Luan Deyan, Szlam Fania, Tanaka Kenichi A, Barie Philip S, Varner Jeffrey D
School of Chemical and Biomolecular Engineering, Cornell University, 244 Olin Hall, Ithaca NY 14853, USA.
Mol Biosyst. 2010 Nov;6(11):2272-86. doi: 10.1039/b920693k. Epub 2010 Sep 16.
The role of mechanistic modeling and systems biology in molecular medicine remains unclear. In this study, we explored whether uncertain models could be used to understand how a network responds to a therapeutic intervention. As a proof of concept, we modeled and analyzed the response of the human coagulation cascade to recombinant factor VIIa (rFVIIa) and prothrombin (fII) addition in normal and hemophilic plasma. An ensemble of parametrically uncertain human coagulation models was developed (N = 437). Each model described the time evolution of 193 proteins and protein complexes interconnected by 301 interactions under quiescent flow. The 467 unknown model parameters were estimated, using multiobjective optimization, from published in vitro coagulation studies. The model ensemble was validated using published in vitro thrombin measurements and thrombin measurements taken from coronary artery disease patients. Sensitivity analysis was then used to rank-order the importance of model parameters as a function of experimental or physiological conditions. A novel strategy for the systematic comparison of ranks identified a family of fX/FXa and fII/FIIa interactions that became more sensitive with decreasing fVIII/fIX. The fragility of these interactions was preserved following the addition of exogenous rFVIIa and fII. This suggested that exogenous rFVIIa did not alter the qualitative operation of the cascade. Rather, exogenous rFVIIa and fII took advantage of existing fluid and interfacial fX/FXa and fII/FIIa sensitivity to restore normal coagulation in low fVIII/fIX conditions. The proposed rFVIIa mechanism of action was consistent with experimental literature not used in model training. Thus, we demonstrated that an ensemble of uncertain models could unravel key facets of the mechanism of action of a focused intervention. Whereas the current study was limited to coagulation, perhaps the general strategy used could be extended to other molecular networks relevant to human health.
机械建模和系统生物学在分子医学中的作用仍不明确。在本研究中，我们探讨了不确定模型是否可用于理解网络对治疗干预的反应。作为概念验证，我们对正常和血友病血浆中添加重组因子VIIa（rFVIIa）和凝血酶原（fII）后人凝血级联反应的反应进行了建模和分析。构建了一组参数不确定的人凝血模型（N = 437）。每个模型描述了在静态流动下由301个相互作用相互连接的193种蛋白质和蛋白质复合物的时间演变。使用多目标优化从已发表的体外凝血研究中估计了467个未知模型参数。使用已发表的体外凝血酶测量值和从冠状动脉疾病患者获得的凝血酶测量值对模型集进行了验证。然后使用敏感性分析根据实验或生理条件对模型参数的重要性进行排序。一种用于系统比较排名的新策略确定了一组fX/FXa和fII/FIIa相互作用，随着fVIII/fIX的降低，这些相互作用变得更加敏感。添加外源性rFVIIa和fII后，这些相互作用的脆弱性得以保留。这表明外源性rFVIIa不会改变级联反应的定性操作。相反，外源性rFVIIa和fII利用现有的流体和界面fX/FXa以及fII/FIIa敏感性在低fVIII/fIX条件下恢复正常凝血。所提出的rFVIIa作用机制与未用于模型训练的实验文献一致。因此，我们证明了一组不确定模型可以揭示聚焦干预作用机制的关键方面。虽然目前的研究仅限于凝血，但也许所使用的一般策略可以扩展到与人类健康相关的其他分子网络。
