Assessing the risk of infection from emerging viruses or of existing viruses jumping the species barrier into novel hosts is limited by the lack of dose response data. The initial stages of the infection of a host by a virus involve a series of specific contact interactions between molecules in the host and on the virus surface. The strength of the interaction is quantified in the literature by the dissociation constant (K_d) which is determined experimentally and is specific for a given virus molecule/host molecule combination. Here, two stages of the initial infection process of host intestinal cells are modelled, namely escape of the virus in the oral challenge dose from the innate host defenses (e.g. mucin proteins in mucus) and the subsequent binding of any surviving virus to receptor molecules on the surface of the host epithelial cells. The strength of virus binding to host cells and to mucins may be quantified by the association constants, K_a and K_mucin, respectively. Here, a mechanistic dose-response model for the probability of infection of a host by a given virus dose is constructed using K_a and K_mucin which may be derived from published K_d values taking into account the number of specific molecular interactions. It is shown that the effectiveness of the mucus barrier is determined not only by the amount of mucin but also by the magnitude of K_mucin. At very high K_mucin values, slight excesses of mucin over virus are sufficient to remove all the virus according to the model. At lower K_mucin values, high numbers of virus may escape even with large excesses of mucin. The output from the mechanistic model is the probability (p₁) of infection by a single virion which is the parameter used in conventional dose-response models to predict the risk of infection of the host from the ingested dose. It is shown here how differences in K_a (due to molecular differences in an emerging virus strain or new host) affect p₁, and how these differences in K_a may be quantified in terms of two thermodynamic parameters, namely enthalpy and entropy. This provides the theoretical link between sequencing data and risk of infection. Lack of data on entropy is a limitation at present and may also affect our interpretation of K_d in terms of infectivity. It is concluded that thermodynamic approaches have a major contribution to make in developing dose-response models for emerging viruses.

缺乏剂量反应数据限制了评估新兴病毒或现有病毒将物种屏障带入新型宿主的感染风险。病毒感染宿主的初始阶段涉及宿主中以及病毒表面上的分子之间的一系列特定的接触相互作用。相互作用的强度在文献中通过解离常数（K _d），通过实验确定，并且对给定的病毒分子/宿主分子组合具有特异性。在此，对宿主肠道细胞初始感染过程的两个阶段进行了建模，即口服攻击剂量的病毒从固有宿主防御系统（例如粘液中的粘蛋白）逃逸，以及随后任何存活的病毒与受体上的受体分子结合宿主上皮细胞的表面。病毒与宿主细胞和粘蛋白的结合强度可以分别通过缔合常数K _a和K _mucin定量。在这里，使用K _a和K_粘蛋白构建机械剂量响应模型，该模型可以通过给定的病毒剂量感染宿主，并可以从已发表的K中获得_d值考虑了特定分子相互作用的数量。结果表明，黏液屏障的有效性不仅由黏蛋白的量决定，而且由K_黏蛋白的大小决定。在非常高的K_粘蛋白值下，根据模型，粘蛋白比病毒稍微过量就足以清除所有病毒。在较低的K_黏蛋白值下，即使大量过量的黏蛋白也可能逃脱大量病毒。机械模型的输出是单个病毒体感染的概率（p ₁），这是常规剂量反应模型中用来从摄入剂量预测宿主感染风险的参数。此处显示了K _a的差异（由于新出现的病毒株或新宿主中的分子差异）影响p ₁，以及如何根据两个热力学参数（即焓和熵）量化K _a的这些差异。这提供了测序数据和感染风险之间的理论联系。目前缺乏关于熵的数据是一个局限，也可能影响我们对K _d的传染性解释。结论是，热力学方法在开发新兴病毒的剂量反应模型方面做出了重大贡献。