Neuroscience Graduate Program, Sackler Institute of Graduate Biomedical Sciences, New York University School of Medicine, New York, NY 10016.
Department of Neuroscience, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104.
Proc Natl Acad Sci U S A. 2017 Sep 19;114(38):E8100-E8109. doi: 10.1073/pnas.1703952114. Epub 2017 Sep 5.
Venom peptide toxins such as conotoxins play a critical role in the characterization of nicotinic acetylcholine receptor (nAChR) structure and function and have potential as nervous system therapeutics as well. However, the lack of solved structures of conotoxins bound to nAChRs and the large size of these peptides are barriers to their computational docking and design. We addressed these challenges in the context of the α4β2 nAChR, a widespread ligand-gated ion channel in the brain and a target for nicotine addiction therapy, and the 19-residue conotoxin α-GID that antagonizes it. We developed a docking algorithm, ToxDock, which used ensemble-docking and extensive conformational sampling to dock α-GID and its analogs to an α4β2 nAChR homology model. Experimental testing demonstrated that a virtual screen with ToxDock correctly identified three bioactive α-GID mutants (α-GID[A10V], α-GID[V13I], and α-GID[V13Y]) and one inactive variant (α-GID[A10Q]). Two mutants, α-GID[A10V] and α-GID[V13Y], had substantially reduced potency at the human α7 nAChR relative to α-GID, a desirable feature for α-GID analogs. The general usefulness of the docking algorithm was highlighted by redocking of peptide toxins to two ion channels and a binding protein in which the peptide toxins successfully reverted back to near-native crystallographic poses after being perturbed. Our results demonstrate that ToxDock can overcome two fundamental challenges of docking large toxin peptides to ion channel homology models, as exemplified by the α-GID:α4β2 nAChR complex, and is extendable to other toxin peptides and ion channels. ToxDock is freely available at rosie.rosettacommons.org/tox_dock.
毒液肽毒素，如 conotoxin，在鉴定烟碱型乙酰胆碱受体（nAChR）结构和功能方面发挥着关键作用，并且具有作为神经系统治疗药物的潜力。然而，与 nAChR 结合的 conotoxin 结构尚未得到解决，并且这些肽的尺寸较大，这是它们进行计算对接和设计的障碍。我们在广泛存在于大脑中的配体门控离子通道 α4β2 nAChR 以及拮抗它的 19 个残基 conotoxin α-GID 的背景下解决了这些挑战。我们开发了一种对接算法 ToxDock，该算法使用了集合对接和广泛的构象采样，将 α-GID 及其类似物对接至 α4β2 nAChR 同源模型。实验测试表明，使用 ToxDock 的虚拟筛选正确鉴定了三种具有生物活性的 α-GID 突变体（α-GID[A10V]、α-GID[V13I]和 α-GID[V13Y]）和一种无活性变体（α-GID[A10Q]）。与 α-GID 相比，两种突变体 α-GID[A10V]和 α-GID[V13Y]在人 α7 nAChR 上的效力大大降低，这是 α-GID 类似物的理想特征。该对接算法的通用性通过将肽毒素重新对接至两个离子通道和一个结合蛋白得到了强调，在这些通道和蛋白中，肽毒素在受到干扰后成功恢复到接近天然晶体的构象。我们的结果表明，ToxDock 可以克服将大型毒素肽对接至离子通道同源模型的两个基本挑战，如 α-GID:α4β2 nAChR 复合物所示，并且可扩展至其他毒素肽和离子通道。ToxDock 可在 rosie.rosettacommons.org/tox_dock 免费获取。
