Symbolic Sound Corporation, Champaign, IL 61820.
Department of Chemistry, University of Illinois Urbana-Champaign, Urbana, IL 61801.
Proc Natl Acad Sci U S A. 2024 May 28;121(22):e2319094121. doi: 10.1073/pnas.2319094121. Epub 2024 May 20.
Protein-protein and protein-water hydrogen bonding interactions play essential roles in the way a protein passes through the transition state during folding or unfolding, but the large number of these interactions in molecular dynamics (MD) simulations makes them difficult to analyze. Here, we introduce a state space representation and associated "rarity" measure to identify and quantify transition state passage (transit) events. Applying this representation to a long MD simulation trajectory that captured multiple folding and unfolding events of the GTT WW domain, a small protein often used as a model for the folding process, we identified three transition categories: Highway (faster), Meander (slower), and Ambiguous (intermediate). We developed data sonification and visualization tools to analyze hydrogen bond dynamics before, during, and after these transition events. By means of these tools, we were able to identify characteristic hydrogen bonding patterns associated with "Highway" versus "Meander" versus "Ambiguous" transitions and to design algorithms that can identify these same folding pathways and critical protein-water interactions directly from the data. Highly cooperative hydrogen bonding can either slow down or speed up transit. Furthermore, an analysis of protein-water hydrogen bond dynamics at the surface of WW domain shows an increase in hydrogen bond lifetime from folded to unfolded conformations with Ambiguous transitions as an outlier. In summary, hydrogen bond dynamics provide a direct window into the heterogeneity of transits, which can vary widely in duration (by a factor of 10) due to a complex energy landscape.
蛋白质-蛋白质和蛋白质-水氢键相互作用在蛋白质折叠或展开过程中穿越过渡态的方式中起着至关重要的作用，但在分子动力学 (MD) 模拟中，这些相互作用的数量众多，使得它们难以分析。在这里，我们引入了一种状态空间表示法和相关的“稀有度”度量方法，以识别和量化过渡态通过（过境）事件。将这种表示法应用于一个长的 MD 模拟轨迹，该轨迹捕获了 GTT WW 结构域的多次折叠和展开事件，该小蛋白通常用作折叠过程的模型，我们确定了三种过渡类别：高速公路（更快）、蜿蜒（更慢）和模糊（中间）。我们开发了数据声音化和可视化工具，以分析过渡事件前后的氢键动力学。通过这些工具，我们能够识别与“高速公路”与“蜿蜒”与“模糊”过渡相关的特征氢键模式，并设计可以直接从数据中识别这些相同折叠途径和关键蛋白质-水相互作用的算法。高度协同的氢键既可以减慢也可以加快过境。此外，对 WW 结构域表面蛋白质-水氢键动力学的分析表明，随着过渡状态的模糊性增加，从折叠构象到展开构象的氢键寿命增加，这是一个异常值。总之，氢键动力学为过境的异质性提供了一个直接的窗口，由于复杂的能量景观，过境的持续时间（相差 10 倍）可能有很大差异。
