Clarivate Analytics, 08025 Barcelona, Spain.
Laboratoire de Physique Théorique, IRSAMC, Université de Toulouse, CNRS, UPS, 31062 Toulouse, France.
Int J Mol Sci. 2021 Dec 22;23(1):67. doi: 10.3390/ijms23010067.
Protein-protein interactions is a longstanding challenge in cardiac remodeling processes and heart failure. Here, we use the MetaCore network and the Google matrix algorithms for prediction of protein-protein interactions dictating cardiac fibrosis, a primary cause of end-stage heart failure. The developed algorithms allow identification of interactions between key proteins and predict new actors orchestrating fibroblast activation linked to fibrosis in mouse and human tissues. These data hold great promise for uncovering new therapeutic targets to limit myocardial fibrosis.
蛋白质-蛋白质相互作用是心脏重构过程和心力衰竭的长期挑战。在这里，我们使用 MetaCore 网络和 Google 矩阵算法来预测决定心脏纤维化的蛋白质-蛋白质相互作用，心脏纤维化是心力衰竭终末期的主要原因。开发的算法允许识别关键蛋白之间的相互作用，并预测新的调节因子，这些因子与小鼠和人类组织中的纤维化相关的成纤维细胞激活有关。这些数据为揭示限制心肌纤维化的新治疗靶点提供了巨大的潜力。
