Peck Yoshimi, Wilson David, Lennox-Bulow Danica, Giribaldi Julien, Seymour Jamie, Dutertre Sebastien, Rosengren K, Liddell Michael, Daly Norelle
Australian Institute of Tropical Health and Medicine, James Cook University, Cairns, QLD, Australia.
IBMM, University of Montpellier, CNRS, ENSCM, Montpellier, France.
Biochem J. 2025 Apr 23;482(11):639-53. doi: 10.1042/BCJ20240753.
The activity of the serotonin type 3 (5-HT3) receptor is associated with neurodegenerative, inflammatory and metabolic diseases, neuropsychiatric disorders, and cancer. Structural analysis of modulators of this receptor is likely to aid in future medicinal chemistry studies aimed at developing lead molecules targeting this receptor. Here we report the structure of a cone snail venom peptide that was purified from the crude venom of Conus geographus and shown to be an antagonist of the 5-HT3 receptor more than 25 years ago, sigma(σ)GVIIIA. This lag in structural characterisation studies is likely due to challenges in isolating the native peptide and difficulties in producing synthetic peptide due to the presence of ten cysteine residues involved in five disulfide bonds. Using NMR spectroscopy, we show that σS-GVIIIA adopts a growth factor cystine knot (GFCK) fold. This is the first example of a cone snail venom peptide experimentally determined to contain the GFCK structural motif, and the first example of a 5-HT3 receptor antagonist containing this motif. Our study also highlights complexities in the use of artificial intelligence-based structure prediction models. Peptide structure predictions using AlphaFold 3 were consistent with our NMR structure when the input sequence contained the well-conserved precursor sequence, but inconsistent when the precursor sequence was excluded. AI-based structure prediction of proteins is a rapidly advancing field, but this inconsistency emphasises the need for more experimental structural training data when novel structures are involved, as was the case here for a cysteine-rich peptide.
5-羟色胺3型(5-HT3)受体的活性与神经退行性疾病、炎症和代谢性疾病、神经精神障碍及癌症相关。对该受体调节剂进行结构分析可能有助于未来的药物化学研究,旨在开发针对该受体的先导分子。在此,我们报告一种芋螺毒液肽的结构,该肽是从地纹芋螺的粗毒液中纯化得到的,25多年前就已证明它是5-HT3受体的拮抗剂,即σ(σ)GVIIIA。结构表征研究的滞后可能是由于分离天然肽存在挑战,以及由于存在五个二硫键所涉及的十个半胱氨酸残基而难以合成肽。利用核磁共振光谱,我们表明σS-GVIIIA具有生长因子胱氨酸结(GFCK)折叠结构。这是首个通过实验确定含有GFCK结构基序的芋螺毒液肽实例,也是首个含有该基序的5-HT3受体拮抗剂实例。我们的研究还凸显了基于人工智能的结构预测模型使用中的复杂性。当输入序列包含保守的前体序列时,使用AlphaFold 3进行的肽结构预测与我们的核磁共振结构一致,但排除前体序列时则不一致。基于人工智能的蛋白质结构预测是一个快速发展的领域,但这种不一致强调了在涉及新结构时需要更多实验性结构训练数据,就像这里富含半胱氨酸的肽的情况一样。