Viruses rely on their host for reproduction. Here, we made use of genomic and structural information to create a biomass function capturing the amino and nucleic acid requirements of SARS-CoV-2. Incorporating this biomass function into a stoichiometric metabolic model of the human lung cell and applying metabolic flux balance analysis, we identified host-based metabolic perturbations inhibiting SARS-CoV-2 reproduction. Our results highlight reactions in the central metabolism, as well as amino acid and nucleotide biosynthesis pathways. By incorporating host cellular maintenance into the model based on available protein expression data from human lung cells, we find that only few of these metabolic perturbations are able to selectively inhibit virus reproduction. Some of the catalysing enzymes of such reactions have demonstrated interactions with existing drugs, which can be used for experimental testing of the presented predictions using gene knockouts and RNA interference techniques. In summary, the developed computational approach offers a platform for rapid, experimentally testable generation of drug predictions against existing and emerging viruses based on their biomass requirements.

中文翻译：

---

通过扰动人类肺细胞代谢网络来抑制SARS-CoV-2的繁殖。

病毒依靠其宿主进行繁殖。在这里，我们利用基因组和结构信息来创建捕获SARS-CoV-2氨基酸和核酸需求的生物量功能。将这种生物量功能纳入人肺细胞的化学计量代谢模型并应用代谢通量平衡分析，我们确定了基于宿主的代谢扰动抑制了SARS-CoV-2的繁殖。我们的结果突出了中枢代谢中的反应以及氨基酸和核苷酸的生物合成途径。通过基于来自人肺细胞的可用蛋白质表达数据将宿主细胞的维持作用纳入模型，我们发现这些代谢扰动中只有极少数能够选择性地抑制病毒繁殖。此类反应的某些催化酶已证明与现有药物发生相互作用，可使用基因敲除和RNA干扰技术对所提出的预测进行实验测试。总之，已开发的计算方法提供了一个平台，可根据其生物量需求快速，通过实验测试生成针对现有和新兴病毒的药物预测。