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1.
氨基酸残基可及性与蛋白质家族成员结构的保守性   总被引:1,自引:1,他引:0       下载免费PDF全文
本文在细胞色素c族蛋白和免疫球蛋白家族中一些蛋白质片段的序列比较和分析的基础上,通过计算其氨基酸残基的可及性,对残基可及性与蛋白质序列及其三维结构的保守性之间的关系进行了分析和探讨。结果表明,序列中凡是保守的残基,其可及性都较低,而且这些低可及性的保守性残基与维持蛋白质特有的三维结构相关。作者认为,同一家族的蛋白质中,在进化上相距较远的各成员之间,结构的保守性主要是体现在其三维结构上;序列中的保守  相似文献   

2.
蛋白质结构的预测在理解蛋白质结构组成和蛋白质的生物学功能有重要意义,而蛋白质二级结构预测是蛋白质结构预测的重要环节。当PSSM位置特异性进化矩阵被广泛应用于将蛋白质初级结构序列编码作为输入样本后,每个残基可以被表示成二维空间的数据平面,由此文中尝试利用卷积神经网络对其进行训练。文中还设计了另一种卷积神经网络,利用长短记忆网络感知了CNN最后卷积特征面的横向特征和纵向特征后连同卷积神经网络的全连接共同完成分类,最后用ensemble方法对两类卷积神经网络模型进行了整合,最终ensemble方法中包含两类卷积神经网络的六个模型,在CB513蛋白质数据集测得的Q3结果为77.2。  相似文献   

3.
详细考察了基于HNP(H:hydtophobic,N:neutral,P:hydrophilic)模型及相对熵的蛋白质设计方法对于不同结构类型蛋白质的适用性,并与基于HP模型的结果进行了比较.通过对190个4种不同结构类型的蛋白质进行预测,结果表明,基于HNP模型及相对熵的设计方法对于不同结构类型的蛋白质具有普适性.进一步的研究发现,对于α螺旋、β折叠等规则的二级结构,该方法的预测成功率高于无规卷曲结构预测成功率.另外,还比较了对不同氨基酸的预测差异,结果显示亲水残基的预测成功率较高.此外,研究表明该方法对于蛋白质保守残基的预测成功率高于非保守残基.在以上分析的基础上,进一步讨论了导致这些差异的原因.这些研究为基于相对熵的蛋白质设计方法的实际应用和进一步的发展打下了良好基础.  相似文献   

4.
结构域是蛋白质的一个结构层次 ,可以看作是蛋白质结构、折叠、功能、进化和设计的基本单位。大多数的蛋白质都可分为若干个结构域 ,结构域的不同组合使蛋白质具有不同的三级结构并具有不同的功能。蛋白质结构域的划分在理论与应用上都具有重要意义 ,但目前对结构域的划分还没有一个十分理想的方法。作者曾经发展了一种通过计算去折叠自由能划分蛋白质结构域的方法 ,但该方法只适用于连续双结构域的划分。现在 ,作者通过构造氨基酸残基相互作用矩阵 ,并进行对应分析 (correspondenceanalysis) ,然后根据去折叠自由能和一些经验打分函数对蛋白质进行切割和优选 ,发展了可以同时处理连续和不连续结构域的划分方法。该方法与晶体结构作者手工分析相比较 ,二者的结果有 76 %的相似。  相似文献   

5.
结构域是进化上的保守序列单元,是蛋白质的结构和功能的标准组件.典型的两个蛋白质间的相互作用涉及特殊结构域间的结合,而且识别相互作用结构域对于在结构域水平上彻底理解蛋白质的功能与进化、构建蛋白质相互作用网络、分析生物学通路等十分重要.目前,依赖于对实验数据的进一步挖掘和对各种不同输入数据的计算预测,已识别出了一些相互作用/功能连锁结构域对,并由此构建了内容丰富、日益更新的结构域相互作用数据库.综述了产生结构域相互作用的8种计算预测方法.介绍了5个结构域相互作用公共数据库3DID、iPfam、InterDom、DIMA和DOMINE的有关信息和最新动态.实例概述了结构域相互作用在蛋白质相互作用计算预测、可信度评估,蛋白质结构域注释,以及在生物学通路分析中的应用.  相似文献   

6.
丝氨酸蛋白酶超家族分子结构进化研究   总被引:5,自引:0,他引:5  
采用刚体结构比较法进行蛋白质的结构比较,根据结构比较分数构建分子进化树, 研究丝氨酸蛋白酶超家族分子的进化规律。对分子进化树进行了一些初步分析,得到了一些有意义的结果。根据蛋白质的进化,可以比较精确的确定某物种的进化地位,对于物种的分类具有重要意义。通过对超家族分子进化的研究可以了解蛋白质超家族不同蛋白质之间的亲缘关系和蛋白质之间的进化差异,对于蛋白质工程分子设计提供帮助,对蛋白质结构预测具有一定意义  相似文献   

7.
真核翻译延伸因子1A(eEF1A)是真核生物蛋白质翻译过程中能将氨酰tRNA运送到核糖体A位点参与多肽延伸反应的多功能蛋白质. 本文主要利用多种生物信息学分析工具进行地中海涡虫翻译延伸因子1A(SmEF1A)蛋白序列的查找与eEF1A直系同源蛋白的搜索, 并基于90条直系同源蛋白进行eEF1A蛋白家族的进化踪迹分析和SmEF1A蛋白功能位点的比较研究. 结果表明,在eEF1A蛋白家族中共识别到338个踪迹残基位点和20个踪迹残基富集区域,SmEF1A蛋白的功能位点与踪迹残基位点密切相关,与GTP/Mg2+结合相关的S21、T72、D91、G94等重要位点均为全家族保守的踪迹残基,N 糖基化、磷酸化等蛋白修饰位点中踪迹残基位点往往是被修饰的部位或修饰功能发挥的关键辅助位点,而位于分子表面的配基结合口袋则与20个踪迹残基富集区域在分子表面形成的踪迹残基簇关系密切. eEF1A蛋白家族的进化踪迹分析为eEF1A蛋白重要功能区域关键残基的确定和未知功能位点的预测提供了重要信息.  相似文献   

8.
固有无序蛋白质(intrinsically disordered proteins,IDPs)是天然条件下自身不能折叠为明确唯一的空间结构,却具有生物学功能的一类新发现的蛋白质.这类蛋白质的发现是对传统的"结构-功能"关系认识模式的挑战.本文首先总结了无序蛋白质的实验鉴定手段、预测方法、数据库;并介绍了无序蛋白质结构(包括一级结构、二级结构、结构域无序性及变构效应)和功能特征;然后重点总结了无序蛋白质在进化角度研究的进展,包括无序区域产生的进化机制、进化速率,蛋白无序性的进化在蛋白质功能进化及生物学复杂性增加等方面的重要作用;最后展望了无序蛋白质在医药方面的应用前景.本文对于深入认识无序蛋白质的形成机制、结构和功能特征及其潜在的临床应用前景具有重要意义.  相似文献   

9.
真核细胞中的许多蛋白质是糖蛋白,其寡糖链以共价键连接到特定的氨基酸残基上。糖蛋白糖链的生物学功能是通过糖链对蛋白质功能的修饰、糖缀合物糖链与蛋白质的识别来实现的,糖基化是生物体最常见最主要的蛋白质修饰作用之一。糖链结构及其功能和调控的复杂性制约了其研究的速度,随着生物信息学的快速发展,糖生物学领域的数据库和预测软件也脱颖而出,该文介绍糖基化作用和糖生物学领域的数据库与预测软件。  相似文献   

10.
蛋白质残基替换是基因突变的产物之一,它可能改变蛋白质三维结构,对其生物学功能产生重大影响,因此研究蛋白质残基替换与结构改变的关系具有重要意义.随着实验解析蛋白质结构的数量迅猛增长,越来越多的野生型-突变体被应用于结构生物学的比较研究中.本研究从蛋白质三维结构数据库(PDB)出发,收集和计算了大量结构特征数据,构建了一个目前已知最大的野生型-突变体(单残基差异)的结构对数据库DRSP,展示出氨基酸类型和主链偏好性对结构保守性的相关性.DRSP的开放使用可为高精度的蛋白质结构分析预测提供有用信息,它的数据库网址是http://www.labshare.cn/drsp/index.php.  相似文献   

11.
Recently, protein sequence coevolution analysis has matured into a predictive powerhouse for protein structure and function. Direct methods, which use global statistical models of sequence coevolution, have enabled the prediction of membrane and disordered protein structures, protein complex architectures, and the functional effects of mutations in proteins. The field of membrane protein biochemistry and structural biology has embraced these computational techniques, which provide functional and structural information in an otherwise experimentally-challenging field. Here we review recent applications of protein sequence coevolution analysis to membrane protein structure and function and highlight the promising directions and future obstacles in these fields. We provide insights and guidelines for membrane protein biochemists who wish to apply sequence coevolution analysis to a given experimental system.  相似文献   

12.
Correlated mutation analysis (CMA) has been used to investigate protein functional sites. However, CMA has suffered from low signal-to-noise ratio caused by meaningless phylogenetic signals or structural constraints. We present a new method, Structure-based Correlated Mutation Analysis (SCMA), which encodes coevolution scores into a protein structure network. A path-based network model is adapted to describe information transfer between residues, and the statistical significance is estimated by network shuffling. This model intrinsically assumes that residues in physical contact have a more reliable coevolution score than distant residues, and that coevolution in distant residues likely arises from a series of contacting and coevolving residues. In addition, coevolutionary coupling is statistically controlled to remove the structural effects. When applied to the rhodopsin structure, the SCMA method identified a much higher percentage of functional residues than the typical coevolution score (61% vs. 22%). In addition, statistically significant residues are used to construct the coevolved residue-residue subnetwork. The network has one highly connected node (retinal bound Lys296), indicating that Lys296 can induce and regulate most other coevolved residues in a variety of locations. The coevolved network consists of a few modular clusters which have distinct functional roles. This article is part of a Special Issue entitled: Computational Methods for Protein Interaction and Structural Prediction.  相似文献   

13.
The identification of protein sites undergoing correlated evolution (coevolution) is of great interest due to the possibility that these pairs will tend to be adjacent in the three-dimensional structure. Identification of such pairs should provide useful information for understanding the evolutionary process, predicting the effects of site-directed substitution, and potentially for predicting protein structure. Here, we develop and apply a maximum likelihood method with the aim of improving detection of coevolution. Unlike previous methods which have had limited success, this method allows for correlations induced by phylogenetic relationships and for variation in rate of evolution along branches, and does not rely on accurate reconstruction of ancestral nodes. In order to reduce the complexity of coevolutionary relationships and identify the primary component of pairwise coevolution between two sites, we reduce the data to a two-state system at each site, regardless of the actual number of residues observed at that site. Simulations show that this strategy is good at identifying simple correlations and at recognizing cases in which the data are insufficient to distinguish between coevolution and spurious correlations. The new method was tested by using size and charge characteristics to group the residues at each site, and then evaluating coevolution in myoglobin sequences. Grouping based on physicochemical characteristics allows categorization of coevolving sites into positive and negative coevolution, depending on the correlation between equilibrium state frequencies. We detected a striking excess of negative coevolution (corresponding to charge) at sites brought into proximity by the periodicity of the alpha-helix, and there was also a tendency for sites with significant likelihood ratios to be close in the three-dimensional structure. Sites on the surface of the protein appear to coevolve both when they are close in the structure, and when they are distant, implying a role for folding and/or avoidance of quaternary structure in the coevolution process.  相似文献   

14.
Intraprotein side chain contacts can couple the evolutionary process of amino acid substitution at one position to that at another. This coupling, known as residue coevolution, may vary in strength. Conserved contacts thus not only define 3-dimensional protein structure, but also indicate which residue-residue interactions are crucial to a protein's function. Therefore, prediction of strongly coevolving residue-pairs helps clarify molecular mechanisms underlying function. Previously, various coevolution detectors have been employed separately to predict these pairs purely from multiple sequence alignments, while disregarding available structural information. This study introduces an integrative framework that improves the accuracy of such predictions, relative to previous approaches, by combining multiple coevolution detectors and incorporating structural contact information. This framework is applied to the ABC-B and ABC-C transporter families, which include the drug exporter P-glycoprotein involved in multidrug resistance of cancer cells, as well as the CFTR chloride channel linked to cystic fibrosis disease. The predicted coevolving pairs are further analyzed based on conformational changes inferred from outward- and inward-facing transporter structures. The analysis suggests that some pairs coevolved to directly regulate conformational changes of the alternating-access transport mechanism, while others to stabilize rigid-body-like components of the protein structure. Moreover, some identified pairs correspond to residues previously implicated in cystic fibrosis.  相似文献   

15.
Currently, the identification of groups of amino acid residues that are important in the function, structure, or interaction of a protein can be both costly and prohibitively complex, involving vast numbers of mutagenesis experiments. Here, we present the application of a novel computational method, which identifies the presence of coevolution in a data set, thereby enabling the a priori identification of amino acid residues that play an important role in protein function. We have applied this method to the heat shock protein (Hsp) protein-folding system, studying the network between Hsp70, Hsp90, and Hop (heat shock-organizing protein). Our analysis has identified functional residues within the tetratricopeptide repeat (TPR) 1 and 2A domains in Hop, previously shown to be interacting with Hsp70 and Hsp90, respectively. Further, we have identified significant residues elsewhere in Hop within domains that have been recently proposed as being important for Hop interaction with Hsp70 and/or Hsp90. In addition, several amino acid sites present in groups of coevolution were identified as 3-dimensionally or linearly proximal to functionally important sites or domains. Based on our results, we also investigate a further functional domain within Hop, between TPR1 and TPR2A, which we suggest as being functionally important in the interaction of Hop with both Hsp70 and Hsp90 whether directly or otherwise. Our method has identified all the previously characterized functionally important regions in this system, thereby indicating the power of this method in the a priori identification of important regions for site-directed mutagenesis studies.  相似文献   

16.
The strength and pattern of coevolution between amino acid residues vary depending on their structural and functional environment. This context dependence, along with differences in analytical technique, is responsible for the different results among coevolutionary analyses of different proteins. It is thus important to perform detailed study of individual proteins to gain better insight into how context dependence can affect coevolutionary patterns even within individual proteins, and to unravel the details of context dependence with respect to structure and function. Here we extend our previous study by presenting further analysis of residue coevolution in cytochrome c oxidase subunit I sequences from 231 vertebrates using a statistically robust phylogeny-based maximum likelihood ratio method. As in previous studies, a strong overall coevolutionary signal was detected, and coevolution within structural regions was significantly related to the Cα distances between residues. While the strong selection for adjacent residues among predicted coevolving pairs in the surface region indicates that the statistical method is highly selective for biologically relevant interactions, the coevolutionary signal was strongest in the transmembrane region, although the distances between coevolving residues were greater. This indicates that coevolution may act to maintain more global structural and functional constraints in the transmembrane region. In the transmembrane region, sites that coevolved according to polarity and hydrophobicity rather than volume had a greater tendency to colocalize with just one of the predicted proton channels (channel H). Thus, the details of coevolution in cytochrome c oxidase subunit I depend greatly on domain structure and residue physicochemical characteristics, but proximity to function appears to play a critical role. We hypothesize that coevolution is indicative of a more important functional role for this channel. Electronic Supplementary Material The online version of this article (doi:) contains supplementary material, which is available to authorized users.  相似文献   

17.
Communication between distant sites often defines the biological role of a protein: amino acid long-range interactions are as important in binding specificity, allosteric regulation and conformational change as residues directly contacting the substrate. The maintaining of functional and structural coupling of long-range interacting residues requires coevolution of these residues. Networks of interaction between coevolved residues can be reconstructed, and from the networks, one can possibly derive insights into functional mechanisms for the protein family. We propose a combinatorial method for mapping conserved networks of amino acid interactions in a protein which is based on the analysis of a set of aligned sequences, the associated distance tree and the combinatorics of its subtrees. The degree of coevolution of all pairs of coevolved residues is identified numerically, and networks are reconstructed with a dedicated clustering algorithm. The method drops the constraints on high sequence divergence limiting the range of applicability of the statistical approaches previously proposed. We apply the method to four protein families where we show an accurate detection of functional networks and the possibility to treat sets of protein sequences of variable divergence.  相似文献   

18.
Small protein fragments, and not just residues, can be used as basic building blocks to reconstruct networks of coevolved amino acids in proteins. Fragments often enter in physical contact one with the other and play a major biological role in the protein. The nature of these interactions might be multiple and spans beyond binding specificity, allosteric regulation and folding constraints. Indeed, coevolving fragments are indicators of important information explaining folding intermediates, peptide assembly, key mutations with known roles in genetic diseases, distinguished subfamily-dependent motifs and differentiated evolutionary pressures on protein regions. Coevolution analysis detects networks of fragments interaction and highlights a high order organization of fragments demonstrating the importance of studying at a deeper level this structure. We demonstrate that it can be applied to protein families that are highly conserved or represented by few sequences, enlarging in this manner, the class of proteins where coevolution analysis can be performed and making large-scale coevolution studies a feasible goal.  相似文献   

19.
Correlated changes of nucleic or amino acids have provided strong information about the structures and interactions of molecules. Despite the rich literature in coevolutionary sequence analysis, previous methods often have to trade off between generality, simplicity, phylogenetic information, and specific knowledge about interactions. Furthermore, despite the evidence of coevolution in selected protein families, a comprehensive screening of coevolution among all protein domains is still lacking. We propose an augmented continuous-time Markov process model for sequence coevolution. The model can handle different types of interactions, incorporate phylogenetic information and sequence substitution, has only one extra free parameter, and requires no knowledge about interaction rules. We employ this model to large-scale screenings on the entire protein domain database (Pfam). Strikingly, with 0.1 trillion tests executed, the majority of the inferred coevolving protein domains are functionally related, and the coevolving amino acid residues are spatially coupled. Moreover, many of the coevolving positions are located at functionally important sites of proteins/protein complexes, such as the subunit linkers of superoxide dismutase, the tRNA binding sites of ribosomes, the DNA binding region of RNA polymerase, and the active and ligand binding sites of various enzymes. The results suggest sequence coevolution manifests structural and functional constraints of proteins. The intricate relations between sequence coevolution and various selective constraints are worth pursuing at a deeper level.  相似文献   

20.
Coevolution between proteins is crucial for understanding protein–protein interaction. Simultaneous changes allow a protein complex to maintain its overall structural–functional integrity. In this study, we combined statistical coupling analysis (SCA) and molecular dynamics simulations on the CDK6–CDKN2A protein complex to evaluate coevolution between proteins. We reconstructed an inter-protein residue coevolution network, consisting of 37 residues and 37 interactions. It shows that most of the coevolved residue pairs are spatially proximal. When the mutations happened, the stable local structures were broken up and thus the protein interaction was decreased or inhibited, with a following increased risk of melanoma. The identification of inter-protein coevolved residues in the CDK6–CDKN2A complex can be helpful for designing protein engineering experiments.  相似文献   

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