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。     

一种在格点模型上模拟蛋白质折叠结构的优化算法

蛋白质折叠问题是生物信息学中一个经典的多项式复杂程度的非确定性(non-deterministic polynomial,NP)难度问题.势能曲面变平法(ELP)是一种启发式的全局优化算法.通过对ELP方法中的直方图函数提出一种新的更新机制,并将基于贪心策略的初始构象的产生,基于牵引移动的邻域搜索策略与ELP方法相结合,为面心立方体(FCC)格点模型的蛋白质折叠问题提出一种改进的势能曲面变平(ELP+)算法.采用文献中9条常用序列作为测试集.对于每条序列,ELP+算法均能找到与文献中的算法所得到的最低能量相等或更低的能量.实验结果表明,ELP+算法是求解FCC格点模型的蛋白质折叠问题的一种有效算法.     

基于新杂合进化算法的蛋白质折叠计算

蛋白质能量最小化是蛋白质折叠的重要内容。用于蛋白质折叠的新的杂合进化算法结合了交叉和柯西变异。基于toy模型的蛋白质能量最小化算例表明,这个新的杂合进化算法是有效的。     

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模型的大麻素受体CB2折叠研究

Cannabinoid receptor Type 2(简称CB2)是大麻素受体的一种亚型,因为其无中枢神经副作用,不会产生成瘾性及耐受性,显示出了非常好的开发前景和潜在的应用价值。其作为免疫调节剂、神经保护剂和抗癌药等将具有巨大市场价值。目前,CB2蛋白的空间结构还未被测定出来,对于CB2的折叠问题研究也开展的较少,为了研究大麻素受体亚型蛋白CB2的折叠问题以及方便更多的研究人员对CB2空间结构和相关药理特性的研究,本文提出了一种基于HP模型的折叠求解方法。通过使用回溯机制和蒙特卡罗方法对此优化问题进行求解,算法可有效的在全局范围内进行寻找最优解,避免了掉入局部最优问题。实验结果表明,本文方法获取的CB2蛋白空间构象具有较低的能量值,折叠情况较好。     

内质网未折叠蛋白应答

<正>生命每时每刻都在制造蛋白质,大部分蛋白质需要经过翻译后修饰并进一步折叠出正确空间结构后被运输到特定位置发挥正确生物学功能。然而细胞在营养缺乏、病毒感染等不利环境下,容易导致蛋白质修饰异常而破坏蛋白质折叠,造成大量未折叠蛋白质积累而损伤细胞功能。为此,细胞需通过三方面调整来适应环境,包括减少翻译以缓解新生蛋白的折叠需求;降解未折叠蛋白质以减轻损伤;增加细胞伴侣蛋白表达以协助蛋白质折叠,这个过     

分子伴侣及其在蛋白质折叠中的作用研究进展

蛋白质折叠是一个复杂的、动态的过程,蛋白质的折叠不是自发的,需要其他物质的帮助.了解分子伴侣在蛋白质折叠过程中的的作用,有助于进一步研究蛋白质折叠机制.本文介绍了分子伴侣及其分类,重点综述了各类分子伴侣在蛋白质折叠中的机制,并提出了研究分子伴侣在蛋白质折叠中的作用的重要意义.     

未折叠蛋白质的普遍初始热力学亚稳态

探索和理解蛋白质折叠问题一直是分子生物学、结构生物学和生物物理学的终极挑战.未折叠的蛋白质应该存在一种普遍初始热力学亚稳态,否则无法解释蛋白质是如何在剧烈的热振动干扰下完成快速精确折叠的.本文通过分析水溶液环境和蛋白质折叠的相关性,揭示了一种由水分子屏蔽效应引起的未折叠蛋白质的普遍初始热力学亚稳态,该亚稳态的存在是水溶液环境中水分子的物理性质决定,并赋予未折叠蛋白质抵抗热扰动和避免错误折叠的能力.我们通过研究已发表的实验数据和建立分子模型,找到了该初始热力学亚稳态存在的相关证据,并推测了该亚稳态导致蛋白质精确折叠的相关物理学机制.     

蛋白质复合物结合自由能的预测

本文发展了一种合理的经验能量函数和结合自由能算法,并应用到２１个蛋白质复合物的结合自由能预测上。与现今发表的其他工作相比,我们的结果与实验的测定值符合得更好,平均预测精度为１．０ｋｃａｌ／ｍｏｌ,与实验值的相关达到９６％。应用本方法预测一个典型的蛋白质与其抑制剂复合物的结合自由能,在ＳＧＩ－ＩＭＰＡＣＴ Ｒ１００００工作站上约需２分钟。本文的结果还证实,与对蛋白折叠过程的认识不同,亲水原子在蛋白质     

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。     

Changes of protein stiffness during folding detect protein folding intermediates

Single-molecule force-quench atomic force microscopy (FQ-AFM) is used to detect folding intermediates of a simple protein by detecting changes of molecular stiffness of the protein during its folding process. Those stiffness changes are obtained from shape and peaks of an autocorrelation of fluctuations in end-to-end length of the folding molecule. The results are supported by predictions of the equipartition theorem and agree with existing Langevin dynamics simulations of a simplified model of a protein folding. In the light of the Langevin simulations the experimental data probe an ensemble of random-coiled collapsed states of the protein, which are present both in the force-quench and thermal-quench folding pathways.     

How RNA folds.

We describe the RNA folding problem and contrast it with the much more difficult protein folding problem. RNA has four similar monomer units, whereas proteins have 20 very different residues. The folding of RNA is hierarchical in that secondary structure is much more stable than tertiary folding. In RNA the two levels of folding (secondary and tertiary) can be experimentally separated by the presence or absence of Mg2+. Secondary structure can be predicted successfully from experimental thermodynamic data on secondary structure elements: helices, loops, and bulges. Tertiary interactions can then be added without much distortion of the secondary structure. These observations suggest a folding algorithm to predict the structure of an RNA from its sequence. However, to solve the RNA folding problem one needs thermodynamic data on tertiary structure interactions, and identification and characterization of metal-ion binding sites. These data, together with force versus extension measurements on single RNA molecules, should provide the information necessary to test and refine the proposed algorithm.     

BetaSuperposer: superposition of protein surfaces using beta-shapes

The comparison between two protein structures is important for understanding a molecular function. In particular, the comparison of protein surfaces to measure their similarity provides another challenge useful for studying molecular evolution, docking, and drug design. This paper presents an algorithm, called the BetaSuperposer, which evaluates the similarity between the surfaces of two structures using the beta-shape which is a geometric structure derived from the Voronoi diagram of molecule. The algorithm performs iterations of mix-and-match between the beta-shapes of two structures for the optimal superposition from which a similarity measure is computed, where each mix-and-match step attempts to solve an NP-hard problem. The devised heuristic algorithm based on the assignment problem formulation quickly produces a good superposition and an assessment of similarity. The BetaSuperposer was fully implemented and benchmarked against popular programs, the Dali and the Click, using the SCOP models. The BetaSuperposer is freely available to the public from the Voronoi Diagram Research Center (http://voronoi.hanyang.ac.kr).     

Multiplexed-Replica Exchange Molecular Dynamics Method for Protein Folding Simulation

Simulating protein folding thermodynamics starting purely from a protein sequence is a grand challenge of computational biology. Here, we present an algorithm to calculate a canonical distribution from molecular dynamics simulation of protein folding. This algorithm is based on the replica exchange method where the kinetic trapping problem is overcome by exchanging noninteracting replicas simulated at different temperatures. Our algorithm uses multiplexed-replicas with a number of independent molecular dynamics runs at each temperature. Exchanges of configurations between these multiplexed-replicas are also tried, rendering the algorithm applicable to large-scale distributed computing (i.e., highly heterogeneous parallel computers with processors having different computational power). We demonstrate the enhanced sampling of this algorithm by simulating the folding thermodynamics of a 23 amino acid miniprotein. We show that better convergence is achieved compared to constant temperature molecular dynamics simulation, with an efficient scaling to large number of computer processors. Indeed, this enhanced sampling results in (to our knowledge) the first example of a replica exchange algorithm that samples a folded structure starting from a completely unfolded state.     

Prediction of the initial folding sites and the entire folding processes for Ig-like beta-sandwich proteins

Describing the whole story of protein folding is currently the main enigmatic problem in molecular bioinformatics study. Protein folding mechanisms have been intensively investigated with experimental as well as simulation techniques. Since a protein folds into its specific 3D structure from a unique amino acid sequence, it is interesting to extract as much information as possible from the amino acid sequence of a protein. Analyses based on inter-residue average distance statistics and a coarse-grained Gō-model simulation were conducted on Ig and FN3 domains of a titin protein to decode the folding mechanisms from their sequence data and native structure data, respectively. The central region of all domains was predicted to be an initial folding unit, that is, stable in an early state of folding. This common feature coincides well with the experimental results and underscores the significance of the β-sandwich proteins' common structure, namely, the key strands for folding and the Greek-key motif, which is located in the central region. We confirmed that our sequence-based techniques were able to predict the initial folding event just next to the denatured state and that a 3D-based Gō-model simulation can be used to investigate the whole process of protein folding.     

Isolation of point mutations that affect the folding of the H chain of human ferritin in E.coli.

We have approached the problem of folding and assembly of the heavy (H) chain of human ferritin by isolating point mutations that affect this process. Apoferritin is an ideal model system to approach the problem of protein folding and assembly into multimeric structures. We have developed a recombinant hybrid molecule that allows us to select for ferritin mutants in which the folding-assembly process is altered or completely impaired. The selection procedure is based on a recombinant protein which consists of a fusion between the H chain of human ferritin and the alpha-peptide of beta-galactosidase. In the wild type situation, the alpha-peptide domain is segregated inside the apoferritin shell upon assembly and is unable to interact with the substrate and perform its enzymic function. We show that by selecting for mutations that restore beta-galactosidase activity we are able to identify ferritin mutations that affect the folding-assembly process. The selective procedure was applied to the analysis of the amino acid side chains that are important for the attainment of the correct conformation of the carboxy-terminal E helix in the 4-fold axis.     

Distinguishing between sequential and nonsequentially folded proteins: implications for folding and misfolding.

We describe here an algorithm for distinguishing sequential from nonsequentially folding proteins. Several experiments have recently suggested that most of the proteins that are synthesized in the eukaryotic cell may fold sequentially. This proposed folding mechanism in vivo is particularly advantageous to the organism. In the absence of chaperones, the probability that a sequentially folding protein will misfold is reduced significantly. The problem we address here is devising a procedure that would differentiate between the two types of folding patterns. Footprints of sequential folding may be found in structures where consecutive fragments of the chain interact with each other. In such cases, the folding complexity may be viewed as being lower. On the other hand, higher folding complexity suggests that at least a portion of the polypeptide backbone folds back upon itself to form three-dimensional (3D) interactions with noncontiguous portion(s) of the chain. Hence, we look at the mechanism of folding of the molecule via analysis of its complexity, that is, through the 3D interactions formed by contiguous segments on the polypeptide chain. To computationally splice the structure into consecutively interacting fragments, we either cut it into compact hydrophobic folding units or into a set of hypothetical, transient, highly populated, contiguous fragments ("building blocks" of the structure). In sequential folding, successive building blocks interact with each other from the amino to the carboxy terminus of the polypeptide chain. Consequently, the results of the parsing differentiate between sequentially vs. nonsequentially folded chains. The automated assessment of the folding complexity provides insight into both the likelihood of misfolding and the kinetic folding rate of the given protein. In terms of the funnel free energy landscape theory, a protein that truly follows the mechanism of sequential folding, in principle, encounters smoother free energy barriers. A simple sequentially folded protein should, therefore, be less error prone and fold faster than a protein with a complex folding pattern.