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Published online before print August 1, 2006, 10.1110/ps.062249106
Protein Science (2006), 15:2120-2128. Published by Cold Spring Harbor Laboratory Press. Copyright © 2006 The Protein Society
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Residue centrality, functionally important residues, and active site shape: Analysis of enzyme and non-enzyme families

Antonio del Sol1, Hirotomo Fujihashi1, Dolors Amoros1 and Ruth Nussinov2,3

1 Bioinformatics Research Unit, Research and Development Division, Fujirebio, Inc., Hachioji-shi, Tokyo 192-0031, Japan
2 Basic Research Program, SAIC-Frederick, Inc., Center for Cancer Research Nanobiology Program, National Cancer Institute, Frederick, Maryland 21702, USA
3 Sackler Institute of Molecular Medicine, Department of Human Genetics and Molecular Medicine, Tel Aviv University, Tel Aviv 69978, Israel

(RECEIVED March 28, 2006; FINAL REVISION May 19, 2006; ACCEPTED May 24, 2006)


   Abstract
TOP
 Abstract
Introduction
 Results
 Discussion
 Materials and methods
 References
 
The representation of protein structures as small-world networks facilitates the search for topological determinants, which may relate to functionally important residues. Here, we aimed to investigate the performance of residue centrality, viewed as a family fold characteristic, in identifying functionally important residues in protein families. Our study is based on 46 families, including 29 enzyme and 17 non-enzyme families. A total of 80% of these central positions corresponded to active site residues or residues in direct contact with these sites. For enzyme families, this percentage increased to 91%, while for non-enzyme families the percentage decreased substantially to 48%. A total of 70% of these central positions are located in catalytic sites in the enzyme families, 64% are in hetero-atom binding sites in those families binding hetero-atoms, and only 16% belong to protein–protein interfaces in families with protein–protein interaction data. These differences reflect the active site shape: enzyme active sites locate in surface clefts, hetero-atom binding residues are in deep cavities, while protein–protein interactions involve a more planar configuration. On the other hand, not all surface cavities or clefts are comprised of central residues. Thus, closeness centrality identifies functionally important residues in enzymes. While here we focus on binding sites, we expect to identify key residues for the integration and transmission of the information to the rest of the protein, reflecting the relationship between fold and function. Residue centrality is more conserved than the protein sequence, emphasizing the robustness of protein structures.

Keywords: network; closeness centrality; characteristic path length; conserved central positions; active sites


   Introduction
TOP
 Abstract
 Introduction
Results
 Discussion
 Materials and methods
 References
 
Protein structures can be represented as small-world networks, where the amino acids are the vertices and their interactions are the edges. This type of network is usually highly clustered and is characterized by the presence of a small number of central vertices connecting any pair of nodes (Watts and Strogatz 1998; Jeong et al. 2001; Greene and Higman 2003). Consequently, a relatively small number of amino acids can be considered as central for the interconnections between all residues in the structure. Indeed, if we think of protein structures as information processing networks, it would be reasonable to assume that central residues in protein structures should play an important role in the transmission of the information in a physical (or chemical) form between all pairs of amino acids. These central residues have been associated with key amino acids in protein folding (Dokholyan et al. 2002; Vendruscolo et al. 2002; Atilgan et al. 2004), hot spots of binding-free energy in different protein complexes (del Sol and O'Meara 2004; del Sol et al. 2005), and active site residues in families of enzymes (Amitai et al. 2004).

The identification of functionally important residues in proteins remains a difficult task. Different methods of combining sequence evolutionary considerations with structural information have been proposed and have successfully predicted active sites in various proteins (Lichtarge et al. 1996; Aloy et al. 2001; Landgraf et al. 2001; Ondrechen et al. 2001; del Sol Mesa et al. 2003). However, new approaches to predict active site residues are still needed, especially for those proteins with known structure and with nonexisting sequence homologs in the databases. Considering a link between protein fold and function, it is interesting to continue exploring the functional information embodied in the topology of the structure.

Recently, Amitai et al. (2004) showed that for a large set of enzymes, active site residues have high centrality values. This result suggested that residue centrality, as an inherent characteristic of the fold, may be evolutionarily maintained to guarantee protein function. Indeed, experimental studies have shown that mutations of most of the residues have little functional effect, while perturbation of a few residues, which are probably centrally located in the interaction network, impairs protein function (Terwillinger et al. 1994; Reddy et al. 1998; Taverna and Goldstein 2002). This led to two questions. First, how good is the performance of residue centrality in identifying active/binding site amino acids in different non-enzyme protein families? Second, why is the origin of the correlation between residue centrality and amino acids important for the protein function? Here, we aimed to elucidate these questions considering residue centrality as a fold characteristic conserved in protein families. Our analysis relied on structural alignments of a set of 46 protein families, including enzyme and non-enzyme families. For each family, we sought to identify aligned positions, which are central in the structures of most family members (below, these residues are termed "centrally conserved positions"). These centrally conserved positions showed significant correlation with active site residues. This correlation was particularly strong for enzyme families. Different types of functional annotations were analyzed, showing that consistently, the catalytic site residues were the best correlated. On the other hand, as expected, other binding sites with flatter shapes are not correlated as well. This could imply that the performance of residue centrality in identifying active site amino acids in enzymes relates to the geometry of the active site clefts. Enzyme clefts have already been shown in a number of studies to constitute the largest ‘holes’ on the protein surface (Laskowski et al. 1996). Indeed, a detailed analysis of the location of the centrally conserved residues indicated that most tend to be clustered with functionally important amino acids situated in protein surface clefts or cavities. However, closeness centrality, as a global topological characteristic, identifies those cavities or clefts containing residues important for the protein function. This fact suggests that central residues are likely to fulfill important roles in networks' communication. The study of the PDZ domain and the HIV-1 protease families shows that some centrally conserved residues are found to be key amino acids for allosteric communications. A detailed analysis revealed that residue centrality is more conserved than sequence in protein families, highlighting the robustness of protein structures.


   Results
TOP
 Abstract
 Introduction
 Results
Discussion
 Materials and methods
 References
 
We compiled a data set of 46 protein families spanning a wide variety of biological functions (Table 1Go). For each family, all members were aligned based on their sequences and structures (Supplemental Material, Fig. 1). The three-dimensional structure of each family member was represented as an undirected graph, where the amino acids were taken as nodes and their interatomic contacts as edges. The concept of closeness centrality was used to characterize the residue centrality in each protein structure (see Materials and Methods). This topological characteristic was found to be well conserved across all of the family member structures (Fig. 1; Supplemental Material, Table 1Go). Residues with high closeness centrality values in a given structure either interact directly or through a few residues with all other amino acids in the structure. The centrally conserved positions were defined as those positions in the alignments with statistically highly significant closeness values (z-score ≥ 2.0) in at least 70% of the structures of the family members (Fig. 2). These cutoffs were established to guarantee a significant number of predicted centrally conserved residues (Supplemental Material, Fig. 2), allowing certain flexibility in the analysis when dealing with low-resolution or possible inaccuracies in the structures.


Figure 1
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  		Figure 1. Distribution over all protein families of the averaged correlation coefficients between the closeness z-score values for all of the aligned residues in all pairs of family members.

 


Figure 2
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  		Figure 2. Fragment of the 1dx4 protein family alignment. The closeness z-score values are shown above each residue. The z-score values >2.0 in at least 70% of the members of the family are highlighted in red. These are the centrally conserved residues.

 


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  		Table 1. Data set of the 46 protein families investigated in this study

 


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  		Table 1. Continued

 
Our goal was to analyze how well centrally conserved positions identify active site residues or their neighbors (called supportive scaffold below). Our results show that 80% of the predicted centrally conserved positions in 37 protein families (families with at least one predicted centrally conserved position) coincide or are in direct contact with experimentally annotated active sites (dubbed sensitivity below), while the fraction of the correct predictions was 63% (dubbed specificity below). These percentages increased to 91% and 68%, respectively, in the 25 enzyme families. In the 12 non-enzyme families, the percentages decreased significantly to 48% and 45%, respectively (Fig. 3; for details see Supplemental Material, Table 2). Furthermore, the sensitivity distribution of our method is shown to be more homogeneous for the enzyme families in comparison with the non-enzyme families (Supplemental Material, Fig. 3). Since our analysis was based on different proteins, the active sites included residues important for binding a variety of ligand groups such as metals, cofactors, or substrates (hereafter called "hetero-atoms"), residues involved in protein–protein interactions and catalytic site residues. Analysis of the centrally conserved positions as predictors of different functional sites revealed that in the 25 enzyme families, 70% of the predicted centrally conserved residues correspond to catalytic site residues or to those that are in direct contact with these amino acids. Similarly, for the 33 protein families binding hetero-atoms, 64% of the predicted centrally conserved residues are either directly involved in interactions with the hetero-atoms or with their neighbors. On the other hand, in the analysis of 20 protein families involved in protein–protein interactions, only 16% of the predicted centrally conserved residues belong to the interacting surface or to the neighboring residues forming the supportive scaffold (Fig. 4). As residue centrality tends to be conserved across all family members, the performance of our method in identifying active site amino acids, based on one of the family representative structures, is very similar to the analysis when considering all members (Supplemental Material, Fig. 4). In an attempt to better understand the topological explanation of our results, we analyzed a possible correlation between the residue centrality and the residue distance to the protein center of mass. Results corroborated that the more central the residue is, the closer it is to the protein center of mass (Supplemental Material, Fig. 5). Yet, our study also shows that centrally conserved residues tend to be buried in the structure, forming clusters with functionally important residues located in cavities or clefts (Supplemental Material, Table 3). This is clearly illustrated with the example of the beta-lactamase (Fig. 5). Thus, closeness centrality, as a global topological characteristic, provides more information than just a local analysis of protein cavities and clefts. Indeed, among all protein surface cavities, high closeness residues tend to be clustered around those cavities containing functionally important residues. This finding suggests that protein topology is closely related to the transmission of the information from high-centrality residues to the rest of the protein. A detailed study of the PDZ domain family identified two centrally conserved residues (Leu379 and Phe325) in contact with each other and forming the ligand-binding site (Fig. 6A). Residue Phe325 has been experimentally reported as a key amino acid for maintaining the allosteric communications between the two distantly coupled sites (Lockless and Ranganathan 1999; Ota and Agard 2005). The HIV-1 protease (Fig. 6B) is another illustrative example of the key role of central residues in long-range interactions (del Sol et al. 2006). Our network analysis identified five centrally conserved residues: Leu23, Asp25, Thr26, Ile85, and Arg87. Three of these amino acids are part of the active site: Leu23, Asp25, and Thr26 (Perryman et al. 2004). Ile85 is in contact with three important active site residues: Leu23, Asp25, and Ile84. On the other hand, Ile85 interacts with the nonactive site residues Leu24, Val64, Leu90, and Ile93, whose substitutions were reported to confer drug resistance on the HIV-1 protease (Olsen et al. 1999). Arg87 also interacts with Asp25 and Leu90. Thus, our results suggest that central amino acids are important for the interconnections between all residues in the structure. Interestingly, approximately only half of the centrally conserved residues of all families (54%) are conserved in sequence (Supplemental Material, Table 4). This fact indicates that residue centrality, as a fold topological characteristic, is more conserved than its sequence position, reflecting the robustness of protein structures.


Figure 3
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  		Figure 3. Sensitivity, specificity, true positive (TP), false positive (FP), and false negative (FN) values calculated for the centrally conserved predicted residues in all families, enzyme, and non-enzyme families.

 


Figure 4
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  		Figure 4. Percentages of conserved central positions in all protein families located in different functional sites—catalytic, heteroatom binding, and protein–protein interaction binding. Circles below the histogram represent in each case the percentage of families with at least one conserved central residue.

 


Figure 5
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  		Figure 5. (A) Representation of two views of the surface of the beta-lactamase (PDB code1bsg). The deepest cavities are depicted in yellow, blue, brown, and purple. Residues from the catalytic site, located in the yellow cavity, are shown as green and red spots. (B) Mesh representation of the same protein. Residues in cyan, red, and yellow correspond to predicted centrally conserved amino acids. The residue in red is also part of the catalytic site. The remaining catalytic site residues are shown in green. Those amino acids in cyan are neighbors of the catalytic site residues. All of these residues are clustered around the same cavity (area colored in yellow).

 


Figure 6
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  		Figure 6. (A) Representation of the PDZ domain (PDB code 1be9). The predicted centrally conserved residues, LEU379 and PHE325, are shown in red. Both amino acids are in contact with the ligand (depicted in yellow). Residue PHE325 has been experimentally determined to be energetically coupled with residue HIS372 (key residue responsible for ligand specificity) and is part of the intramolecular signaling pathway proposed by Lockless and Ranganathan (1999). The other residues forming this pathway, ALA347 and LEU353 (colored in blue), have been suggested to participate in the allosteric communications (Lockless and Ranganathan 1999) and are in direct contact with the Cdc42 binding site of the PDZ domain in the mPar-6B protein. The functional importance of this pathway has been largely confirmed by experimental mutagenesis (Ota and Agard 2005). (B) The structure of the HIV-1 protease homodimer (PDB code1kzk). Predicted central residues are shown in red.

 

   Discussion
TOP
 Abstract
 Introduction
 Results
 Discussion
Materials and methods
 References
 
The identification of active site residues solely based on the structure remains a difficult task. Different approaches relying on structural features have been proposed, identifying active sites in various proteins (Lichtarge et al. 1996; Aloy et al. 2001; Landgraf et al. 2001; Ondrechen et al. 2001). The representation of protein structures as interacting networks facilitates the analysis of topological characteristics, which can contain some information about functionally important amino acids (Greene and Higman 2003). In addition, this model permits the investigation of the role of each individual amino acid within the complex interacting network (Vendruscolo et al. 2002; del Sol and O'Meara 2004). It was further shown for a set of enzymes that active site residues tend to have high centrality values (Amitai et al. 2004). This finding supports the idea that protein structure topology holds valuable information about functionally important residues. Here, we aimed to study the generality of this result by analyzing a set of biologically different protein families, involving different functionally important sites. In our analysis, we approached residue centrality as a conserved topological characteristic in protein families.

To pursue this goal, we compiled a set of 46 protein families, including a wide variety of biological cases. Based on the family structural alignments and the closeness parameter as a measure of residue centrality, we determined the central positions associated with family folds (centrally conserved positions). A total of 80% of the centrally conserved positions in all of the analyzed families were located in active sites. These predictions were significantly better for enzymes (91%) than for non-enzyme families (48%). A more detailed analysis revealed that centrally conserved positions were much better predictors for catalytic site residues and residues binding hetero-atoms than for protein–protein binding sites. We attribute these findings to the geometrical differences of the functional sites. The shapes of the binding sites are different. Active sites in enzymes are often characterized by large clefts, and hetero-atom binding residues are located in cavities on the protein's surface. On the other hand, protein–protein interaction interfaces exhibit a range of shapes, depending on the biological case. Usually, the antibody presents a large cleft for antigen binding, while homodimers tend to have planar interfaces (Laskowski et al. 1996; Valdar and Thornton 2001; Ma et al. 2003). Indeed, our results show that many centrally conserved amino acids are clustered with active site residues in cavities or clefts. Nevertheless, we note that unlike local geometrical considerations on the protein surface, closeness centrality is a global topological characteristic reflecting the effect of all protein residues on single amino acids. It identifies those cavities or clefts comprised of functionally important residues. Thus, centrally conserved residues are assumed to integrate and propagate the information to the rest of the protein. The examples of the PDZ domain and HIV-1 protease illustrate the key role of centrally conserved amino acids in the long-range communications. Residue centrality, as a topological characteristic of the protein fold, is more conserved than the sequence in protein families. This manifests the robustness of protein structures.


   Materials and methods
TOP
 Abstract
 Introduction
 Results
 Discussion
 Materials and methods
References
 
Protein structure analysis
Using the Structural Classification of Proteins database (SCOP) (Murzin et al. 1995), we compiled a set of 46 nonredundant protein families, with all of their members having a known structure in the PDB database (Berman et al. 2000). The family alignments were generated using 3DCoffee, which is a method that combines protein sequences and structures (O'Sullivan et al. 2004). For each family, information was collected from the Catalytic Site Atlas (Torrance et al. 2005) for catalytic site residues, from the PDBsum database (Laskowski et al. 1997) for ligand and metal binding residues, and from the Biomolecular Interaction Network Database (BIND) (Bader et al. 2001) for residues involved at protein–protein interfaces. Complementary information was added using our own programs for the calculation of residues in contact with hetero-atoms. The analysis of protein cavities in protein structures was carried out using the program Speedfill, which is a modified version of the SURFNET program (Glaser et al. 2006).

Protein sequence analysis
The study of the protein sequence conservation was carried out using the ConSurf server (Glaser et al. 2003).

Graph representation of protein structures
Each protein structure was modeled as an undirected graph, where amino acid residues corresponded to vertices, and contacts between them were represented as edges. Residues i and j were considered to be in contact if at least one atom corresponding to residue i was at a distance of ≤5.0 Å to an atom from residue j.

The closeness centrality value Ck for residue k is defined as

Formula

where d(i,k) is the shortest path distance between residues i and k, and n is the total number of residues.

Statistical Analysis
The statistically significant central residues were evaluated using the z-score values of the residue closeness centrality, defined as

Formula

where Ck is the closeness centrality of residue k, Formula is the closeness centrality average value over all protein residues, and {sigma} is the corresponding standard deviation.

The sensitivity and specificity of our method were defined as

Formula

Formula

where TP and TN are the number of true positives and true negatives, respectively. Npred is the total number of predicted centrally conserved residues, and Nres is the total number of residues. These variables were calculated based on all the protein families.


   Footnotes
 
Supplemental material: see www.proteinscience.org

Reprint requests to: Antonio del Sol, Bioinformatics Research Unit, Research and Development Division, Fujirebio, Inc., 51 Komiya cho, Hachioji-shi, Tokyo 192-0031, Japan; e-mail: ao-mesa@fujirebio.co.jp; fax: 81-426-46-8325.

Article published online ahead of print. Article and publication date are at http://www.proteinscience.org/cgi/doi/10.1110/ps.062249106.


   Acknowledgments
 
This project has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, under contract number NO1-CO-12400. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government. This research was supported (in part) by the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research.


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