He Xin-Heng, Li Jun-Rui, Shen Shi-Yi, Xu H Eric
State Key Laboratory of Drug Research and CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China.
University of Chinese Academy of Sciences, Beijing, 100049, China.
Acta Pharmacol Sin. 2025 Apr;46(4):1111-1122. doi: 10.1038/s41401-024-01429-y. Epub 2024 Dec 6.
G protein-coupled receptors (GPCRs) are critical drug targets involved in numerous physiological processes, yet many of their structures remain unresolved due to inherent flexibility and diverse ligand interactions. This study systematically evaluates the accuracy of AlphaFold3-predicted GPCR structures compared to experimentally determined structures, with a primary focus on ligand-bound states. Our analysis reveals that while AlphaFold3 shows improved performance over AlphaFold2 in predicting overall GPCR backbone architecture, significant discrepancies persist in ligand-binding poses, particularly for ions, peptides, and proteins. Despite advancements, these limitations constrain the utility of AlphaFold3 models in functional studies and structure-based drug design, where high-resolution details of ligand interactions are crucial. We assess the accuracy of predicted structures across various ligand types, quantifying deviations in binding pocket geometries and ligand orientations. Our findings highlight specific challenges in the computational prediction of ligand-bound GPCR structures, emphasizing areas where further refinement is needed. This study provides valuable insights for researchers using AlphaFold3 in GPCR studies, underscores the ongoing necessity for experimental structure determination, and offers direction for improving protein-ligand interaction predictions in future computational models.
G蛋白偶联受体(GPCRs)是参与众多生理过程的关键药物靶点,但由于其固有的灵活性和多样的配体相互作用,许多GPCRs的结构仍未得到解析。本研究系统地评估了与实验测定结构相比,AlphaFold3预测的GPCR结构的准确性,主要关注配体结合状态。我们的分析表明,虽然AlphaFold3在预测GPCR整体骨架结构方面比AlphaFold2表现出更好的性能,但在配体结合姿势方面仍存在显著差异,特别是对于离子、肽和蛋白质。尽管取得了进展,但这些限制制约了AlphaFold3模型在功能研究和基于结构的药物设计中的应用,在这些研究中,配体相互作用的高分辨率细节至关重要。我们评估了各种配体类型预测结构的准确性,量化了结合口袋几何形状和配体取向的偏差。我们的研究结果突出了配体结合GPCR结构计算预测中的特定挑战,强调了需要进一步优化的领域。本研究为在GPCR研究中使用AlphaFold3的研究人员提供了有价值的见解,强调了实验结构测定的持续必要性,并为改进未来计算模型中的蛋白质-配体相互作用预测提供了方向。