston, MA 02115; Bioinformatics Program, Northeastern University, Boston, MA 02115;
  • Hu Y; Department of Genetics, Harvard Medical School, Boston, MA 02115; Drosophila RNAi Screening Center, Department of Genetics, Harvard Medical School, Boston, MA 02115;
  • Kwon Y; Department of Genetics, Harvard Medical School, Boston, MA 02115;
  • Sharma A; Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115; Center for Complex Network Research, Department of Physics, Northeastern University, Boston, MA 02115; Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Boston, MA 02115;
  • Liu YY; Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115; Center for Complex Network Research, Department of Physics, Northeastern University, Boston, MA 02115; Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Boston, MA 02115; vin
  • Perrimon N; Department of Genetics, Harvard Medical School, Boston, MA 02115; Howard Hughes Medical Institute, Harvard Medical School, MA 02115 vinu@genetics.med.harvard.edu yyl@channing.harvard.edu perrimon@receptor.med.harvard.edu alb@neu.edu.
  • Barabási AL; Center for Complex Network Research, Department of Physics, Northeastern University, Boston, MA 02115; Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Boston, MA 02115; vinu@genetics.med.harvard.edu yyl@channing.harvard.edu perrimon@receptor.med.harvard.edu alb@neu.edu.
Proc Natl Acad Sci U S A ; 113(18): 4976-81, 2016 May 03.
Article em En | MEDLINE | ID: mdl-27091990
ABSTRACT
The protein-protein interaction (PPI) network is crucial for cellular information processing and decision-making. With suitable inputs, PPI networks drive the cells to diverse functional outcomes such as cell proliferation or cell death. Here, we characterize the structural controllability of a large directed human PPI network comprising 6,339 proteins and 34,813 interactions. This network allows us to classify proteins as "indispensable," "neutral," or "dispensable," which correlates to increasing, no effect, or decreasing the number of driver nodes in the network upon removal of that protein. We find that 21% of the proteins in the PPI network are indispensable. Interestingly, these indispensable proteins are the primary targets of disease-causing mutations, human viruses, and drugs, suggesting that altering a network's control property is critical for the transition between healthy and disease states. Furthermore, analyzing copy number alterations data from 1,547 cancer patients reveals that 56 genes that are frequently amplified or deleted in nine different cancers are indispensable. Among the 56 genes, 46 of them have not been previously associated with cancer. This suggests that controllability analysis is very useful in identifying novel disease genes and potential drug targets.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteínas / Predisposição Genética para Doença Limite: Humans Idioma: En Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteínas / Predisposição Genética para Doença Limite: Humans Idioma: En Ano de publicação: 2016 Tipo de documento: Article