Core D4: Computational Modeling

膜蛋白结构动力学联盟 (MPSD) 的所有努力都旨在获得膜蛋白功能的深入机制视角，将结构与动力学联系起来。计算预计将在这一过程中发挥基础性作用，因为每个桥接项目 (BP) 都包含一个计算组件，旨在 (1) 分析结果，(2) 帮助解释结构和动态数据，以及 (3) 构建模型/假设以进行预测，这些预测将在迭代过程中进行实验测试，该迭代过程利用了本次资助所支持的广泛的跨学科合作和资源。 出于这些原因，拟议的计算建模核心 D4（简称为 CMC）是联盟的核心统一组成部分，通过重叠团队和共同验证的方法在 BP 之间提供共享观点和相关机制解释。 膜蛋白可以被认为充当“分子机器”，需要改变形状并访问许多构象状态才能发挥其功能，主要是通过复杂的变构机制。为了了解膜蛋白如何执行此类功能，以及该功能如何被疾病（例如自然发生的突变）调节和/或改变，有必要详细了解所有膜蛋白 这些构象状态以及连接它们的反应途径。对膜蛋白及其生物功能的深刻机械理解将通过计算模型对结构、动力学和功能进行定量和准确预测的能力得到认可。 不可否认，复杂的计算已经成为膜蛋白生物分子研究的一个组成部分 [1, 2]。尽管如此，在本次拨款中与 BP 进行的合作研究指出，当前的方法将大大受益于跨多个尺度的更统一的方法，并且 来自计算和实验工作的紧密结合。如果所有研究人员（实验学家和理论家）都能更容易地使用计算方法，那么它们也会产生更大的影响。显然，需要额外的进步和改进来解决膜蛋白系统提出的挑战性问题。关于计算在生物分子系统研究中的作用的明智的长期战略必须确保投入精力以满足传播和影响的需求以及新方法的持续发展。这一观点被纳入 CMC 的总体目标中，即提供和开发研究复杂膜蛋白系统功能机制所需的最先进的方法和“工具”。

All the efforts within the Membrane Protein Structural Dynamics Consortium (MPSD) are aimed at gaining a deep mechanistic perspective on membrane protein function, linking structure to dynamics. Computation is expected to play a fundamental role in this process, as every Bridging Project (BP) comprises a computational component aiming to (1) analyze results, (2) help interpret structural and dynamical data, and (3) construct models/hypotheses to make predictions that will be tested experimentally in an iterative process that takes advantage of the wide range of interdisciplinary collaborations and resources enabled by this grant. For these reasons, the proposed Computational Modeling Core D4, referred to as CMC, is a central unifying component of the Consortium offering shared perspectives and correlated mechanistic interpretations among the BPs by virtue of ovedapping teams and common validated approaches. Membrane proteins can be considered to function as "molecular machines" that need to change shape and visit many conformational states to perform their function, mostly through complex allosteric mechanisms. To understand how membrane proteins perform such functions, and how this function is regulated and/or modified by disease (e.g., naturally occurring mutations), it is necessary to have detailed knowledge about all those conformational states as well as the reaction pathway connecting them. A profound mechanistic understanding of membrane proteins and their biological function will be recognized by one's ability to make quantitative and accurate predictions of structure, dynamics and function from computational models. Undeniably, sophisticated computations are already an integral part of biomolecular research on membrane proteins [1, 2]. Nonetheless, the collaborative research undertaken with the BPs in this Grant points out that current methodologies would significantly benefit from a more unified approach across multiple scales, and from a close integration of computational and experimental efforts. The computational approaches would also have a greater impact if they became more routinely accessible to all investigators (experimentalists and theoreticians alike). Clearty, additional advances and improvements are needed to address the challenging problems presented by membrane protein systems. A judicious long-term strategy about the role of computation in the investigation of biomolecular systems must ensure that efforts are invested to respond to both the need for dissemination and impact, and the continued development of novel methodologies. This view is incorporated in the overall goal of the CMC to provide and develop state-of-the-art methods and "tools" required for studying the mechanisms of function of complex membrane protein systems.