Signaling Systems Laboratory, Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA 92093, USA; San Diego Center for Systems Biology, University of California, San Diego, La Jolla, CA 92093, USA; Computational Biosciences Institute, University of California, Los Angeles, Los Angeles, CA 90025, USA; Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA 90025, USA.
Cell. 2013 Oct 10;155(2):448-61. doi: 10.1016/j.cell.2013.09.018.
Highly networked signaling hubs are often associated with disease, but targeting them pharmacologically has largely been unsuccessful in the clinic because of their functional pleiotropy. Motivated by the hypothesis that a dynamic signaling code confers functional specificity, we investigated whether dynamic features may be targeted pharmacologically to achieve therapeutic specificity. With a virtual screen, we identified combinations of signaling hub topologies and dynamic signal profiles that are amenable to selective inhibition. Mathematical analysis revealed principles that may guide stimulus-specific inhibition of signaling hubs, even in the absence of detailed mathematical models. Using the NFκB signaling module as a test bed, we identified perturbations that selectively affect the response to cytokines or pathogen components. Together, our results demonstrate that the dynamics of signaling may serve as a pharmacological target, and we reveal principles that delineate the opportunities and constraints of developing stimulus-specific therapeutic agents aimed at pleiotropic signaling hubs.
高度网络化的信号枢纽通常与疾病有关，但由于其功能多效性，临床上靶向它们进行药物治疗在很大程度上尚未成功。受动态信号编码赋予功能特异性的假设的启发，我们研究了是否可以通过靶向药物治疗来针对动态特征以实现治疗特异性。通过虚拟筛选，我们确定了可进行选择性抑制的信号枢纽拓扑结构和动态信号特征的组合。数学分析揭示了即使在没有详细的数学模型的情况下，也可能指导信号枢纽刺激特异性抑制的原则。我们使用 NFκB 信号模块作为测试平台，确定了选择性影响细胞因子或病原体成分反应的扰动。总之，我们的结果表明信号的动态性可以作为一种药物靶点，并且我们揭示了阐明开发针对多效性信号枢纽的刺激特异性治疗剂的机会和限制的原则。
