title: Robustness and evolvability of the human signaling network.
abstract: Biological systems are known to be both robust and evolvable to internal and external perturbations, but what causes these apparently contradictory properties? We used Boolean network modeling and attractor landscape analysis to investigate the evolvability and robustness of the human signaling network. Our results show that the human signaling network can be divided into an evolvable core where perturbations change the attractor landscape in state space, and a robust neighbor where perturbations have no effect on the attractor landscape. Using chemical inhibition and overexpression of nodes, we validated that perturbations affect the evolvable core more strongly than the robust neighbor. We also found that the evolvable core has a distinct network structure, which is enriched in feedback loops, and features a higher degree of scale-freeness and longer path lengths connecting the nodes. In addition, the genes with high evolvability scores are associated with evolvability-related properties such as rapid evolvability, low species broadness, and immunity whereas the genes with high robustness scores are associated with robustness-related properties such as slow evolvability, high species broadness, and oncogenes. Intriguingly, US Food and Drug Administration-approved drug targets have high evolvability scores whereas experimental drug targets have high robustness scores.
authors: Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Yuseong-gu, Daejeon, Republic of Korea.
authors: Junil
authors: J
authors: Kim
authors: Systems Biology Ireland, University College Dublin, Dublin, Ireland.
authors: Drieke
authors: D
authors: Vandamme
authors: Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Yuseong-gu, Daejeon, Republic of Korea; Department of Mathematics, University of Seoul, Seoul, Republic of Korea.
authors: Jeong-Rae
authors: JR
authors: Kim
authors: Systems Biology Ireland, University College Dublin, Dublin, Ireland.
authors: Amaya Garcia
authors: AG
authors: Munoz
authors: Systems Biology Ireland, University College Dublin, Dublin, Ireland; Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland; School of Medicine and Medical Science, University College Dublin, Dublin, Ireland.
authors: Walter
authors: W
authors: Kolch
authors: Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Yuseong-gu, Daejeon, Republic of Korea.
authors: Kwang-Hyun
authors: KH
authors: Cho
mesh_terms: D000465:Algorithms; D055808:Drug Discovery; D019143:Evolution, Molecular; D006801:Humans; D008954:Models, Biological; D015398:Signal Transduction / Q000235:genetics* / Q000502:physiology*