Recent advances in reconstruction and analytical methods for signaling networks have spurred the development of large-scale models that incorporate fully functional and biologically relevant features. An extended reconstruction of the human Toll-like receptor signaling network is presented herein. This reconstruction contains an extensive complement of kinases, phosphatases, and other associated proteins that mediate the signaling cascade along with a delineation of their associated chemical reactions. A computational framework based on the methods of large-scale convex analysis was developed and applied to this network to characterize input–output relationships. The input–output relationships enabled significant modularization of the network into ten pathways. The analysis identified potential candidates for inhibitory mediation of TLR signaling with respect to their specificity and potency. Subsequently, we were able to identify eight novel inhibition targets through constraint-based modeling methods. The results of this study are expected to yield meaningful avenues for further research in the task of mediating the Toll-like receptor signaling network and its effects.

The human innate immune system, as the first line of defense against pathogens, is a vital component of our survival. One component of the innate immune system is the Toll-like receptor signaling network, which is responsible for transmitting activation signals from the outside of the cell to molecular machinery inside the cell. The innate immune system must be properly balanced, as excessive activation can lead to potentially lethal septic shock. Therefore, there is much interest in developing drugs that can mediate Toll-like receptor signaling so as to alleviate effects of excess activation. We present an in silico reconstruction of the Toll-like receptor signaling network and convert it into a mathematical framework that is suitable for constraint-based modeling and analysis. This approach leads to the identification of potential candidates for drug-based mediation. In addition to identifying targets for drug mediation of the Toll-like receptor network, we also supply a network model that may be continually updated and maintained.