Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets.
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.
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.
Arunachalam
A
Vinayagam
Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115;
Travis E
TE
Gibson
Department of Systems Biology, Harvard Medical School, Boston, MA 02115;
Ho-Joon
HJ
Lee
Drosophila RNAi Screening Center, Department of Genetics, Harvard Medical School, Boston, MA 02115; Bioinformatics Program, Northeastern University, Boston, MA 02115;
Bahar
B
Yilmazel
Drosophila RNAi Screening Center, Department of Genetics, Harvard Medical School, Boston, MA 02115; Bioinformatics Program, Northeastern University, Boston, MA 02115;
Charles
C
Roesel
Department of Genetics, Harvard Medical School, Boston, MA 02115; Drosophila RNAi Screening Center, Department of Genetics, Harvard Medical School, Boston, MA 02115;
Yanhui
Y
Hu
Department of Genetics, Harvard Medical School, Boston, MA 02115;
Young
Y
Kwon
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;
Amitabh
A
Sharma
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; vinu@genetics.med.harvard.edu yyl@channing.harvard.edu perrimon@receptor.med.harvard.edu alb@neu.edu.
Yang-Yu
YY
Liu
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.
Norbert
N
Perrimon
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.
Albert-László
AL
Barabási
D020022:Genetic Predisposition to Disease; D006801:Humans; D009154:Mutation; D011485:Protein Binding; D011506:Proteins / Q000378:metabolism*
D011506:Proteins
controllability; disease genes; drug targets; network biology; protein–protein interaction network