# Fibroblast-Specific Protein Interactions for Myocardial Fibrosis from MetaCore Network
## 4 Discussion and Conclusions
In a profibrotic scanario, TGF-\(\beta\)-activated kinase 1 (TAK1) is one of the best characterized non-Smad signal transducers critical for TGF-\(\beta\) functions in EMT and apoptosis through activating the c-Jun N-terminal kinase (JNK) and p38 MAPK cascade [50]. TAK1 also plays an essential role in mediating TGF-\(\beta\) activation of I-kappa B kinase (IKK) and the master transcription factor nuclear factor kappa B (NF-kB) that is required for cell survival [51]. In analogy to the mechanism defined in interleukin-1/Toll-like receptor pathways, TGF-\(\beta\)-induced activation of TAK1 requires TRAF6, a RING domain ubiquitin ligase that itself is modified by a K63-linked polyubiquitin chain, which acts as a scaffold to recruit TAK1 to the TGF-\(\beta\) receptor complex and triggers TAK1 activation [50]. Activity of TAK1 is also regulated by its binding proteins, including TAK1-binding protein 1 (TAB1) that binds constitutively the kinase domain and TAB2 or TAB3 that binds the C-terminal domain and functions as an adaptor linking TRAF6 to TAK1 [52]. However, how TGF-\(\beta\) coordinates TAK1 kinase to dictate the opposing responses of cell survival and apoptosis in different cellular scenarios. Thus the PPI network leads to a very complex system properties. In view of that we hope that the proposed INFI model may lead to better understading of PPI systems. The presented method of INFI model is based on mathematical properties of PPI networks and thus it is generic and universal. It can be applied to any other disease progression on PPI network and construction of Erdos barrage for disease propagation. As initial income for the application of this method a medical researcher should provide positive and negative responses on certain protein stimulation similar to those of Table 1 with TGF-\(\beta\) stimulation of fibrosis. Thus we developed an efficient method of the Erdos barrage when a small group of e.g., 4 repairing protein can reduce the number of fibrosis activated proteins (nodes) by a factor 300 leading to a healthy state of the global system described here by the MetaCore network. We expect that similar results can be obtained for other disease progression. We think that it would be very interesting to test this INFI approach with other global PPI networks like [35; 36]. We hope that the described INFI method will lead to new efficient medical treatments of fibrosis and other various diseases. Conceptualization, D.L.S. ; Investigation, K.M.F., E.K. and O.K. All authors equally contributed to all stages of this work. All authors have read and agreed to the published version of the manuscript. This research was supported in part through the grant NANOX N\({}^{\infty}\) ANR-17-EURE-0009, (project MTDINA) in the frame of the Programme des Investissements d'Avenir, France; it was granted access to the HPC resources of CALMIP (Toulouse) under the allocation 2024-P0110; it was also supported by INSERM funding. Not applicable. The data presented in this study are available on request from the corresponding author. We thank [PERSON] for useful discussions. Author [PERSON] was employed by Clarivate Analytics. The authors declare no conflict of interest.