Structural Bioinformatics Unit, Department of Structural Biology and Chemistry, Institut Pasteur, CNRS UMR3528, C3BI, USR3756 Paris, France; Faculty of Health and Life Sciences, University Pompeu Fabra, Carrer del Doctor Aiguader 80, Barcelona 08003, Spain.
Structural Bioinformatics Unit, Department of Structural Biology and Chemistry, Institut Pasteur, CNRS UMR3528, C3BI, USR3756 Paris, France.
Structure. 2020 Jan 7;28(1):75-82.e4. doi: 10.1016/j.str.2019.10.018. Epub 2019 Nov 18.
Chemical crosslinking, combined with mass spectrometry analysis, is a key source of information for characterizing the structure of large protein assemblies, in the context of molecular modeling. In most approaches, the interpretation is limited to simple spatial restraints, neglecting physico-chemical interactions between the crosslinker and the protein and their flexibility. Here we present a method, named NRGXL (new realistic grid for crosslinks), which models the flexibility of the crosslinker and the linked side-chains, by explicitly sampling many conformations. Also, the method can efficiently deal with overall protein dynamics. This method creates a physical model of the crosslinker and associated energy. A classifier based on it outperforms others, based on Euclidean distance or solvent-accessible distance and its efficiency makes it usable for validating 3D models from crosslinking data. NRGXL is freely available as a web server at: https://nrgxl.pasteur.fr.
化学交联结合质谱分析是分子建模中用于描述大型蛋白质组装结构的重要信息来源。在大多数方法中，解释仅限于简单的空间约束，忽略了交联剂与蛋白质之间的物理化学相互作用及其灵活性。在这里，我们提出了一种名为 NRGXL（新的交联网格）的方法，该方法通过显式采样许多构象来模拟交联剂和连接侧链的灵活性。此外，该方法还可以有效地处理整体蛋白质动力学。该方法创建了交联剂及其相关能量的物理模型。基于它的分类器优于基于欧几里得距离或溶剂可及距离的其他分类器，其效率使其可用于验证交联数据的 3D 模型。NRGXL 可作为一个网络服务器在以下网址免费获取：https://nrgxl.pasteur.fr。
