基于质谱技术的蛋白质互作研究进展

蛋白质作为生命活动的执行者,其功能往往体现在与其他蛋白质的相互作用中,研究蛋白-蛋白相互作用对于人们深入了解和预防传染病、靶向治疗多基因疾病、阐明蛋白质的分子作用机制及各种复杂的生命现象具有重要意义。目前,有多种技术被用来研究蛋白间的相互作用,研究难点在于实时捕获瞬时或弱蛋白质间的相互作用,质谱技术（mass spectrometry, MS）可在某种程度上解决该难点。由于质谱技术可研究简单的蛋白质复合物再到大规模的蛋白质组实验,基于质谱技术研究蛋白质间相互作用被越来越多地应用于科学研究中。综述了蛋白质间相互作用检测方法的研究进展,重点介绍了氢氘交换质谱法和化学交联质谱法研究蛋白质间相互作用的优缺点及其应用,最后对基于质谱技术研究蛋白质间相互作用进行了总结与展望,以期为深入开展相关研究提供借鉴。     

Protein evolution is faster outside the cell

Some proteins are highly conserved across all species, whereas others diverge significantly even between closely related species. Attempts have been made to correlate the rate of protein evolution to amino acid composition, protein dispensability, and the number of protein-protein interactions, but in all cases, conflicting studies have shown that the theories are hard to confirm experimentally. The only correlation that is undisputed so far is that highly/broadly expressed proteins seem to evolve at a lower rate. Consequently, it has been suggested that correlations between evolution rate and factors like protein dispensability or the number of protein-protein interactions could be just secondary effects due to differences in expression. The purpose of this study was to analyze mammalian proteins/genes with known subcellular location for variations in evolution rates. We show that proteins that are exported (extracellular proteins) evolve faster than proteins that reside inside the cell (intracellular proteins). We find weak, but significant, correlations between evolution rates and expression levels, percentage of tissues in which the proteins are expressed (expression broadness), and the number of protein interaction partners. More important, we show that the observed difference in evolution rate between extra- and intracellular proteins is largely independent of expression levels, expression broadness, and the number of protein-protein interactions. We also find that the difference is not caused by an overrepresentation of immunological proteins or disulfide bridge-containing proteins among the extracellular data set. We conclude that the subcellular location of a mammalian protein has a larger effect on its evolution rate than any of the other factors studied in this paper, including expression levels/patterns. We observe a difference in evolution rates between extracellular and intracellular proteins for a yeast data set as well and again show that it is completely independent of expression levels.     

蛋白质相互作用的生物信息学研究进展

生命过程的分子基础在于生物分子之间的相互作用,其中蛋白质分子之间的相互作用占有极其重要的地位。研究蛋白质相互作用对于理解生命的真谛、探讨致病微生物的致病机理,以及研究新药提高人们的健康水平具有重要的作用。用生物信息学的方法研究蛋白质的相互作用已经取得了许多重要的成果,但也有很多问题还需解决。本文从蛋白质相互作用的数据库、预测方法、可预测蛋白质相互作用的网上服务、蛋白质相互作用网络等几方面,对蛋白质相互作用的生物信息学研究成果及其存在的问题做了概述。     

一种利用荧光蛋白mNeonGreen2鉴定EI24蛋白拓扑结构的方法

方便且精准地检测跨膜蛋白拓扑结构,尤其是跨膜片段的氨基(N-)和羧基(C-)端的朝向,有利于发现新的蛋白质与蛋白质之间的相互作用,并进一步揭示蛋白质重要的生物学功能．自组装荧光蛋白已被广泛用于观察蛋白质与蛋白质之间的相互作用、标记细胞内源蛋白质并实现mRNA定位的可视化．本文扩展了自组装荧光蛋白的应用,将自组装荧光蛋白mNeonGreen2与定点标记技术相结合,以确定跨膜蛋白的拓扑结构．通过该方法,第一次清楚地证明了EI24的N端和C端均朝向细胞质方向．此外,该方法可用于确定定位于其他细胞器且结构尚未解析的跨膜蛋白的拓扑结构．     

Computational approaches to protein-protein interaction

The interactions between proteins allow the cell's life. A number of experimental, genome-wide, high-throughput studies have been devoted to the determination of protein-protein interactions and the consequent interaction networks. Here, the bioinformatics methods dealing with protein-protein interactions and interaction network are overviewed. 1. Interaction databases developed to collect and annotate this immense amount of data; 2. Automated data mining techniques developed to extract information about interactions from the published literature; 3. Computational methods to assess the experimental results developed as a consequence of the finding that the results of high-throughput methods are rather inaccurate; 4. Exploitation of the information provided by protein interaction networks in order to predict functional features of the proteins; and 5. Prediction of protein-protein interactions.     

Green fluorescent protein as a signal for protein-protein interactions.

Green fluorescent protein (GFP) is autofluorescent. This property has made GFP useful in monitoring in vivo activities such as gene expression and protein localization. We find that GFP can be used in vitro to reveal and characterize protein-protein interactions. The interaction between the S-peptide and S-protein fragments of ribonuclease A was chosen as a model system. GFP-tagged S-peptide was produced, and the interaction of this fusion protein with S-protein was analyzed by two distinct methods: fluorescence gel retardation and fluorescence polarization. The fluorescence gel retardation assay is a rapid method to demonstrate the existence of a protein-protein interaction and to estimate the dissociation constant (Kd) of the resulting complex. The fluorescence polarization assay is an accurate method to evaluate Kd in a specified homogeneous solution and can be adapted for the high-throughput screening of protein or peptide libraries. These two methods are powerful new tools to probe protein-protein interactions.     

计算方法在蛋白质相互作用研究中的应用

计算方法在蛋白质相互作用研究的各个阶段扮演了一个重要的角色。对此,作者将从以下几个方面对计算方法在蛋白质相互作用及相互作用网络研究中的应用做一个概述：蛋白质相互作用数据库及其发展;数据挖掘方法在蛋白质相互作用数据收集和整合中的应用;高通量方法实验结果的验证;根据蛋白质相互作用网络预测和推断未知蛋白质的功能;蛋白质相互作用的预测。     

基于TurboID的植物蛋白邻近标记实验方法

邻近标记作为近些年发展起来的一项检测活细胞内蛋白互作关系和亚细胞结构蛋白组的新型技术,已成功应用于多种动植物体系的研究。该技术通过给诱饵蛋白融合一个具有特定催化连接活性的酶,在酶的催化作用下将小分子底物(如生物素)共价连接到酶邻近的内源蛋白,通过富集和分析被标记的蛋白可获得与诱饵互作的蛋白组。经定向进化产生的生物素连接...     

MULTIPROSPECTOR: an algorithm for the prediction of protein-protein interactions by multimeric threading

In this postgenomic era, the ability to identify protein-protein interactions on a genomic scale is very important to assist in the assignment of physiological function. Because of the increasing number of solved structures involving protein complexes, the time is ripe to extend threading to the prediction of quaternary structure. In this spirit, a multimeric threading approach has been developed. The approach is comprised of two phases. In the first phase, traditional threading on a single chain is applied to generate a set of potential structures for the query sequences. In particular, we use our recently developed threading algorithm, PROSPECTOR. Then, for those proteins whose template structures are part of a known complex, we rethread on both partners in the complex and now include a protein-protein interfacial energy. To perform this analysis, a database of multimeric protein structures has been constructed, the necessary interfacial pairwise potentials have been derived, and a set of empirical indicators to identify true multimers based on the threading Z-score and the magnitude of the interfacial energy have been established. The algorithm has been tested on a benchmark set comprised of 40 homodimers, 15 heterodimers, and 69 monomers that were scanned against a protein library of 2478 structures that comprise a representative set of structures in the Protein Data Bank. Of these, the method correctly recognized and assigned 36 homodimers, 15 heterodimers, and 65 monomers. This protocol was applied to identify partners and assign quaternary structures of proteins found in the yeast database of interacting proteins. Our multimeric threading algorithm correctly predicts 144 interacting proteins, compared to the 56 (26) cases assigned by PSI-BLAST using a (less) permissive E-value of 1 (0.01). Next, all possible pairs of yeast proteins have been examined. Predictions (n = 2865) of protein-protein interactions are made; 1138 of these 2865 interactions have counterparts in the Database of Interacting Proteins. In contrast, PSI-BLAST made 1781 predictions, and 1215 have counterparts in DIP. An estimation of the false-negative rate for yeast-predicted interactions has also been provided. Thus, a promising approach to help assist in the assignment of protein-protein interactions on a genomic scale has been developed.     

In vivo quantification of protein-protein interactions in Saccharomyces cerevisiae using bimolecular fluorescence complementation assay

Most of the biological processes are carried out and regulated by dynamic networks of protein-protein interactions. In this study, we demonstrate the feasibility of the bimolecular fluorescence complementation (BiFC) assay for in vivo quantitative analysis of protein-protein interactions in Saccharomyces cerevisiae. We show that the BiFC assay can be used to quantify not only the amount but also the cell-to-cell variation of protein-protein interactions in S. cerevisiae. In addition, we show that protein sumoylation and condition-specific protein-protein interactions can be quantitatively analyzed by using the BiFC assay. Taken together, our results validate that the BiFC assay is a very effective method for quantitative analysis of protein-protein interactions in living yeast cells and has a great potential as a versatile tool for the study of protein function.     

Potential of mean force for protein-protein interaction studies.

Calculating protein-protein interaction energies is crucial for understanding protein-protein associations. On the basis of the methodology of mean-field potential, we have developed an empirical approach to estimate binding free energy for protein-protein interactions. This knowledge-based approach has been used to derive distance-dependent free energies of protein complexes from a nonredundant training set in the Protein Data Bank (PDB), with a careful treatment of homology. We calculate atom pair potentials for 16 pair interactions, which can reflect the importance of hydrophobic interactions and specific hydrogen-bonding interactions. The derived potentials for hydrogen-bonding interactions show a valley of favorable interactions at a distance of approximately 3 A, corresponding to that of an established hydrogen bond. For the test set of 28 protein complexes, the calculated energies have a correlation coefficient of 0.75 compared with experimental binding free energies. The performance of the method in ranking the binding energies of different protein-protein complexes shows that the energy estimation can be applied to value binding free energies for protein-protein associations.     

Molecular simulation of the effect of cholesterol on lipid-mediated protein-protein interactions

Experiments and molecular simulations have shown that the hydrophobic mismatch between proteins and membranes contributes significantly to lipid-mediated protein-protein interactions. In this article, we discuss the effect of cholesterol on lipid-mediated protein-protein interactions as function of hydrophobic mismatch, protein diameter and protein cluster size, lipid tail length, and temperature. To do so, we study a mesoscopic model of a hydrated bilayer containing lipids and cholesterol in which proteins are embedded, with a hybrid dissipative particle dynamics-Monte Carlo method. We propose a mechanism by which cholesterol affects protein interactions: protein-induced, cholesterol-enriched, or cholesterol-depleted lipid shells surrounding the proteins affect the lipid-mediated protein-protein interactions. Our calculations of the potential of mean force between proteins and protein clusters show that the addition of cholesterol dramatically reduces repulsive lipid-mediated interactions between proteins (protein clusters) with positive mismatch, but does not affect attractive interactions between proteins with negative mismatch. Cholesterol has only a modest effect on the repulsive interactions between proteins with different mismatch.     

Methods for the detection and analysis of protein-protein interactions

A large number of methods have been developed over the years to study protein-protein interactions. Many of these techniques are now available to the nonspecialist researcher thanks to new affordable instruments and/or resource centres. A typical protein-protein interaction study usually starts with an initial screen for novel binding partners. We start this review by describing three techniques that can be used for this purpose: (i) affinity-tagged proteins (ii) the two-hybrid system and (iii) some quantitative proteomic techniques that can be used in combination with, e.g., affinity chromatography and coimmunoprecipitation for screening of protein-protein interactions. We then describe some public protein-protein interaction databases that can be searched to identify previously reported interactions for a given bait protein. Four strategies for validation of protein-protein interactions are presented: confocal microscopy for intracellular colocalization of proteins, coimmunoprecipitation, surface plasmon resonance (SPR) and spectroscopic studies. Throughout the review we focus particularly on the advantages and limitations of each method.     

用于蛋白质间相互作用研究的新型双杂交系统

近年来,一些不依赖于转录因子活性的新型双杂交系统相继建立,如分离的泛素系统、蛋白质片段互补分析、阻遏物重构分析和SOS恢复系统等。同利用转录因子活性的酵母双杂交系统相似,这些方法也利用了一些活性蛋白的结构与功能特点来研究蛋白质间相互作用,这些活性蛋白不是转录因子,但也可在结构上进行分离可通过重构使其生物活性得以恢复。由于这些新型双杂交系统的各自特点,使得它们成为酵母双杂交系统的有益补充和研究蛋白质间相互作用的有力工具。     

In vitro protein microarrays for detecting protein-protein interactions: application of a new method for fluorescence labeling of proteins

Protein microarrays or proteome chips are potentially powerful tools for comprehensive analysis of protein-protein interactions. In interaction analysis, a set of immobilized proteins is arrayed on slides and each slide is probed with a set of fluorescently labeled proteins. Here we have developed and tested an in vitro protein microarray, in which both arraying and probing proteins were prepared by cell-free translation. The in vitro synthesis of fluorescently labeled proteins was accomplished by a new method: a fluorophore-puromycin conjugate was incorporated into a protein at the C-terminus on the ribosome. The resulting fluorescently labeled proteins were confirmed to be useful for probing protein-protein interactions on protein microarrays in model experiments. Since the in vitro protein microarrays can easily be extended to a high-throughput format and also combined with in vitro display technologies such as the streptavidin-biotin linkage in emulsions method (Doi and Yanagawa, FEBS Lett. 1999, 457, 227-230), our method should be useful for large-scale analysis of protein-protein interactions.     

Detection of transient protein-protein interactions by bimolecular fluorescence complementation: the Abl-SH3 case

Protein-protein interactions are essential in most biological processes. Many proteomic approaches have succeeded in the identification of strong and obligatory interactions but the study of weak and transient protein-protein interactions is still a challenge. The aim of the present study was to test the ability of bimolecular fluorescence complementation to detect and discriminate in vivo weak intracellular protein interactions. As a test case, the interaction of the SH3 domain from the c-Abl tyrosine kinase with both natural and designed targets has been chosen. The reassociation of functional yellow fluorescent protein (YFP) from its fragments requires previous binding between the SH3 domain and its partners; but once this occurs, the complex is trapped, turning transient SH3 interactions into stable, easily detectable ones. The method is very sensitive and can be implemented for proteomic analysis of weak protein interactions using flow cytometry. The fluorescence emission is dependent on the strength of the interaction, in such a way that it can be used, at least qualitatively, to screen for best binding candidates among similar proline-rich peptides. In addition, it is illustrated how this method can be used to gain structural insights into particular c-Abl SH3 interactions.     

Wrapping mimicking in drug-like small molecules disruptive of protein-protein interfaces

The discovery of small-molecule drugs aimed at disrupting protein-protein associations is expected to lead to promising therapeutic strategies. The small molecule binds to the target protein thus replacing its natural protein partner. Noteworthy, structural analysis of complexes between successful disruptive small molecules and their target proteins has suggested the possibility that such ligands might somehow mimic the binding behavior of the protein they replace. In these cases, the molecules show a spatial and "chemical" (i.e., hydrophobicity) similarity with the residues of the partner protein involved in the protein-protein complex interface. However, other disruptive small molecules do not seem to show such spatial and chemical correspondence with the replaced protein. In turn, recent progress in the understanding of protein-protein interactions and binding hot spots has revealed the main role of intermolecular wrapping interactions: three-body cooperative correlations in which nonpolar groups in the partner protein promote dehydration of a two-body electrostatic interaction of the other protein. Hence, in the present work, we study some successful complexes between already discovered small disruptive drug-like molecules and their target proteins already reported in the literature and we compare them with the complexes between such proteins and their natural protein partners. Our results show that the small molecules do in fact mimic to a great extent the wrapping behavior of the protein they replace. Thus, by revealing the replacement the small molecule performs of relevant wrapping interactions, we convey precise physical meaning to the mimicking concept, a knowledge that might be exploited in future drug-design endeavors.     

Designing specific protein-protein interactions using computation, experimental library screening, or integrated methods

Given the importance of protein-protein interactions for nearly all biological processes, the design of protein affinity reagents for use in research, diagnosis or therapy is an important endeavor. Engineered proteins would ideally have high specificities for their intended targets, but achieving interaction specificity by design can be challenging. There are two major approaches to protein design or redesign. Most commonly, proteins and peptides are engineered using experimental library screening and/or in vitro evolution. An alternative approach involves using protein structure and computational modeling to rationally choose sequences predicted to have desirable properties. Computational design has successfully produced novel proteins with enhanced stability, desired interactions and enzymatic function. Here we review the strengths and limitations of experimental library screening and computational structure-based design, giving examples where these methods have been applied to designing protein interaction specificity. We highlight recent studies that demonstrate strategies for combining computational modeling with library screening. The computational methods provide focused libraries predicted to be enriched in sequences with the properties of interest. Such integrated approaches represent a promising way to increase the efficiency of protein design and to engineer complex functionality such as interaction specificity.     

Protein-protein interactions in concentrated electrolyte solutions

Protein-protein interactions were measured for ovalbumin and for lysozyme in aqueous salt solutions. Protein-protein interactions are correlated with a proposed potential of mean force equal to the free energy to desolvate the protein surface that is made inaccessible to the solvent due to the protein-protein interaction. This energy is calculated from the surface free energy of the protein that is determined from protein-salt preferential-interaction parameter measurements. In classical salting-out behavior, the protein-salt preferential interaction is unfavorable. Because addition of salt raises the surface free energy of the protein according to the surface-tension increment of the salt, protein-protein attraction increases, leading to a reduction in solubility. When the surface chemistry of proteins is altered by binding of a specific ion, salting-in is observed when the interactions between (kosmotrope) ion-protein complexes are more repulsive than those between the uncomplexed proteins. However, salting-out is observed when interactions between (chaotrope) ion-protein complexes are more attractive than those of the uncomplexed proteins.