用于治疗 STING 相关炎症性疾病的 STING 抑制剂的开发继续遇到重大挑战。 STING 的激活是一个多步骤过程，包括与 cGAMP 结合、自身寡聚化以及从内质网易位至高尔基体，最终诱导 IRF3 和 NF-κB 介导的干扰素和炎症细胞因子的表达。已经证明，破坏这些步骤中的任何一个都可以有效抑制 STING 激活。传统的基于结构的药物筛选方法通常关注特定的结合位点。在本研究中，采用基于蛋白质一级序列且独立于结合位点的 TransformerCPI 模型来识别能够与 STING 蛋白质结合的化合物。天然产物 Licochalcone D (LicoD) 被认为是一种有效的选择性 STING 抑制剂。 LicoD 不结合经典的配体结合口袋；相反，它共价修饰 STING 的 Cys148 残基。这种修饰抑制 STING 寡聚化，从而抑制 TBK1 的募集以及 IRF3 和 NF-κB 的核转位。 LicoD 治疗可改善 Trex1-1- 小鼠的炎症表型，并抑制 DSS 诱导的结肠炎和 AOM/DSS 诱导的结肠炎相关结肠癌 (CAC) 的进展。总之，这项研究揭示了 LicoD 在治疗 STING 驱动的炎症性疾病方面的潜力。它还展示了 TransformerCPI 模型在发现传统结合袋之外的变构化合物方面的实用性。© 2024。中国科学出版社。

The development of STING inhibitors for the treatment of STING-related inflammatory diseases continues to encounter significant challenges. The activation of STING is a multi-step process that includes binding with cGAMP, self-oligomerization, and translocation from the endoplasmic reticulum to the Golgi apparatus, ultimately inducing the expression of IRF3 and NF-κB-mediated interferons and inflammatory cytokines. It has been demonstrated that disruption of any of these steps can effectively inhibit STING activation. Traditional structure-based drug screening methodologies generally focus on specific binding sites. In this study, a TransformerCPI model based on protein primary sequences and independent of binding sites is employed to identify compounds capable of binding to the STING protein. The natural product Licochalcone D (LicoD) is identified as a potent and selective STING inhibitor. LicoD does not bind to the classical ligand-binding pocket; instead, it covalently modifies the Cys148 residue of STING. This modification inhibits STING oligomerization, consequently suppressing the recruitment of TBK1 and the nuclear translocation of IRF3 and NF-κB. LicoD treatment ameliorates the inflammatory phenotype in Trex1-1- mice and inhibits the progression of DSS-induced colitis and AOM/DSS-induced colitis-associated colon cancer (CAC). In summary, this study reveals the potential of LicoD in treating STING-driven inflammatory diseases. It also demonstrates the utility of the TransformerCPI model in discovering allosteric compounds beyond the conventional binding pockets.© 2024. Science China Press.