目前,G蛋白偶联受体(GPCRs)构成代表超过30%的治疗靶标的膜结合受体的重要组。氟通常用于设计高活性生物化合物,食品和药物管理局(FDA)稳步增加的药物数量证明了这一点。在这里,我们在ChEMBL数据库-FiSAR组鉴定并分析了898个基于靶标的含F异构模拟组,用于SAR分析,这些模拟组对33种不同的胺能GPCRs具有活性,包括总共2163种氟化(1201种独特)化合物.我们发现30个FiSAR集包含活动悬崖(AC),定义为结构相似的化合物对,显示出亲和力的显着差异(≥50倍变化),其中氟位置的变化可能导致效力的1300倍变化。对匹配分子对(MMP)网络的分析表明,芳环的氟化对亲和力没有明显的正面或负面影响。此外,我们提出了一个计算机工作流程(包括诱导对接,分子动力学,量子极化配体对接,和基于广义玻恩表面积(GBSA)模型的结合自由能计算),以对分子中的氟位置进行评分。
Currently, G protein-coupled receptors (GPCRs) constitute a significant group of membrane-bound receptors representing more than 30% of therapeutic targets.
Fluorine is commonly used in designing highly active biological compounds, as evidenced by the steadily increasing number of drugs by the Food and Drug Administration (FDA). Herein, we identified and analyzed 898 target-based F-containing isomeric analog sets for SAR analysis in the ChEMBL database-FiSAR sets active against 33 different aminergic GPCRs comprising a total of 2163 fluorinated (1201 unique) compounds. We found 30 FiSAR sets contain activity cliffs (ACs), defined as pairs of structurally similar compounds showing significant differences in affinity (≥50-fold change), where the change of
fluorine position may lead up to a 1300-fold change in potency. The analysis of matched molecular pair (MMP) networks indicated that the fluorination of aromatic rings showed no clear trend toward a positive or negative effect on affinity. Additionally, we propose an in silico workflow (including induced-fit docking, molecular dynamics, quantum polarized ligand docking, and binding free energy calculations based on the Generalized-Born Surface-Area (GBSA) model) to score the
fluorine positions in the molecule.