Dynamical-nonequilibrium simulations: an emerging approach to study time-dependent structural changes in proteins

蛋白质在生理条件下既不是静态的，也不是孤立工作的。事实上，恰恰相反；蛋白质不断地在不同的构象之间移动和转换。此外，环境的变化可以改变它们众多构象之间的平衡。例如，pH值的变化以及离子或小分子与蛋白质的结合可以促进特定的结构变化，并最终决定蛋白质的宏观行为。这种通过在构象之间波动来响应外部变化的能力是一种迷人的特征，对蛋白质的功能和调节至关重要。对蛋白质构象重排的详细描述对于理解其工作机制和功能至关重要。即使有可能通过实验确定蛋白质中原子的位置（例如使用低温电子显微镜或x射线晶体学），在某些情况下，对蛋白质进行改变的影响（例如突变或配体和离子的结合）并不明显。替代实验方法的另一种方法是应用计算机模拟。我一直站在开发和使用计算方法来绘制蛋白质结构变化的前沿。特别是在这个项目中，结合不同条件下的计算机模拟（例如在配体存在和不存在的情况下）的方法是关键。这种方法允许对响应外部扰动（例如配体解结合）的蛋白质结构变化的时间演变进行详细的绘图。这项由布里斯托尔大学（University of Bristol）承担的拟议研究将开发并应用新的计算方法来改变蛋白质构象变化的研究。在本奖学金的时间框架内，将研究三种基本不同的生物分子系统，从可溶性酶（β -内酰胺酶）到膜通道（囊性纤维化跨膜传导调节剂（CFTR）通道）和受体（烟碱乙酰胆碱受体）。所研究的系统的多样性完美地突出了所使用的计算方法的灵活性和一般适用性。β -内酰胺酶是能够水解抗生素（如青霉素）的细菌酶，是对这些药物产生耐药性的重要原因。位于细胞表面的CFTR通道运输氯化物和碳酸氢盐，其功能障碍导致囊性纤维化。尼古丁乙酰胆碱受体是广泛分布于神经系统的离子通道，与许多疾病和病症有关，包括尼古丁和酒精成瘾。在这项工作中，我将绘制连接每个蛋白质中功能重要区域的通信网络，并了解小分子和突变如何影响这些网络。我的计算发现将解开我的合作者将通过实验探索的相互作用的多样性，即斯宾塞教授（布里斯托尔大学）、谢泼德教授（布里斯托尔大学）、贝穆德斯教授（牛津布鲁克斯大学）、西因教授（梅奥诊所）和加拉格尔教授（布里斯托尔大学）。他们的实验结果将输入到我的计算模型中，帮助改进和增强它们。这是一个高度协作的多学科项目，结合了计算（与Oracle合作）和实验专业知识，为扩展所有三个系统工作机制的基础知识提供了独特的机会。从长远来看，这些知识将预测新出现的β -内酰胺酶突变体的特性，这些突变体会导致抗菌素耐药性，并为新疗法的设计提供信息（例如治疗囊性纤维化的药物、治疗慢性疼痛的非阿片类药物、抗成瘾药物和对抗抗生素耐药性的β -内酰胺酶抑制剂）。

Proteins are neither static nor work in isolation in physiological conditions. In fact, it is the opposite; proteins are continuously moving and switching between different conformations. Moreover, changes in the environment can shift the balance between their multitude of conformations. For example, changes in pH and the binding of ions or small molecules to a protein can promote specific structural changes and ultimately determine the protein's macroscopic behaviour. This ability to respond to external changes by fluctuating between conformations is a fascinating feature and is crucial for protein's function and regulation. A detailed description of a protein's conformational rearrangements is essential to understand its working mechanism and function. Even though it is possible to experimentally determine the positions of the atoms in a protein (e.g. using cryogenic electron microscopy or X-ray crystallography), in some cases, the effects of making changes to the protein (e.g. mutations or the binding of ligands and ions) are not obvious. An alternative to experimental approaches is the application of computer simulations. I have been at the forefront of developing and employing computational methods to map structural changes in proteins. For this project, in particular, the approach of combining computer simulations in different conditions (e.g. in the presence and absence of a ligand) is the keystone. This approach permits for a detailed mapping of the time evolution of the structural changes in a protein in response to an external perturbation (e.g. ligand unbinding). The proposed research, undertaken at the University of Bristol, will develop and apply new computational approaches to transform the study of conformational changes in proteins. Three fundamentally different biomolecular systems will be studied during the timeframe of this Fellowship, ranging from soluble enzymes (beta-lactamases) to membrane channels (cystic fibrosis transmembrane conductance regulator (CFTR) channel) and receptors (nicotinic acetylcholine receptors). The diversity of the systems under investigation perfectly highlights the flexibility and general applicability of the computational approaches to be used. Beta-lactamases are bacterial enzymes capable of hydrolysing antibiotics (e.g. penicillin) and are an important cause of resistance to these drugs. The CFTR channel, which sits on the surface of cells, transports chloride and bicarbonate, and its malfunction causes cystic fibrosis. Nicotinic acetylcholine receptors are ion channels widely distributed in the nervous system and are associated with many diseases and conditions, including nicotine and alcohol addiction. In this work, I will map the communication networks connecting functionally important regions within each protein and understand how small molecules and mutations impact those networks. My computational findings will unlock a diversity of interactions that will be explored experimentally by my collaborators, namely Profs Spencer (University of Bristol), Sheppard (University of Bristol), Bermudez (Oxford Brookes University), Sine (Mayo Clinic) and Gallagher (University of Bristol). Their experimental results will feed into my computational models, helping to refine and enhance them. This is a highly collaborative, multidisciplinary project that combines computational (in partnership with Oracle) and experimental expertise, which provides a unique opportunity to expand fundamental knowledge of all three systems' working mechanisms. In the longer term, this knowledge will foretell the properties of newly emerged beta-lactamases mutants, which cause antimicrobial resistance, and inform the design of new therapeutics (e.g. drugs to treat cystic fibrosis, non-opioid drugs for chronic pain, anti-addiction agents and beta-lactamases inhibitors to fight antibiotic resistance).