Evolutionarily conserved networks of residues mediate allosteric communication in proteins

A fundamental goal in cellular signaling is to understand allosteric communication, the process by which signals originating at one site in a protein propagate reliably to affect distant functional sites. The general principles of protein structure that underlie this process remain unknown. Here, we describe a sequence-based statistical method for quantitatively mapping the global network of amino acid interactions in a protein. Application of this method for three structurally and functionally distinct protein families (G protein-coupled receptors, the chymotrypsin class of serine proteases and hemoglobins) reveals a surprisingly simple architecture for amino acid interactions in each protein family: a small subset of residues forms physically connected networks that link distant functional sites in the tertiary structure. Although small in number, residues comprising the network show excellent correlation with the large body of mechanistic data available for each family. The data suggest that evolutionarily conserved sparse networks of amino acid interactions represent structural motifs for allosteric communication in proteins.     

Conservation of residue interactions in a family of Ca-binding proteins

In the TNC family of Ca-binding proteins (calmodulin, parvalbumin, intestinal calcium binding protein and troponin C) approximately 70 well-conserved amino acid sequences and six crystal structures are known. We find a clear correlation between residue contacts in the structures and residue conservation in the sequences: residues with strong sidechain-sidechain contacts in the three-dimenesional structure tend to be the more conserved in the sequence. This is one way to quantify the intuitive notion of the importance of sidechain interactions for maintaining protein three-dimensional structure in evolution and may usefully be taken into account in planning point mutations in protein engineering.     

Extent and nature of contacts between protein molecules in crystal lattices and between subunits of protein oligomers

A survey was compiled of several characteristics of the intersubunit contacts in 58 oligomeric proteins, and of the intermolecular contacts in the lattice for 223 protein crystal structures. The total number of atoms in contact and the secondary structure elements involved are similar in the two types of interfaces. Crystal contact patches are frequently smaller than patches involved in oligomer interfaces. Crystal contacts result from more numerous interactions by polar residues, compared with a tendency toward nonpolar amino acids at oligomer interfaces. Arginine is the only amino acid prominent in both types of interfaces. Potentials of mean force for residue–residue contacts at both crystal and oligomer interfaces were derived from comparison of the number of observed residue–residue interactions with the number expected by mass action. They show that hydrophobic interactions at oligomer interfaces favor aromatic amino acids and methionine over aliphatic amino acids; and that crystal contacts form in such a way as to avoid inclusion of hydrophobic interactions. They also suggest that complex salt bridges with certain amino acid compositions might be important in oligomer formation. For a protein that is recalcitrant to crystallization, substitution of lysine residues with arginine or glutamine is a recommended strategy. Proteins 28:494–514, 1997. © 1997 Wiley-Liss, Inc.     

Uncovering post-translational modification-associated protein–protein interactions

In living systems, the chemical space and functional repertoire of proteins are dramatically expanded through the post-translational modification (PTM) of various amino acid residues. These modifications frequently trigger unique protein–protein interactions (PPIs) – for example with reader proteins that directly bind the modified amino acid residue – which leads to downstream functional outcomes. The modification of a protein can also perturb its PPI network indirectly, for example, through altering its conformation or subcellular localization. Uncovering the network of unique PTM-triggered PPIs is essential to fully understand the roles of an ever-expanding list of PTMs in our biology. In this review, we discuss established strategies and current challenges associated with this endeavor.     

Comparing four different approaches for the determination of inter‐residue interactions provides insight for the structure prediction of helical membrane proteins

Studying inter‐residue interactions provides insight into the folding and stability of both soluble and membrane proteins and is essential for developing computational tools for protein structure prediction. As the first step, various approaches for elucidating such interactions within protein structures have been proposed and proven useful. Since different approaches may grasp different aspects of protein structural folds, it is of interest to systematically compare them. In this work, we applied four approaches for determining inter‐residue interactions to the analysis of three distinct structure datasets of helical membrane proteins and compared their correlation to the three individual quality measures of structures in these datasets. These datasets included one of 35 structures of rhodopsin receptors and bacterial rhodopsins determined at various resolutions, one derived from the HOMEP benchmark dataset previously reported, and one comprising of 139 homology models. It was found that the correlation between the average number of inter‐residue interactions obtained by applying the four approaches and the available structure quality measures varied quite significantly among them. The best correlation was achieved by the approach focusing exclusively on favorable inter‐residue interactions. These results provide interesting insight for the development of objective quality measure for the structure prediction of helical membrane proteins. © 2009 Wiley Periodicals, Inc. Biopolymers 91: 547–556, 2009. This article was originally published online as an accepted preprint. The “Published Online” date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at biopolymers@wiley.com     

A network model of early events in epidermal growth factor receptor signaling that accounts for combinatorial complexity

We consider a model of early events in signaling by the epidermal growth factor (EGF) receptor (EGFR). The model includes EGF, EGFR, the adapter proteins Grb2 and Shc, and the guanine nucleotide exchange factor Sos, which is activated through EGF-induced formation of EGFR-Grb2-Sos and EGFR-Shc-Grb2-Sos assemblies at the plasma membrane. The protein interactions involved in signaling can potentially generate a diversity of protein complexes and phosphoforms; however, this diversity has been largely ignored in models of EGFR signaling. Here, we develop a model that accounts more fully for potential molecular diversity by specifying rules for protein interactions and then using these rules to generate a reaction network that includes all chemical species and reactions implied by the protein interactions. We obtain a model that predicts the dynamics of 356 molecular species, which are connected through 3749 unidirectional reactions. This network model is compared with a previously developed model that includes only 18 chemical species but incorporates the same scope of protein interactions. The predictions of this model are reproduced by the network model, which also yields new predictions. For example, the network model predicts distinct temporal patterns of autophosphorylation for different tyrosine residues of EGFR. A comparison of the two models suggests experiments that could lead to mechanistic insights about competition among adapter proteins for EGFR binding sites and the role of EGFR monomers in signal transduction.     

残基相互作用网络特征与木聚糖酶耐热性的关系

残基相互作用网络是体现蛋白质中残基与残基之间协同和制约关系的重要形式。残基相互作用网络的拓扑性质以及社团结构与蛋白质的功能和性质有密切的关系。本文在构建一系列耐热木聚糖酶和常温木聚糖酶的残基相互作用网络后,通过计算网络的度、聚类系数、连接强度、特征路径长度、接近中心性、介数中心性等拓扑参数来确定网络拓扑结构与木聚糖酶耐热性的关系。识别残基相互作用网络的hub点,分析hub点的亲疏水性、带电性以及各种氨基酸在hub点中所占的比例。进一步使用GA-Net算法对网络进行社团划分,并计算社团的规模、直径和密度。网络的高平均度、高连接强度、以及更短的最短路径等表明耐热木聚糖酶残基相互作用网络的结构更加紧密;耐热木聚糖酶网络中的hub节点比常温木聚糖酶网络hub节点具有更多的疏水性残基,hub点中Phe、Ile、Val的占比更高。社团检测后发现,耐热木聚糖酶网络拥有更大的社团规模、较小的社团直径和较大的社团密度。社团规模越大表明耐热木聚糖酶的氨基酸残基更倾向于形成大的社团,而较小的社团直径和较大的社团密度则表明社团内部氨基酸残基的相互作用比常温木聚糖酶更强。     

残基相互作用网络特征与木聚糖酶耐热性的关系

残基相互作用网络是体现蛋白质中残基与残基之间协同和制约关系的重要形式。残基相互作用网络的拓扑性质以及社团结构与蛋白质的功能和性质有密切的关系。本文在构建一系列耐热木聚糖酶和常温木聚糖酶的残基相互作用网络后,通过计算网络的度、聚类系数、连接强度、特征路径长度、接近中心性、介数中心性等拓扑参数来确定网络拓扑结构与木聚糖酶耐热性的关系。识别残基相互作用网络的hub点,分析hub点的亲疏水性、带电性以及各种氨基酸在hub点中所占的比例。进一步使用GA-Net算法对网络进行社团划分,并计算社团的规模、直径和密度。网络的高平均度、高连接强度、以及更短的最短路径等表明耐热木聚糖酶残基相互作用网络的结构更加紧密;耐热木聚糖酶网络中的hub节点比常温木聚糖酶网络hub节点具有更多的疏水性残基,hub点中Phe、Ile、Val的占比更高。社团检测后发现,耐热木聚糖酶网络拥有更大的社团规模、较小的社团直径和较大的社团密度。社团规模越大表明耐热木聚糖酶的氨基酸残基更倾向于形成大的社团,而较小的社团直径和较大的社团密度则表明社团内部氨基酸残基的相互作用比常温木聚糖酶更强。     

A dissection of specific and non-specific protein-protein interfaces

We compare the geometric and physical-chemical properties of interfaces involved in specific and non-specific protein-protein interactions in crystal structures reported in the Protein Data Bank. Specific interactions are illustrated by 70 protein-protein complexes and by subunit contacts in 122 homodimeric proteins; non-specific interactions are illustrated by 188 pairs of monomeric proteins making crystal-packing contacts selected to bury more than 800 A2 of protein surface. A majority of these pairs have 2-fold symmetry and form "crystal dimers" that cannot be distinguished from real dimers on the basis of the interface size or symmetry. The chemical and amino acid compositions of the large crystal-packing interfaces resemble the protein solvent-accessible surface. These interfaces are less hydrophobic than in homodimers and contain much fewer fully buried atoms. We develop a residue propensity score and a hydrophobic interaction score to assess preferences seen in the chemical and amino acid compositions of the different types of interfaces, and we derive indexes to evaluate the atomic packing, which we find to be less compact at non-specific than at specific interfaces. We test the capacity of these parameters to identify homodimeric proteins in crystal structures, and show that a simple combination of the non-polar interface area and the fraction of buried interface atoms assigns the quaternary structure of 88% of the homodimers and 77% of the monomers in our data set correctly. These success rates increase to 93-95% when the residue propensity score of the interfaces is taken into consideration.     

Computational Modeling of Allosteric Regulation in the Hsp90 Chaperones: A Statistical Ensemble Analysis of Protein Structure Networks and Allosteric Communications

A fundamental role of the Hsp90 chaperone in regulating functional activity of diverse protein clients is essential for the integrity of signaling networks. In this work we have combined biophysical simulations of the Hsp90 crystal structures with the protein structure network analysis to characterize the statistical ensemble of allosteric interaction networks and communication pathways in the Hsp90 chaperones. We have found that principal structurally stable communities could be preserved during dynamic changes in the conformational ensemble. The dominant contribution of the inter-domain rigidity to the interaction networks has emerged as a common factor responsible for the thermodynamic stability of the active chaperone form during the ATPase cycle. Structural stability analysis using force constant profiling of the inter-residue fluctuation distances has identified a network of conserved structurally rigid residues that could serve as global mediating sites of allosteric communication. Mapping of the conformational landscape with the network centrality parameters has demonstrated that stable communities and mediating residues may act concertedly with the shifts in the conformational equilibrium and could describe the majority of functionally significant chaperone residues. The network analysis has revealed a relationship between structural stability, global centrality and functional significance of hotspot residues involved in chaperone regulation. We have found that allosteric interactions in the Hsp90 chaperone may be mediated by modules of structurally stable residues that display high betweenness in the global interaction network. The results of this study have suggested that allosteric interactions in the Hsp90 chaperone may operate via a mechanism that combines rapid and efficient communication by a single optimal pathway of structurally rigid residues and more robust signal transmission using an ensemble of suboptimal multiple communication routes. This may be a universal requirement encoded in protein structures to balance the inherent tension between resilience and efficiency of the residue interaction networks.     

Oligomeric protein structure networks: insights into protein-protein interactions

Background  

Protein-protein association is essential for a variety of cellular processes and hence a large number of investigations are being carried out to understand the principles of protein-protein interactions. In this study, oligomeric protein structures are viewed from a network perspective to obtain new insights into protein association. Structure graphs of proteins have been constructed from a non-redundant set of protein oligomer crystal structures by considering amino acid residues as nodes and the edges are based on the strength of the non-covalent interactions between the residues. The analysis of such networks has been carried out in terms of amino acid clusters and hubs (highly connected residues) with special emphasis to protein interfaces.     

Network representation of protein interactions: Theory of graph description and analysis

A methodological framework is presented for the graph theoretical interpretation of NMR data of protein interactions. The proposed analysis generalizes the idea of network representations of protein structures by expanding it to protein interactions. This approach is based on regularization of residue‐resolved NMR relaxation times and chemical shift data and subsequent construction of an adjacency matrix that represents the underlying protein interaction as a graph or network. The network nodes represent protein residues. Two nodes are connected if two residues are functionally correlated during the protein interaction event. The analysis of the resulting network enables the quantification of the importance of each amino acid of a protein for its interactions. Furthermore, the determination of the pattern of correlations between residues yields insights into the functional architecture of an interaction. This is of special interest for intrinsically disordered proteins, since the structural (three‐dimensional) architecture of these proteins and their complexes is difficult to determine. The power of the proposed methodology is demonstrated at the example of the interaction between the intrinsically disordered protein osteopontin and its natural ligand heparin.     

Structure-wise discrimination of cytosine,thymine, and uracil by proteins in terms of their nonbonded interactions

The molecular recognition and discrimination of very similar ligand moieties by proteins are important subjects in protein–ligand interaction studies. Specificity in the recognition of molecules is determined by the arrangement of protein and ligand atoms in space. The three pyrimidine bases, viz. cytosine, thymine, and uracil, are structurally similar, but the proteins that bind to them are able to discriminate them and form interactions. Since nonbonded interactions are responsible for molecular recognition processes in biological systems, our work attempts to understand some of the underlying principles of such recognition of pyrimidine molecular structures by proteins. The preferences of the amino acid residues to contact the pyrimidine bases in terms of nonbonded interactions; amino acid residue–ligand atom preferences; main chain and side chain atom contributions of amino acid residues; and solvent-accessible surface area of ligand atoms when forming complexes are analyzed. Our analysis shows that the amino acid residues, tyrosine and phenyl alanine, are highly involved in the pyrimidine interactions. Arginine prefers contacts with the cytosine base. The similarities and differences that exist between the interactions of the amino acid residues with each of the three pyrimidine base atoms in our analysis provide insights that can be exploited in designing specific inhibitors competitive to the ligands.     

The construction of an amino acid network for understanding protein structure and function

Amino acid networks (AANs) are undirected networks consisting of amino acid residues and their interactions in three-dimensional protein structures. The analysis of AANs provides novel insight into protein science, and several common amino acid network properties have revealed diverse classes of proteins. In this review, we first summarize methods for the construction and characterization of AANs. We then compare software tools for the construction and analysis of AANs. Finally, we review the application of AANs for understanding protein structure and function, including the identification of functional residues, the prediction of protein folding, analyzing protein stability and protein–protein interactions, and for understanding communication within and between proteins.     

Optimization and evaluation of a coarse-grained model of protein motion using x-ray crystal data

Simple coarse-grained models, such as the Gaussian network model, have been shown to capture some of the features of equilibrium protein dynamics. We extend this model by using atomic contacts to define residue interactions and introducing more than one interaction parameter between residues. We use B-factors from 98 ultra-high resolution (相似文献   

Accurate prediction of protein–protein interactions from sequence alignments using a Bayesian method

Accurate and large‐scale prediction of protein–protein interactions directly from amino‐acid sequences is one of the great challenges in computational biology. Here we present a new Bayesian network method that predicts interaction partners using only multiple alignments of amino‐acid sequences of interacting protein domains, without tunable parameters, and without the need for any training examples. We first apply the method to bacterial two‐component systems and comprehensively reconstruct two‐component signaling networks across all sequenced bacteria. Comparisons of our predictions with known interactions show that our method infers interaction partners genome‐wide with high accuracy. To demonstrate the general applicability of our method we show that it also accurately predicts interaction partners in a recent dataset of polyketide synthases. Analysis of the predicted genome‐wide two‐component signaling networks shows that cognates (interacting kinase/regulator pairs, which lie adjacent on the genome) and orphans (which lie isolated) form two relatively independent components of the signaling network in each genome. In addition, while most genes are predicted to have only a small number of interaction partners, we find that 10% of orphans form a separate class of ‘hub’ nodes that distribute and integrate signals to and from up to tens of different interaction partners.     

Understanding on the residue contact network using the log‐normal cluster model and the multilevel wheel diagram

Residue clusters play essential role in stabilizing protein structures in the form of complex networks. We show that the cluster sizes in a native protein follow the log‐normal distribution for a dataset consisting of 424 proteins. To our knowledge, this is the first time of such fitting for the native structures. Based on log‐normal model, the asymptotically increasing mean cluster sizes produce a critical protein chain length of about 200 amino acids, beyond which length most globular proteins have nearly the same mean cluster sizes. This suggests that the larger proteins use a different packing mechanism than the smaller proteins. We confirmed the scale‐free property of the residue contact network for most of the protein structures in the dataset, although the violations were observed for the tightly packed proteins. Residue cluster network wheel (RCNW) is proposed to visualize the relationship between the multiple properties of the residue network such as the cluster size, the residue types and contacts, and the flexibility of the residue. We noticed that the residues with large cluster size have smaller Cα displacement measured using the normal mode analysis. © 2010 Wiley Periodicals, Inc. Biopolymers 93: 904–916, 2010.     

Analysis of protein interactions within the cytokinin-signaling pathway of Arabidopsis thaliana

The signal of the plant hormone cytokinin is perceived by membrane-located sensor histidine kinases and transduced by other members of the plant two-component system. In Arabidopsis thaliana, 28 two-component system proteins (phosphotransmitters and response regulators) act downstream of three receptors, transmitting the signal from the membrane to the nucleus and modulating the cellular response. Although the principal signaling mechanism has been elucidated, redundancy in the system has made it difficult to understand which of the many components interact to control the downstream biological processes. Here, we present a large-scale interaction study comprising most members of the Arabidopsis cytokinin signaling pathway. Using the yeast two-hybrid system, we detected 42 new interactions, of which more than 90% were confirmed by in vitro coaffinity purification. There are distinct patterns of interaction between protein families, but only a few interactions between proteins of the same family. An interaction map of this signaling pathway shows the Arabidopsis histidine phosphotransfer proteins as hubs, which interact with members from all other protein families, mostly in a redundant fashion. Domain-mapping experiments revealed the interaction domains of the proteins of this pathway. Analyses of Arabidopsis histidine phosphotransfer protein 5 mutant proteins showed that the presence of the canonical phospho-accepting histidine residue is not required for the interactions. Interaction of A-type response regulators with Arabidopsis histidine phosphotransfer proteins but not with B-type response regulators suggests that their known activity in feedback regulation may be realized by interfering at the level of Arabidopsis histidine phosphotransfer protein-mediated signaling. This study contributes to our understanding of the protein interactions of the cytokinin-signaling system and provides a framework for further functional studies in planta.