用计算机折叠蛋白质:我们走了多远?(英文)

蛋白质折叠是现代科学最具挑战性的难题之一。Anfinsen的先驱性工作已经过去数十年了,我们对蛋白质折叠的机理仍不甚了然。但值得庆幸的是,科学工作者们在解析几个模型蛋白质的折叠机理上已经取得了明显的进展。这篇综述将主要回顾在蛋白质折叠的计算研究方面的进展。受益于计算机技术的迅猛发展,在1998年首次实现了一个微秒的全原子水平的蛋白质折叠,从2000年开始,folding@home将全球分布式计算技术应用于蛋白质折叠。在经历了数十年艰苦的努力之后,天然蛋白质亚埃精度的折叠终于在2007年成功实现。近年来,一种全新的概念开始出现,人们越来越多地用网络来解释蛋白质折叠的机理。随着分子力场的不断完善,分子模拟将会在解析蛋白质折叠的机理上起到越来越重要的作用。     

蛋白质跨膜运送研究的新进展

本文对(1)分泌蛋白质、线粒体蛋白质跨膜运送的新进展,(2)蛋白质跨膜运送过程中的解折叠、重折叠与分子伴侣以及(3)蛋白质跨膜运送的机理研究概况作了扼要的介绍。     

从量子跃迁观点对蛋白质折叠速率的统计分析

理解蛋白质折叠速率是探明蛋白质结构和折叠机制物理基础的关键.蛋白质折叠速率的温度依赖关系是当前一个未解决的难题.假定蛋白质折叠是一个分子构象间的量子跃迁,导出了一个蛋白质折叠速率的解析公式.由此公式出发,计算了资料库中二态蛋白质的折叠速率和研究了它们的温度依赖性.从第一性原理出发,对实验给出的16个二态蛋白质折叠速率的非阿列尼乌斯(non-Arrhenius)温度关系给予成功解释,进而预测了这些蛋白质解折叠速率的温度依赖关系.依据量子折叠理论,给出了一个预测二态蛋白质折叠速率的统计公式,用于65个蛋白的资料库,理论和实验比较的相关系数为0.73.此外,理论还给出了与实验结果一致的最大和最小折叠速率估计.     

封面故事

蛋白质折叠是蛋白质从一级结构向三级结构转变的物理过程。蛋白质的正确折叠对其行使正常的生理功能至关重要,错误折叠可以导致疾病的发生。研究蛋白质折叠机理存在诸     

毛细管电泳及其在蛋白质折叠研究中的应用

简要介绍了毛细管电泳的常用分离模式及其原理,并对毛细管电泳在蛋白质化学领域中的新应用——研究蛋白质折叠和发展前景作了评述。     

蛋白质折叠类型分类方法及分类数据库

蛋白质折叠规律研究是生命科学重大前沿课题,折叠分类是蛋白质折叠研究的基础。目前的蛋白质折叠类型分类基本上靠专家完成,不同的库分类并不相同,迫切需要一个建立在统一原理基础上的蛋白质折叠类型数据库。本文以ASTRAL-1.65数据库中序列同源性在25%以下、分辨率小于2.5的蛋白为基础,通过对蛋白质空间结构的观察及折叠类型特征的分析,提出以蛋白质折叠核心为中心、以蛋白质结构拓扑不变性为原则、以蛋白质折叠核心的规则结构片段组成、连接和空间排布为依据的蛋白质折叠类型分类方法,建立了低相似度蛋白质折叠分类数据库——LIFCA,包含259种蛋白质折叠类型。数据库的建立,将为进一步的蛋白质折叠建模及数据挖掘、蛋白质折叠识别、蛋白质折叠结构进化研究奠定基础。     

基于HP模型的蛋白质折叠问题的研究

基于蛋白质二维HP模型提出改进的遗传算法对真实蛋白质进行计算机折叠模拟。结果显示疏水能量函数最小值的蛋白质构象对应含疏水核心的稳定结构,疏水作用在蛋白质折叠中起主要作用。研究表明二维HP模型在蛋白质折叠研究中是可行的和有效的并为进一步揭示蛋白质折叠机理提供重要参考信息。     

模拟蛋白质折叠过程的新算法研究

蛋白质折叠过程模拟是当前蛋白质研究领域的一个难点问题。针对这一问题,提出了一个描述蛋白质折叠过程的算法-拟蛇算法,并且从分子振荡和分子动力学理论两个方面来证明该算法的核心函数是可行和正确的。经过实验总结出所有蛋白质空间结构都可以通过两种类型函数构造出来,提出了描述蛋白质折叠过程模型。与其它蛋白质折叠过程模拟算法的实验结果比较表明,拟蛇算法所构造的空间结构能量值最小、相似度最好。进而说明拟蛇算法和蛋白质折叠过程模型在描述蛋白质折叠过程方面具有明显优势。     

具有分子伴侣功能的抗体

蛋白质的折叠问题一直是生物学研究的前沿之一，蛋白质稳态平衡的破坏与衰老及很多神经退行性疾病的发病机理密切相关，而蛋白质的正确折叠与蛋白质稳态在很大程度上取决于分子伴侣参与构建的复杂网络。许多研究表明，抗体可以作为分子伴侣促进蛋白质的正确折叠，并阻止蛋白质的异常聚集，抗体所具有的严格底物特异性使其具备了治疗特定蛋白质折叠病、帮助包涵体复性等应用潜力。本文简要介绍了分子伴侣的研究进展，详细阐述了具有分子伴侣功能的抗体及单链抗体的研究进展，最后重点讨论了可抑制蛋白质聚集的抗体的研究近况。     

蛋白质工程和蛋白质折叠

蛋白质一级结构决定着高级结构。蛋白质肽链在适宜条件下会自动卷曲形成其相应的高级结构,即自动发生蛋白质折叠,其自动发生的原因和过程仍不十分清楚,但是随着蛋白质工程的日益兴起,这些与折叠有关的问题也愈显重要,就此已有文章进行过讨论[1,2]。反之,如把新兴的蛋白质工程手段(尤其是基因定点诱变技术)应用来研究这些折叠问题,必将推动蛋白质折叠的研究。本文将就蛋白质折叠与蛋白质工程相互影响的一些例子进行讨论。     

Mechanisms of protein folding

Understanding the mechanism by which a polypeptide chain folds into its native structure is a central problem of modern biophysics. The collaborative efforts of experimental and theoretical studies recently raised the tantalizing possibility to define a unifying mechanism for protein folding. In this review we summarize some of these intriguing advances and analyze them together with a discussion on the new findings concerning the so-called downhill folding.     

Folding pathway of the b1 domain of protein G explored by multiscale modeling

The understanding of the folding mechanisms of single-domain proteins is an essential step in the understanding of protein folding in general. Recently, we developed a mesoscopic CA-CB side-chain protein model, which was successfully applied in protein structure prediction, studies of protein thermodynamics, and modeling of protein complexes. In this research, this model is employed in a detailed characterization of the folding process of a simple globular protein, the B1 domain of IgG-binding protein G (GB1). There is a vast body of experimental facts and theoretical findings for this protein. Performing unbiased, ab initio simulations, we demonstrated that the GB1 folding proceeds via the formation of an extended folding nucleus, followed by slow structure fine-tuning. Remarkably, a subset of native interactions drives the folding from the very beginning. The emerging comprehensive picture of GB1 folding perfectly matches and extends the previous experimental and theoretical studies.     

Correlation of folding kinetics with the number and isomerization states of prolines in three homologous proteins of the RNase family

Several studies attribute the slower phases in protein folding to prolyl isomerizations, and several others do not. A correlation exists between the number of prolines in a protein and the complexity of the mechanism with which it folds. In this study, we have demonstrated a direct correlation between the number of cis-prolyl bonds in a native protein and the complexity with which it folds via slower phases by studying the folding of three structurally homologous proteins of the ribonuclease family, namely RNase A, onconase and angiogenin, which differ in the number and isomerization states of their proline residues.     

Using motion planning to map protein folding landscapes and analyze folding kinetics of known native structures.

We investigate a novel approach for studying the kinetics of protein folding. Our framework has evolved from robotics motion planning techniques called probabilistic roadmap methods (PRMs) that have been applied in many diverse fields with great success. In our previous work, we presented our PRM-based technique and obtained encouraging results studying protein folding pathways for several small proteins. In this paper, we describe how our motion planning framework can be used to study protein folding kinetics. In particular, we present a refined version of our PRM-based framework and describe how it can be used to produce potential energy landscapes, free energy landscapes, and many folding pathways all from a single roadmap which is computed in a few hours on a desktop PC. Results are presented for 14 proteins. Our ability to produce large sets of unrelated folding pathways may potentially provide crucial insight into some aspects of folding kinetics, such as proteins that exhibit both two-state and three-state kinetics that are not captured by other theoretical techniques.     

Taming the complexity of protein folding

Protein folding is an important problem in structural biology with significant medical implications, particularly for misfolding disorders like Alzheimer's disease. Solving the folding problem will ultimately require a combination of theory and experiment, with theoretical models providing a comprehensive view of folding and experiments grounding these models in reality. Here we review progress towards this goal over the past decade, with an emphasis on recent theoretical advances that are empowering chemically detailed models of folding and the new results these technologies are providing. In particular, we discuss new insights made possible by Markov state models (MSMs), including the role of non-native contacts and the hub-like character of protein folded states.     

GroEL-mediated protein folding: making the impossible, possible

Protein folding is a spontaneous process that is essential for life, yet the concentrated and complex interior of a cell is an inherently hostile environment for the efficient folding of many proteins. Some proteins-constrained by sequence, topology, size, and function-simply cannot fold by themselves and are instead prone to misfolding and aggregation. This problem is so deeply entrenched that a specialized family of proteins, known as molecular chaperones, evolved to assist in protein folding. Here we examine one essential class of molecular chaperones, the large, oligomeric, and energy utilizing chaperonins or Hsp60s. The bacterial chaperonin GroEL, along with its co-chaperonin GroES, is probably the best-studied example of this family of protein-folding machine. In this review, we examine some of the general properties of proteins that do not fold well in the absence of GroEL and then consider how folding of these proteins is enhanced by GroEL and GroES. Recent experimental and theoretical studies suggest that chaperonins like GroEL and GroES employ a combination of protein isolation, unfolding, and conformational restriction to drive protein folding under conditions where it is otherwise not possible.     

What we have learned about prokaryotes from structural genomics

Five years ago systematic determination and theoretical analysis of all protein structures encoded in model prokaryotic organisms was proposed as a powerful way to obtain new insights into protein function and the variety of protein folds. What has been the pay-off from studying structures in genomic context? Have we learned anything new about protein structure? Can we now predict protein function better? In this contribution, I summarize the status of large-scale structure determination projects on prokaryotes and provide an overview of the main results obtained from experimental and theoretical studies in this dynamic research field.     

GroEL-Mediated Protein Folding: Making the Impossible,Possible

ABSTRACT

Protein folding is a spontaneous process that is essential for life, yet the concentrated and complex interior of a cell is an inherently hostile environment for the efficient folding of many proteins. Some proteins—constrained by sequence, topology, size, and function—simply cannot fold by themselves and are instead prone to misfolding and aggregation. This problem is so deeply entrenched that a specialized family of proteins, known as molecular chaperones, evolved to assist in protein folding. Here we examine one essential class of molecular chaperones, the large, oligomeric, and energy utilizing chaperonins or Hsp60s. The bacterial chaperonin GroEL, along with its co-chaperonin GroES, is probably the best-studied example of this family of protein-folding machine. In this review, we examine some of the general properties of proteins that do not fold well in the absence of GroEL and then consider how folding of these proteins is enhanced by GroEL and GroES. Recent experimental and theoretical studies suggest that chaperonins like GroEL and GroES employ a combination of protein isolation, unfolding, and conformational restriction to drive protein folding under conditions where it is otherwise not possible.     

Multi-State Proteins: Approach Allowing Experimental Determination of the Formation Order of Structure Elements in the Green Fluorescent Protein

The most complex problem in studying multi-state protein folding is the determination of the sequence of formation of protein intermediate states. A far more complex issue is to determine at what stages of protein folding its various parts (secondary structure elements) develop. The structure and properties of different intermediate states depend in particular on these parts. An experimental approach, named μ-analysis, which allows understanding the order of formation of structural elements upon folding of a multi-state protein was used in this study. In this approach the same elements of the protein secondary structure are “tested” by substitutions of single hydrophobic amino acids and by incorporation of cysteine bridges. Single substitutions of hydrophobic amino acids contribute to yielding information on the late stages of protein folding while incorporation of ss-bridges allows obtaining data on the initial stages of folding. As a result of such an μ-analysis, we have determined the order of formation of beta-hairpins upon folding of the green fluorescent protein.