Geometric cooperativity and anticooperativity of three-body interactions in native proteins

Characterizing multibody interactions of hydrophobic, polar, and ionizable residues in protein is important for understanding the stability of protein structures. We introduce a geometric model for quantifying 3-body interactions in native proteins. With this model, empirical propensity values for many types of 3-body interactions can be reliably estimated from a database of native protein structures, despite the overwhelming presence of pairwise contacts. In addition, we define a nonadditive coefficient that characterizes cooperativity and anticooperativity of residue interactions in native proteins by measuring the deviation of 3-body interactions from 3 independent pairwise interactions. It compares the 3-body propensity value from what would be expected if only pairwise interactions were considered, and highlights the distinction of propensity and cooperativity of 3-body interaction. Based on the geometric model, and what can be inferred from statistical analysis of such a model, we find that hydrophobic interactions and hydrogen-bonding interactions make nonadditive contributions to protein stability, but the nonadditive nature depends on whether such interactions are located in the protein interior or on the protein surface. When located in the interior, many hydrophobic interactions such as those involving alkyl residues are anticooperative. Salt-bridge and regular hydrogen-bonding interactions, such as those involving ionizable residues and polar residues, are cooperative. When located on the protein surface, these salt-bridge and regular hydrogen-bonding interactions are anticooperative, and hydrophobic interactions involving alkyl residues become cooperative. We show with examples that incorporating 3-body interactions improves discrimination of protein native structures against decoy conformations. In addition, analysis of cooperative 3-body interaction may reveal spatial motifs that can suggest specific protein functions.     

Interaction energy based protein structure networks

The three-dimensional structure of a protein is formed and maintained by the noncovalent interactions among the amino-acid residues of the polypeptide chain. These interactions can be represented collectively in the form of a network. So far, such networks have been investigated by considering the connections based on distances between the amino-acid residues. Here we present a method of constructing the structure network based on interaction energies among the amino-acid residues in the protein. We have investigated the properties of such protein energy-based networks (PENs) and have shown correlations to protein structural features such as the clusters of residues involved in stability, formation of secondary and super-secondary structural units. Further we demonstrate that the analysis of PENs in terms of parameters such as hubs and shortest paths can provide a variety of biologically important information, such as the residues crucial for stabilizing the folded units and the paths of communication between distal residues in the protein. Finally, the energy regimes for different levels of stabilization in the protein structure have clearly emerged from the PEN analysis.     

Clustering of non-polar contacts in proteins.

MOTIVATION: Hydrophobic or non-polar contacts in proteins are important for protein folding, protein stability and protein-protein interactions. In particular, in the interior of a protein, in the hydrophobic core, a large number of such contacts are found. The residues involved in these contacts often form a tightly packed cluster of atoms. It is useful for the understanding of protein structure to be able to identify and analyse such clusters. RESULTS: Tools for hierarchical cluster analysis of non-polar contacts in proteins are described. These tools allow for efficient identification of clusters of non-polar interactions in proteins, both internal clusters and clusters involved in protein-protein contacts. The non-polar contacts are represented by a dendrogram structure, which is a simple approach for flexible identification of clusters by visual inspection. The tools are demonstrated on the structure of crambin, the structure of the complex between human growth hormone and the human growth hormone binding protein, and a pair of lipase/esterase structures. Availability: On request from the author.     

Structural analysis of cation-pi interactions in DNA binding proteins

Cation-pi interactions play an important role in the stability of protein structures. In this work, we have analyzed the influence of cation-pi interactions in DNA binding proteins. We observed cation-pi interactions in 45 out of 62 DNA binding proteins and there is no significant correlation between the number of amino acid residues and number of cation-pi interactions. These interactions are mainly formed by long-range contacts, and the role of short and medium-range contacts is minimal. The preference of Arg is higher than Lys to form cation-pi interactions. The pair-wise cation-pi interaction energy between aromatic and positively charged residues shows that Arg-Tyr energy is the strongest among the possible six pairs. The structural analysis of cation-pi interaction forming residues shows that Lys, Trp, and Tyr prefer to be in the binding site of protein-DNA complexes. Further, the accessible surface areas of cation-pi interaction forming cationic residues are significantly less than that of other residues. The preference of cation-pi interaction forming residues in different secondary structures shows that Lys prefers to be in strand and Phe prefers to be in turn regions. The results obtained in the present study will be useful in understanding the contribution of cation-pi interactions to the stability and specificity of protein-DNA complexes.     

Geometry of nonbonded interactions involving planar groups in proteins

Although hydrophobic interaction is the main contributing factor to the stability of the protein fold, the specificity of the folding process depends on many directional interactions. An analysis has been carried out on the geometry of interaction between planar moieties of ten side chains (Phe, Tyr, Trp, His, Arg, Pro, Asp, Glu, Asn and Gln), the aromatic residues and the sulfide planes (of Met and cystine), and the aromatic residues and the peptide planes within the protein tertiary structures available in the Protein Data Bank. The occurrence of hydrogen bonds and other nonconventional interactions such as C-H...pi, C-H...O, electrophile-nucleophile interactions involving the planar moieties has been elucidated. The specific nature of the interactions constraints many of the residue pairs to occur with a fixed sequence difference, maintaining a sequential order, when located in secondary structural elements, such as alpha-helices and beta-turns. The importance of many of these interactions (for example, aromatic residues interacting with Pro or cystine sulfur atom) is revealed by the higher degree of conservation observed for them in protein structures and binding regions. The planar residues are well represented in the active sites, and the geometry of their interactions does not deviate from the general distribution. The geometrical relationship between interacting residues provides valuable insights into the process of protein folding and would be useful for the design of protein molecules and modulation of their binding properties.     

Identification of side-chain clusters in protein structures by a graph spectral method.

This paper presents a novel method to detect side-chain clusters in protein three-dimensional structures using a graph spectral approach. Protein side-chain interactions are represented by a labeled graph in which the nodes of the graph represent the Cbeta atoms and the edges represent the distance between the Cbeta atoms. The distance information and the non-bonded connectivity of the residues are represented in the form of a matrix called the Laplacian matrix. The constructed matrix is diagonalized and clustering information is obtained from the vector components associated with the second lowest eigenvalue and cluster centers are obtained from the vector components associated with the top eigenvalues. The method uses global information for clustering and a single numeric computation is required to detect clusters of interest. The approach has been adopted here to detect a variety of side-chain clusters and identify the residue which makes the largest number of interactions among the residues forming the cluster (cluster centers). Detecting such clusters and cluster centers are important from a protein structure and folding point of view. The crucial residues which are important in the folding pathway as determined by PhiF values (which is a measure of the effect of a mutation on the stability of the transition state of folding) as obtained from protein engineering methods, can be identified from the vector components corresponding to the top eigenvalues. Expanded clusters are detected near the active and binding site of the protein, supporting the nucleation condensation hypothesis for folding. The method is also shown to detect domains in protein structures and conserved side-chain clusters in topologically similar proteins.     

Influence of cation-pi interactions in different folding types of membrane proteins

Cation-pi interactions play an important role to the stability of protein structures. In this work, we analyze the influence of cation-pi interactions in three-dimensional structures of membrane proteins. We found that transmembrane strand (TMS) proteins have more number of cation-pi interactions than transmembrane helical (TMH) proteins. In TMH proteins, both the positively charged residues Lys and Arg equally experience favorable cation-pi interactions whereas in TMS proteins, Arg is more likely than Lys to be in such interactions. There is no relationship between number of cation-pi interactions and number of residues in TMH proteins whereas a good correlation was observed in TMS proteins. The average cation-pi interaction energy for TMH proteins is -16 kcal/mol and that for TMS proteins is -27 kcal/mol. The pair-wise cation-pi interaction energy between aromatic and positively charged residues showed that Lys-Trp energy is stronger in TMS proteins than TMH proteins; Arg-Phe, Arg-Tyr and Lys-Phe have higher energy in TMH proteins than TMS proteins. The decomposition of energies into electrostatic and van der Waals revealed that the contribution from electrostatic energy is twice as that from van der Waals energy in both TMH and TMS proteins. The results obtained in the present study would be helpful to understand the contribution of cation-pi interactions to the stability of membrane proteins.     

Geometry of nonbonded interactions involving planar groups in proteins

Although hydrophobic interaction is the main contributing factor to the stability of the protein fold, the specificity of the folding process depends on many directional interactions. An analysis has been carried out on the geometry of interaction between planar moieties of ten side chains (Phe, Tyr, Trp, His, Arg, Pro, Asp, Glu, Asn and Gln), the aromatic residues and the sulfide planes (of Met and cystine), and the aromatic residues and the peptide planes within the protein tertiary structures available in the Protein Data Bank. The occurrence of hydrogen bonds and other nonconventional interactions such as C–H⋯π, C–H⋯O, electrophile–nucleophile interactions involving the planar moieties has been elucidated. The specific nature of the interactions constraints many of the residue pairs to occur with a fixed sequence difference, maintaining a sequential order, when located in secondary structural elements, such as α-helices and β-turns. The importance of many of these interactions (for example, aromatic residues interacting with Pro or cystine sulfur atom) is revealed by the higher degree of conservation observed for them in protein structures and binding regions. The planar residues are well represented in the active sites, and the geometry of their interactions does not deviate from the general distribution. The geometrical relationship between interacting residues provides valuable insights into the process of protein folding and would be useful for the design of protein molecules and modulation of their binding properties.     

Analysis of homodimeric protein interfaces by graph-spectral methods

The quaternary structures impart structural and functional credibility to proteins. In a multi-subunit protein, it is important to understand the factors that drive the association or dissociation of the subunits. It is a well known fact that both hydrophobic and charged interactions contribute to the stability of the protein interface. The interface residues are also known to be highly conserved. Though they are buried in the oligomer, these residues are either exposed or partially exposed in the monomer. It is felt that a systematic and objective method of identifying interface clusters and their analysis can significantly contribute to the identification of a residue or a collection of residues important for oligomerization. Recently, we have applied the techniques of graph-spectral methods to a variety of problems related to protein structure and folding. A major advantage of this methodology is that the problem is viewed from a global protein topology point of view rather than localized regions of the protein structure. In the present investigation, we have applied the methods of graph-spectral analysis to identify side chain clusters at the interface and the centers of these clusters in a set of homodimeric proteins. These clusters are analyzed in terms of properties such as amino acid composition, accessibility to solvent and conservation of residues. Interesting results such as participation of charged and aromatic residues like arginine, glutamic acid, histidine, phenylalanine and tyrosine, consistent with earlier investigations, have emerged from these analyses. Important additional information is that the residues involved are a part of a cluster(s) and that they are sequentially distant residues which have come closer to each other in the three-dimensional structure of the protein. These residues can easily be detected using our graph-spectral algorithm. This method has also been used to identify important residues ('hot spots') in dimerization and also to detect dimerization sites on the monomer. The residues predicted using the present algorithm have correlated well with the experiments indicating the efficacy of this method in predicting residues involved in dimer stability.     

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.     

Structural analysis of residues involving cation-pi interactions in different folding types of membrane proteins

Cation-pi interactions play an important role to the stability of protein structures. In our earlier work, we have analyzed the influence and energetic contribution of cation-pi interactions in three-dimensional structures of membrane proteins. In this work, we investigate the characteristic features of residues that are involved in cation-pi interactions. We have computed several parameters, such as surrounding hydrophobicity, number of long-range contacts, conservation score and normalized B-factor for all these residues and identified their location, whether in the membrane or at surface. We found that the cation-pi interactions are mainly formed by long-range interactions. The cationic residues involved in cation-pi interactions have higher surrounding hydrophobicity than their average values in the whole dataset and an opposite trend is observed for aromatic residues. In transmembrane helical proteins, except Phe, all other residues that are responsible for cation-pi interactions are highly conserved with other related protein sequences whereas in transmembrane strand proteins, an appreciable conservation is observed only for Arg. The analysis on the flexibility of residues reveals that the cation-pi interaction forming residues are more stable than other residues. The results obtained in the present study would be helpful to understand the role of cation-pi interactions in the structure and folding of membrane proteins.     

Aromatic clusters: a determinant of thermal stability of thermophilic proteins

A number of factors have been elucidated as responsible for the thermal stability of thermophilic proteins. However, the contribution of aromatic interactions to thermal stability has not been systematically studied. In the present investigation we used a graph spectral method to identify aromatic clusters in a dataset of 24 protein families for which the crystal structures of both the thermophilic and their mesophilic homologues are known. Our analysis shows a presence of additional aromatic clusters or enlarged aromatic networks in 17 different thermophilic protein families, which are absent in the corresponding mesophilic homologue. The additional aromatic clusters identified in the thermophiles are smaller in size and are largely found on the protein surface. The aromatic clusters are found to be relatively rigid regions of the surface and often the additional aromatic cluster is located close to the active site of the thermophilic enzyme. The residues in the additional aromatic clusters are preferably mutated to Leu, Ser or Ile in the mesophilic homologue. An analysis of the packing geometry of the pairwise aromatic interaction in the additional aromatic clusters shows a preference for a T-shaped orthogonal packing geometry. The present study also provides new insights for protein engineers to design thermostable and thermophilic proteins.     

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.     

Hydrophobic interaction network analysis for thermostabilization of a mesophilic xylanase

One widely known drawback of enzymes is their instability in diverse conditions. The thermostability of enzymes is particularly relevant for industrial applications because operation at high temperatures has the advantage of a faster reaction rate. Protein stability is mainly determined in this study by intra-molecular hydrophobic interactions that have a collective and 3-dimensional clustering effect. To interpret the thermostability of enzymes, network analysis was introduced into the protein structure, and a network parameter of structural hierarchy, k of k-clique, was used to discern more developed hydrophobic interaction clusters in the protein structure. The favorable clustering conformations of hydrophobic residues, which seemed to be important for protein thermostability, were discovered by the application of a network analysis to hydrophobic interactions of GH11 xylanases. Coordinating higher k-clique hydrophobic interaction clusters through the site-directed mutagenesis of the model enzyme, Bacillus circulans xylanase, stabilized the local structure and thus improved thermostability, such that the enzyme half-life and melting temperature increased by 78 fold and 8.8 °C, respectively. This study highlights the advantages of interpreting collective hydrophobic interaction patterns and their structural hierarchy and the possibility of applying network analysis to the thermostabilization of enzymes.     

Inter-residue and solvent-residue interactions in proteins: a statistical study on experimental structures

A large set of protein structures resolved by X-ray or NMR techniques has been extracted from the Protein Data Bank and analyzed using statistical methods. In particular, we investigate the interactions between side chains and the interactions between solvent and side chains, pointing out on the possibility of including the solvent as part of a knowledge-based potential. The solvent-residue contacts are accounted for on the basis of the Voronoi's polyhedron analysis. Our investigation confirms the importance of hydrophobic residues in determining the protein stability. We observe that in general hydrophobic-hydrophobic interactions and, more specifically, aromatic-aromatic contacts tend to be increasingly distally separated in the primary sequence of proteins, thus connecting distinct secondary structure elements. A simple relation expressing the dependence of the protein free energy by the number of residues is proposed. Such a relation includes both the residue-residue and the solvent-residue contributions. The former is dominant for large size proteins, whereas for small sizes (number of residues less than 100) the two terms are comparable. Gapless threading experiments show that the solvent-residue knowledge-based potential yields a significant contribution with respect to discriminating the native structure of proteins. Such contribution is important especially for proteins of small size and is similar to that given by the most favorable residue-residue knowledge-based potential referring to hydrophobic-hydrophobic interactions such as isoleucine-leucine. In general, the inclusion of the solvent-residue interaction produces a relevant increase of the free energy gap between the native structures and decoys.     

Interaction geometry involving planar groups in protein-protein interfaces

The geometry of interactions of planar residues is nonrandom in protein tertiary structures and gives rise to conventional, as well as nonconventional (X--H...pi, X--H...O, where X = C, N, or O) hydrogen bonds. Whether a similar geometry is maintained when the interaction is across the protein-protein interface is addressed here. The relative geometries of interactions involving planar residues, and the percentage of contacts giving rise to different types of hydrogen bonds are quite similar in protein structures and the biological interfaces formed by protein chains in homodimers and protein-protein heterocomplexes--thus pointing to the similarity of chemical interactions that occurs during protein folding and binding. However, the percentage is considerably smaller in the nonspecific and nonphysiological interfaces that are formed in crystal lattices of monomeric proteins. The C--H...O interaction linking the aromatic and the peptide groups is quite common in protein structures as well as the three types of interfaces. However, as the interfaces formed by crystal contacts are depleted in aromatic residues, the weaker hydrogen bond interactions would contribute less toward their stability.     

Structural evidence for a dominant role of nonpolar interactions in the binding of a transport/chemosensory receptor to its highly polar ligands.

The receptor, a maltose/maltooligosaccharide-binding protein, has been found to be an excellent system for the study of molecular recognition because its polar and nonpolar binding functions are segregated into two globular domains. The X-ray structures of the "closed" and "open" forms of the protein complexed with maltose and maltotetraitol have been determined. These sugars have approximately 3 times more accessible polar surface (from OH groups) than nonpolar surface (from small clusters of sugar ring CH bonds). In the closed structures, the oligosaccharides are buried in the groove between the two domains of the protein and bound by extensive hydrogen bonding interactions of the OH groups with the polar residues confined mostly in one domain and by nonpolar interactions of the CH clusters with four aromatic residues lodged in the other domain. Substantial contacts between the sugar hydroxyls and aromatic residues are also formed. In the open structures, the oligosaccharides are bound almost exclusively in the domain rich in aromatic residues. This finding, along with the analysis of buried surface area due to complex formations in the open and closed structures, supports a major role for nonpolar interactions in initial ligand binding even when the ligands have significantly greater potential for highly specific polar interactions.     

On the contribution of water-mediated interactions to protein-complex stability

Protein-water interactions have long been recognized as a major determinant of chain folding, conformational stability, binding specificity and catalysis. However, the detailed effects of water on stabilizing protein-protein interactions remain elusive. A way to test experimentally the contribution of water-mediated interactions is by applying double mutant cycle analysis on pairs of residues that do not form direct interactions, but are bridged by water. Seven such interactions within the interface between TEM1 and BLIP proteins were evaluated. No significant interaction free energy was found between either of them. Water can bridge interactions, but also stabilize the structure of the monomer. To distinguish between these, we performed a bioinformatic analysis using AQUAPROT (http://bioinfo.weizmann.ac.il/aquaprot) to determine the degree of water conservation between the bound and unbound states. 29 structures of twelve complexes and 20 related monomers were analyzed. Of the 262 water molecules located within the interfaces, 145 were conserved between the unbound and bound structures. Strikingly, all 50 buried or partially buried waters in the monomer structures were conserved at the same location in the bound structures. Thus, buried waters have an important role in stabilizing the monomer fold rather than contributing to protein-protein binding, and are not replaced by residues from the incoming protein. Taking together the experimental and bioinformatics evidence suggests that exposed waters within the interface may be good sites for protein engineering, while buried or mostly buried waters should be left unchanged.     

A two-stage classifier for identification of protein-protein interface residues

MOTIVATION: The ability to identify protein-protein interaction sites and to detect specific amino acid residues that contribute to the specificity and affinity of protein interactions has important implications for problems ranging from rational drug design to analysis of metabolic and signal transduction networks. RESULTS: We have developed a two-stage method consisting of a support vector machine (SVM) and a Bayesian classifier for predicting surface residues of a protein that participate in protein-protein interactions. This approach exploits the fact that interface residues tend to form clusters in the primary amino acid sequence. Our results show that the proposed two-stage classifier outperforms previously published sequence-based methods for predicting interface residues. We also present results obtained using the two-stage classifier on an independent test set of seven CAPRI (Critical Assessment of PRedicted Interactions) targets. The success of the predictions is validated by examining the predictions in the context of the three-dimensional structures of protein complexes.     

Aromatic-aromatic interactions in structures of proteins and protein-DNA complexes: a study based on orientation and distance

Interactions between the aromatic amino acid residues have a significant influence on the protein structures and protein-DNA complexes. These interactions individually provide little stability to the structure; however, together they contribute significantly to the conformational stability of the protein structure. In this study, we focus on the four aromatic amino acid residues and their interactions with one another and their individual interactions with the four nucleotide bases. These are analyzed in order to determine the extent to which their orientation and the number of interactions contribute to the protein and protein-DNA complex structures.