Ser Zheng
Institute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A*STAR), Singapore 138673, Singapore.
QRB Discov. 2024 Dec 27;6:e6. doi: 10.1017/qrd.2024.13. eCollection 2025.
High resolution structures of protein complexes provide a wealth of information on protein structure and function. Databases of these protein structures are also used for artificial-intelligence (AI)-based methods of structural modelling. Despite the wealth of protein structures that have been determined by structural biologists, there are still gaps, or missing pieces in the puzzle of protein structural biology. Highly flexible regions may be missing from protein structures and conformational changes of different protein complex states may not be captured by current databases. In this perspective, I sketch out several ways that cross-linking mass spectrometry can contribute to filling in some of these missing pieces: Identification of cross-linked interactions in highly flexible protein regions not captured by other structural techniques; capturing conformational changes of protein complexes in different functional states; serving as distance constraints in integrative structural modelling and providing structural information of proteins. The myriad ways in which cross-linking mass spectrometry contributes to filling in missing pieces in structural biology makes it a powerful technique in structural biology.
蛋白质复合物的高分辨率结构提供了关于蛋白质结构和功能的丰富信息。这些蛋白质结构数据库也被用于基于人工智能（AI）的结构建模方法。尽管结构生物学家已经确定了大量的蛋白质结构，但在蛋白质结构生物学的拼图中仍然存在空白或缺失部分。蛋白质结构中可能缺少高度灵活的区域，并且当前数据库可能无法捕捉到不同蛋白质复合物状态的构象变化。从这个角度来看，我概述了交联质谱法可以帮助填补其中一些缺失部分的几种方式：识别其他结构技术未捕捉到的高度灵活蛋白质区域中的交联相互作用；捕捉处于不同功能状态的蛋白质复合物的构象变化；在整合结构建模中作为距离约束并提供蛋白质的结构信息。交联质谱法在填补结构生物学缺失部分方面的众多方式使其成为结构生物学中的一项强大技术。
