AlphaFold3与实验结构:评估配体结合G蛋白偶联受体的准确性。

IF 6.9 1区 医学 Q1 CHEMISTRY, MULTIDISCIPLINARY Acta Pharmacologica Sinica Pub Date : 2024-12-06 DOI:10.1038/s41401-024-01429-y
Xin-Heng He, Jun-Rui Li, Shi-Yi Shen, H Eric Xu
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引用次数: 0

摘要

G蛋白偶联受体(gpcr)是参与许多生理过程的关键药物靶点,但由于其固有的灵活性和多种配体相互作用,其许多结构仍未解决。本研究系统地评估了与实验确定的结构相比,alphafold3预测的GPCR结构的准确性,主要关注配体结合态。我们的分析表明,虽然AlphaFold3在预测GPCR主链结构方面比AlphaFold2表现更好,但在配体结合姿势方面仍然存在显著差异,特别是对于离子、肽和蛋白质。尽管取得了进步,但这些局限性限制了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,量化了结合袋几何形状和配体方向的偏差。我们的研究结果强调了在配体结合GPCR结构的计算预测方面的具体挑战,强调了需要进一步改进的领域。本研究为研究人员在GPCR研究中使用AlphaFold3提供了有价值的见解,强调了实验结构确定的持续必要性,并为未来计算模型中改进蛋白质-配体相互作用预测提供了方向。
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AlphaFold3 versus experimental structures: assessment of the accuracy in ligand-bound G protein-coupled receptors.

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.

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来源期刊
Acta Pharmacologica Sinica
Acta Pharmacologica Sinica 医学-化学综合
CiteScore
15.10
自引率
2.40%
发文量
4365
审稿时长
2 months
期刊介绍: APS (Acta Pharmacologica Sinica) welcomes submissions from diverse areas of pharmacology and the life sciences. While we encourage contributions across a broad spectrum, topics of particular interest include, but are not limited to: anticancer pharmacology, cardiovascular and pulmonary pharmacology, clinical pharmacology, drug discovery, gastrointestinal and hepatic pharmacology, genitourinary, renal, and endocrine pharmacology, immunopharmacology and inflammation, molecular and cellular pharmacology, neuropharmacology, pharmaceutics, and pharmacokinetics. Join us in sharing your research and insights in pharmacology and the life sciences.
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