Abstract：
Contemporary research has convincingly demonstrated that upregulation of G protein-coupled receptor 183 (GPR183), orchestrated by its endogenous agonist, 7α,25-dihydroxyxcholesterol (7α,25-OHC), leads to the development of cancer, diabetes, multiple sclerosis, infectious, and inflammatory diseases. A recent study unveiled the cryo-EM structure of 7α,25-OHC bound GPR183 complex, presenting an untapped opportunity for computational exploration of potential GPR183 inhibitors, which served as our inspiration for the current work. A predictive and validated two-dimensional QSAR model using genetic algorithm (GA) and multiple linear regression (MLR) on experimental GPR183 inhibition data was developed. QSAR study highlighted that structural features like dissimilar electronegative atoms, quaternary carbon atoms, and CH2RX fragment (X: heteroatoms) influence positively, while the existence of oxygen atoms with a topological separation of 3, negatively affects GPR183 inhibitory activity. Post assessment of true external set prediction capability, the MLR model was deployed to screen 12,449 DrugBank compounds, followed by a screening pipeline involving molecular docking, druglikeness, ADMET, protein-ligand stability assessment using deep learning algorithm, molecular dynamics, and molecular mechanics. The current findings strongly evidenced DB05790 as a potential lead for prospective interference of oxysterol-mediated GPR183 overexpression, warranting further in vitro and in vivo validation.
摘要：
当代研究令人信服地表明，G蛋白偶联受体183（GPR183）的上调，由其内源性激动剂精心策划，7α,25-二羟基胆固醇（7α，25-OHC），导致癌症的发展，糖尿病,多发性硬化症,传染性,和炎症性疾病。最近的一项研究揭示了7α的低温EM结构，25-OHC结合的GPR183复合物，为潜在的GPR183抑制剂的计算探索提供了尚未开发的机会，这是我们当前工作的灵感来源。在实验GPR183抑制数据上，使用遗传算法（GA）和多元线性回归（MLR）开发了预测和验证的二维QSAR模型。QSAR研究强调了不同电负性原子等结构特征，季碳原子,和CH2RX片段（X：杂原子）积极影响，而氧原子的存在具有3个拓扑分离，对GPR183抑制活性产生负面影响。真实外部集预测能力的后评估，MLR模型被用来筛选12,449种药库化合物，随后是涉及分子对接的筛选管道，像毒品一样，ADMET,使用深度学习算法进行蛋白质-配体稳定性评估，分子动力学,和分子力学。目前的发现有力地证明了DB05790是氧固醇介导的GPR183过表达的潜在干扰，保证进一步的体外和体内验证。
