Madaj Rafal, Martinez-Goikoetxea Mikel, Kaminski Kamil, Ludwiczak Jan, Dunin-Horkawicz Stanislaw
Institute of Evolutionary Biology, Faculty of Biology, Biological and Chemical Research Centre, University of Warsaw, Warsaw, Poland.
Department of Protein Evolution, Max Planck Institute for Biology Tübingen, Tübingen, Germany.
Protein Sci. 2025 Jan;34(1):e5244. doi: 10.1002/pro.5244.
Coiled coils are a common protein structural motif involved in cellular functions ranging from mediating protein-protein interactions to facilitating processes such as signal transduction or regulation of gene expression. They are formed by two or more alpha helices that wind around a central axis to form a buried hydrophobic core. Various forms of coiled-coil bundles have been reported, each characterized by the number, orientation, and degree of winding of the constituent helices. This variability is underpinned by short sequence repeats that form coiled coils and whose properties determine both their overall topology and the local geometry of the hydrophobic core. The strikingly repetitive sequence has enabled the development of accurate sequence-based coiled-coil prediction methods; however, the modeling of coiled-coil domains remains a challenging task. In this work, we evaluated the accuracy of AlphaFold2 in modeling coiled-coil domains, both in modeling local geometry and in predicting global topological properties. Furthermore, we show that the prediction of the oligomeric state of coiled-coil bundles can be achieved by using the internal representations of AlphaFold2, with a performance better than any previous state-of-the-art method (code available at https://github.com/labstructbioinf/dc2_oligo).
卷曲螺旋是一种常见的蛋白质结构基序,参与从介导蛋白质 - 蛋白质相互作用到促进信号转导或基因表达调控等细胞功能。它们由两个或更多的α螺旋围绕中心轴缠绕形成一个埋藏的疏水核心。已经报道了各种形式的卷曲螺旋束,每种都由组成螺旋的数量、方向和缠绕程度来表征。这种变异性由形成卷曲螺旋的短序列重复序列支撑,其性质决定了它们的整体拓扑结构和疏水核心的局部几何形状。这种显著的重复序列使得能够开发出基于序列的准确卷曲螺旋预测方法;然而,卷曲螺旋结构域的建模仍然是一项具有挑战性的任务。在这项工作中,我们评估了AlphaFold2在卷曲螺旋结构域建模方面的准确性,包括对局部几何形状的建模和对全局拓扑性质的预测。此外,我们表明,通过使用AlphaFold2的内部表示可以实现卷曲螺旋束寡聚状态的预测,其性能优于任何先前的最先进方法(代码可在https://github.com/labstructbioinf/dc2_oligo获取)。