Understanding protein folding, evolution and function via molecular simulation

该项目在过去一年中涉及以下领域： 1.高电荷质内无序蛋白质的复杂凝聚。最近在苏黎世与本·舒勒的单分子FRET小组合作的研究表明，高亲和力的蛋白质或蛋白质与相反电荷的核酸的无序复合体可能普遍存在于细胞核中。此外，我们现在发现，这些分子中的一些经历了复杂的凝聚。使用新的多尺度模拟方法，我们正在对两个核蛋白的复杂凝聚进行全原子模拟，以阐明负责稳定这些相的相互作用，我们还使用来自FRET实验和渗透压测量的新实验数据来帮助完善蛋白质中盐桥的力场以及蛋白质与离子的相互作用(M.Ivanovic)。(1) 2.发展更好的粗粒单链核酸模型，用于研究其相分离/复凝聚。我们已经成功地为dsDNA开发了一个粗粒度模型，用于模拟它在凝聚中的作用。我们现在将这一点扩展到单链核酸。为了发展更好的单链核酸模型，我们利用单分子FRET数据和小角X射线散射数据对力场进行了力平衡优化。我们目前正在扩展这个模型，以包括序列特定的效果，以及在多尺度方法中向后映射到原子模拟。(K·利博尔德) 3.发展可转移序列特定的蛋白质液-液分离(LLP)模型。我们使用了舒勒实验室在相同条件下收集的一组具有不同序列的蛋白质的FRET数据集，以进一步细化我们现有的潜力，导致显著改进。由于粗粒模型必然是实验条件的函数，我们正在努力考虑这种影响，特别是温度以及助溶剂或霍夫迈斯特效应。(T.Dannenhoffer-Lafage) 4.蛋白质共相分离的顺序依赖性。在细胞中，无膜细胞器不是简单地由单个大分子组成(或在复杂凝聚的情况下，由两个大分子组成)，而是可能涉及许多不同的分子。作为了解一种蛋白质与另一种蛋白质形成的凝聚体的相对亲和力的起点，我们正在与剑桥大学的Tuoma Knowles合作开发一种高通量序列扫描方法，我们将结合粗粒度模拟来研究这个问题(2)。(L.Good) 5.在粗粒度模型中包含二级结构。许多简单的粗粒模型(如用于相分离的单珠模型)以及更高分辨率的粗粒模型的一个共同缺点是能够基于序列而不是作为模拟的输入参数来形成二级结构。我们正在开发序列特定的模型来捕获粗粒度模型中的二级结构，这将使他们能够更好地描述无序蛋白质中的瞬时二级结构的形成，以及更广泛的二级结构的形成，如淀粉样蛋白(R.Best)。 6.使用基于序列的能量函数来描述蛋白质适应度图景，并用于蛋白质设计。我们已经证明，使用共同进化模型设计新的可折叠蛋白质序列是可能的。最近我们发现，通过这种途径，我们可以提高热稳定性(2)。我们也在寻求开发类似的想法，利用序列信息来识别自然切换折叠的蛋白质(如RfaH)。另外，我们正在探索使用机器学习来预测任何给定结构的蛋白质的适应情况；我们也在探索这种模型捕捉变构转变机制的能力(L.Frechette，D.Wang)。 7.使用粗粒度模型模拟细胞外基质的特性。我们最近开始开发自下而上的粗粒度模拟模型，以描述细胞外基质及其与其基本分子结构的关系。我们最初专注于开发准确的胶原原子模型，并根据核磁共振和小角X射线散射的现有数据进行验证；我们正在将其扩展到粗粒模型，这将允许研究原胶原在胶原纤维中的堆积。(G.Pantelopos)。 8.我们正在与Steve Vogel合作，了解某些荧光蛋白质的机制，这些机制允许通过从分子模拟中参数化的模型进行连贯的能量转移。(G.Taumoefolau) 每一节的末尾列出了参与每个项目的小组成员或共同监督的外部合作者。

The project has addressed the following areas in the past year: 1. Complex coacervation of highly charged intrinsically disordered proteins. Recent work in collaboration with Ben Schuler's single molecule FRET group in Zurich has shown that high affinity disordered complexes of proteins or proteins and nucleic acids of opposite charge may be ubiquitous in cell nuclei. In addition, we have now found that some of these molecules undergo complex coacervation. Using novel multiscale simulation methodology, we are performing all-atom simulations of a complex coacervate of two nuclear proteins in order to elucidate the interactions responsible for stabilizing these phases, and we are also using new experimental data from FRET experiments and osmotic pressure measurements to help refine the force fields for salt bridges in the proteins as well as interactions of the proteins with ions (M. Ivanovic). (1) 2. Development of better coarse-grained models single-stranded nucleic acids for studying their phase separation/complex coacervation. We have successfully developed a coarse grained model for dsDNA for modeling its role in coacervation. We are now extending this to single stranded nucleic acids. For the purpose of developing better single-stranded nucleic acid models, we are using single-molecule FRET data and small-angle X-ray scattering data to do a force-balance optimization of the force-field. We are currently extending this model to include sequence-specific effects as well as back-mapping to atomistic simulations in a multiscale approach. (K. Lebold) 3. Development of transferable sequence-specific models for liquid-liquid phase separation (LLPS) of intrinsically disordered proteins. We had used a FRET data set on a set of proteins with diverse sequences collected under identical conditions in the Schuler lab to further refine our existing potential, resulting in significant improvements. Because coarse-grained models are necessarily a function of the experimental conditions, we are working to include such effects, in particular temperature as well as cosolvent or Hofmeister effects. (T. Dannenhoffer-Lafage) 4. Sequence dependence of co-phase separation of proteins. In cells, membraneless organelles do not simply consist of a single macromolecular component (or two, in the case of complex coacervation), but likely involve many different molecules. As a starting point for understanding the relative affinity one protein for a coacervate formed by another, we are collaborating with Tuomas Knowles at the University of Cambridge to develop a high-throughput sequence-scanning methodology, which we will use in conjunction with coarse-grained simulations to study this problem (2). (L. Good) 5. Inclusion of secondary structure in coarse-grained models. A common deficiency of many simple coarse grained models (such as single-bead models used for phase separation) as well as higher resolution coarse-grained models is the ability to form secondary structure based on sequence rather than as an input parameter of the simulation. We are developing sequence-specific model to capture secondary structure in coarse-grained models that will allow them to better describe transient secondary structure formation in disordered proteins, as well as formation of more extended secondary structure such as amyloids (R. Best). 6. Using sequence-based energy functions to describe protein fitness landscapes and for protein design. We have shown that it is possible to design novel foldable protein sequences using coevolutionary models. Most recently we have found that we can achieve increased thermostability via this route (2). We are also looking to develop similar ideas to identify proteins which naturally switch folds (such as RfaH), using sequence information. Separately, we are exploring the use of machine learning to predict fitness landscapes for proteins of any given structure; we are also exploring the ability of such models to capture the mechanism of allosteric transitions (L. Frechette, D. Wang). 7. Modelling properties of the extracellular matrix using coarse-grained models. We have recently started developing bottom up coarse-grained simulation models to describe the extracellular matrix and how they are related to its underlying molecular structure. We have initially focused on developing accurate atomistic models for collagen, and validating them against the available data from NMR and small angle X-ray scattering; we are extending this to coarse-grained models that will allow the investigation of packing of tropocollagen in collagen fibers. (G. Pantelopulos). 8. We are working in collaboration with Steve Vogel to understand the mechanisms in certain fluorescent proteins that allow coherent energy transfer via models parameterized from molecular simulations. (G. Taumoefolau). Group members or jointly supervised external collaborators involved in each project are listed at the end of each section.