Raffaelli Tiziano, Wilson David T, Dutertre Sebastien, Giribaldi Julien, Vetter Irina, Robinson Samuel D, Thapa Ashvriya, Widi Antin, Loukas Alex, Daly Norelle L
Australian Institute of Tropical Health and Medicine, James Cook University, Cairns, Australia.
IBMM, Univ Montpellier, CNRS, ENSCM, Montpellier, France.
J Biol Chem. 2024 Apr;300(4):107203. doi: 10.1016/j.jbc.2024.107203. Epub 2024 Mar 18.
We are entering an exciting time in structural biology where artificial intelligence can be used to predict protein structures with greater accuracy than ever before. Extending this level of accuracy to the predictions of disulfide-rich peptide structures is likely to be more challenging, at least in the short term, given the tight packing of cysteine residues and the numerous ways that the disulfide bonds can potentially be linked. It has been previously shown in many cases that several disulfide bond connectivities can be accommodated by a single set of NMR-derived structural data without significant violations. Disulfide-rich peptides are prevalent throughout nature, and arguably the most well-known are those present in venoms from organisms such as cone snails. Here, we have determined the first three-dimensional structure and disulfide connectivity of a U-superfamily cone snail venom peptide, TxVIIB. TxVIIB has a VI/VII cysteine framework that is generally associated with an inhibitor cystine knot (ICK) fold; however, AlphaFold predicted that the peptide adopts a mini-granulin fold with a granulin disulfide connectivity. Our experimental studies using NMR spectroscopy and orthogonal protection of cysteine residues indicate that TxVIIB indeed adopts a mini-granulin fold but with the ICK disulfide connectivity. Our findings provide structural insight into the underlying features that govern formation of the mini-granulin fold rather than the ICK fold and will provide fundamental information for prediction algorithms, as the subtle complexity of disulfide isomers may be not adequately addressed by the current prediction algorithms.
我们正步入结构生物学的一个激动人心的时代,在这个时代,人工智能可用于以前所未有的更高精度预测蛋白质结构。鉴于半胱氨酸残基的紧密堆积以及二硫键可能的连接方式众多,将这种精度水平扩展到富含二硫键的肽结构预测可能更具挑战性,至少在短期内如此。此前在许多情况下已表明,一组源自核磁共振(NMR)的结构数据可以容纳几种二硫键连接方式而不会有明显冲突。富含二硫键的肽在自然界中普遍存在,可以说最广为人知的是那些存在于诸如芋螺等生物毒液中的肽。在此,我们确定了一种U超家族芋螺毒液肽TxVIIB的首个三维结构和二硫键连接方式。TxVIIB具有VI/VII半胱氨酸框架,通常与抑制性胱氨酸结(ICK)折叠相关;然而,AlphaFold预测该肽采用具有颗粒蛋白二硫键连接方式的小颗粒蛋白折叠。我们使用核磁共振光谱和半胱氨酸残基的正交保护进行的实验研究表明,TxVIIB确实采用小颗粒蛋白折叠,但具有ICK二硫键连接方式。我们的研究结果为控制小颗粒蛋白折叠而非ICK折叠形成的潜在特征提供了结构上的见解,并将为预测算法提供基础信息,因为当前的预测算法可能无法充分解决二硫键异构体的细微复杂性。