Inter-helical interactions in membrane proteins: analysis based on the local backbone geometry and the side chain interactions

The availability of a significant number of the structures of helical membrane proteins has prompted us to investigate the mode of helix-helix packing. In the present study, we have considered a dataset of alpha-helical membrane proteins representing structures solved from all the known superfamilies. We have described the geometry of all the helical residues in terms of local coordinate axis at the backbone level. Significant inter-helical interactions have been considered as contacts by weighing the number of atom-atom contacts, including all the side-chain atoms. Such a definition of local axis and the contact criterion has allowed us to investigate the inter-helical interaction in a systematic and quantitative manner. We show that a single parameter (designated as alpha), which is derived from the parameters representing the mutual orientation of local axes, is able to accurately capture the details of helix-helix interaction. The analysis has been carried out by dividing the dataset into parallel, anti-parallel, and perpendicular orientation of helices. The study indicates that a specific range of alpha value is preferred for interactions among the anti-parallel helices. Such a preference is also seen among interacting residues of parallel helices, however to a lesser extent. No such preference is seen in the case of perpendicular helices, the contacts that arise mainly due to the interaction of surface helices with the end of the trans-membrane helices. The study supports the prevailing view that the anti-parallel helices are well packed. However, the interactions between helices of parallel orientation are non-trivial. The packing in alpha-helical membrane proteins, which is systematically and rigorously investigated in this study, may prove to be useful in modeling of helical membrane proteins.

Functional correlation of bacterial LuxS with their quaternary associations: interface analysis of the structure networks

Background

The genome of a wide variety of prokaryotes contains the luxS gene homologue, which encodes for the protein S-ribosylhomocysteinelyase (LuxS). This protein is responsible for the production of the quorum sensing molecule, AI-2 and has been implicated in a variety of functions such as flagellar motility, metabolic regulation, toxin production and even in pathogenicity. A high structural similarity is present in the LuxS structures determined from a few species. In this study, we have modelled the structures from several other species and have investigated their dimer interfaces. We have attempted to correlate the interface features of LuxS with the phenotypic nature of the organisms.

Results

The protein structure networks (PSN) are constructed and graph theoretical analysis is performed on the structures obtained from X-ray crystallography and on the modelled ones. The interfaces, which are known to contain the active site, are characterized from the PSNs of these homodimeric proteins. The key features presented by the protein interfaces are investigated for the classification of the proteins in relation to their function. From our analysis, structural interface motifs are identified for each class in our dataset, which showed distinctly different pattern at the interface of LuxS for the probiotics and some extremophiles. Our analysis also reveals potential sites of mutation and geometric patterns at the interface that was not evident from conventional sequence alignment studies.

Conclusion

The structure network approach employed in this study for the analysis of dimeric interfaces in LuxS has brought out certain structural details at the side-chain interaction level, which were elusive from the conventional structure comparison methods. The results from this study provide a better understanding of the relation between the luxS gene and its functional role in the prokaryotes. This study also makes it possible to explore the potential direction towards the design of inhibitors of LuxS and thus towards a wide range of antimicrobials.

Variations in clique and community patterns in protein structures during allosteric communication: investigation of dynamically equilibrated structures of methionyl tRNA synthetase complexes

The allosteric concept has played a key role in understanding the biological functions of proteins. The rigidity or plasticity and the conformational population are the two important ideas invoked in explaining the allosteric effect. Although molecular insights have been gained from a large number of structures, a precise assessment of the ligand-induced conformational changes in proteins at different levels, ranging from gross topology to intricate details, remains a challenge. In this study, we have explored the conformational changes in the complexes of methionyl tRNA synthetase (MetRS) through novel network parameters such as cliques and communities, which identify the rigid regions in the protein structure networks (PSNs) constructed from the noncovalent interactions of amino acid side chains. MetRS belongs to the aminoacyl tRNA synthetase (aaRS) family that plays a crucial role in the translation of genetic code. These enzymes are modular with distinct domains from which extensive genetic, kinetic, and structural data are available, highlighting the role of interdomain communication. The network parameters evaluated here on the conformational ensembles of MetRS complexes, generated from molecular dynamics simulations, have enabled us to understand the interdomain communication in detail. Additionally, the characterization of conformational changes in terms of cliques and communities has also become possible, which had eluded conventional analyses. Furthermore, we find that most of the residues participating in cliques and communities are strikingly different from those that take part in long-range communication. The cliques and communities evaluated here for the first time on PSNs have beautifully captured the local geometries in detail within the framework of global topology. Here the allosteric effect is revealed at the residue level via identification of the important residues specific for structural rigidity and functional flexibility in MetRS. This ought to enhance our understanding of the functioning of aaRS in general.

Molecular mechanism of in vitro oligomerization of Dps from Mycobacterium smegmatis: mutations of the residues identified by "interface cluster" analysis

The irreversible dodecamerization of native Dps trimers from Mycobacterium smegmatis, in vitro, is known to be directly associated with the bimodal function of this protein. Hence it is important to explore this pathway at the molecular level. Two types of trimers, Trimer A (tA) and Trimer B (tB), can be derived from the dodecamer due to the inherent 3-fold symmetry of the spherical crystal structure. These derived trimers were expressed as protein structure graphs (PSGs) using the computed interaction strength among the residues. Interface clusters which were identified from PSGs allowed us to convincingly predict E146 and F47 for further mutation studies. Various single and double mutants were constructed and characterized. We were finally able to generate a single mutant F47E impaired in dodecamerization and a double mutant E146AF47E as native monomer in solution. These two observed results suggest that the two trimers are important for dodecamerization and that the residues selected are important for the structural stability of the protein in vitro.

Insights into protein-DNA interactions through structure network analysis

Protein–DNA interactions are crucial for many cellular processes. Now with the increased availability of structures of protein–DNA complexes, gaining deeper insights into the nature of protein–DNA interactions has become possible. Earlier, investigations have characterized the interface properties by considering pairwise interactions. However, the information communicated along the interfaces is rarely a pairwise phenomenon, and we feel that a global picture can be obtained by considering a protein–DNA complex as a network of noncovalently interacting systems. Furthermore, most of the earlier investigations have been carried out from the protein point of view (protein-centric), and the present network approach aims to combine both the protein-centric and the DNA-centric points of view. Part of the study involves the development of methodology to investigate protein–DNA graphs/networks with the development of key parameters. A network representation provides a holistic view of the interacting surface and has been reported here for the first time. The second part of the study involves the analyses of these graphs in terms of clusters of interacting residues and the identification of highly connected residues (hubs) along the protein–DNA interface. A predominance of deoxyribose–amino acid clusters in β-sheet proteins, distinction of the interface clusters in helix–turn–helix, and the zipper-type proteins would not have been possible by conventional pairwise interaction analysis. Additionally, we propose a potential classification scheme for a set of protein–DNA complexes on the basis of the protein–DNA interface clusters. This provides a general idea of how the proteins interact with the different components of DNA in different complexes. Thus, we believe that the present graph-based method provides a deeper insight into the analysis of the protein–DNA recognition mechanisms by throwing more light on the nature and the specificity of these interactions.

The interaction of proteins with DNA is crucial for several cellular processes. Some insights into the mode of interaction can be obtained from the analysis of the complexed structures. Conventional analyses are based on the identification of pairwise interactions. However, a collective representation of the network of interactions and the analyses of such networks provide valuable information, which is not easy to obtain from pairwise analyses. Although the protein structure networks have been described in the literature, this is the first time that a network representation of protein–DNA is described. Construction and analysis of such networks have given valuable information on protein–DNA interactions in terms of network parameters, such as clusters of interacting residues and hubs, which are highly connected residues. Furthermore, the results also represent both the protein- and the DNA-centric viewpoints, because the analysis is carried out on combined networks. The methodology developed here can lead to predictions, such as important residues responsible for stabilizing protein–DNA interactions, and will be of interest to experimentalists.

Insight into the early stages of thermal unfolding of peanut agglutinin by molecular dynamics simulations

Peanut agglutinin is a homotetrameric nonglycosylated protein. The protein has a unique open quaternary structure. Molecular dynamics simulations have been employed to follow the atomistic details of its unfolding at different temperatures. The early events of the deoligomerization of the protein have been elucidated in the present study. Simulation trajectories of the monomer as well as those of the tetramer have been compared and the tetramer is found to be substantially more stable than its monomeric counterpart. The tetramer shows retention of most of its secondary structure but considerable loss of the tertiary structure at high temperature. This observation implies the generation of a molten globule-like intermediate in the later stages of deoligomerization. The quaternary structure of the protein has weakened to a large extent, but none of the subunits are separated. In addition, the importance of the metal-binding to the stability of the protein structure has also been investigated. Binding of the metal ions not only enhances the local stability of the metal-ion binding loop, but also imparts a global stability to the overall structure. The dynamics of different interfaces vary significantly as probed through interface clusters. The differences are substantially enhanced at higher temperatures. The dynamics and the stability of the interfaces have been captured mainly by cluster analysis, which has provided detailed information on the thermal deoligomerization of the protein.

A study of communication pathways in methionyl- tRNA synthetase by molecular dynamics simulations and structure network analysis

The enzymes of the family of tRNA synthetases perform their functions with high precision by synchronously recognizing the anticodon region and the aminoacylation region, which are separated by approximately 70 A in space. This precision in function is brought about by establishing good communication paths between the two regions. We have modeled the structure of the complex consisting of Escherichia coli methionyl-tRNA synthetase (MetRS), tRNA, and the activated methionine. Molecular dynamics simulations have been performed on the modeled structure to obtain the equilibrated structure of the complex and the cross-correlations between the residues in MetRS have been evaluated. Furthermore, the network analysis on these simulated structures has been carried out to elucidate the paths of communication between the activation site and the anticodon recognition site. This study has provided the detailed paths of communication, which are consistent with experimental results. Similar studies also have been carried out on the complexes (MetRS + activated methonine) and (MetRS + tRNA) along with ligand-free native enzyme. A comparison of the paths derived from the four simulations clearly has shown that the communication path is strongly correlated and unique to the enzyme complex, which is bound to both the tRNA and the activated methionine. The details of the method of our investigation and the biological implications of the results are presented in this article. The method developed here also could be used to investigate any protein system where the function takes place through long-distance communication.

Metabolome based reaction graphs of M. tuberculosis and M. leprae: a comparative network analysis

BACKGROUND

Several types of networks, such as transcriptional, metabolic or protein-protein interaction networks of various organisms have been constructed, that have provided a variety of insights into metabolism and regulation. Here, we seek to exploit the reaction-based networks of three organisms for comparative genomics. We use concepts from spectral graph theory to systematically determine how differences in basic metabolism of organisms are reflected at the systems level and in the overall topological structures of their metabolic networks.

METHODOLOGY/PRINCIPAL FINDINGS

Metabolome-based reaction networks of Mycobacterium tuberculosis, Mycobacterium leprae and Escherichia coli have been constructed based on the KEGG LIGAND database, followed by graph spectral analysis of the network to identify hubs as well as the sub-clustering of reactions. The shortest and alternate paths in the reaction networks have also been examined. Sub-cluster profiling demonstrates that reactions of the mycolic acid pathway in mycobacteria form a tightly connected sub-cluster. Identification of hubs reveals reactions involving glutamate to be central to mycobacterial metabolism, and pyruvate to be at the centre of the E. coli metabolome. The analysis of shortest paths between reactions has revealed several paths that are shorter than well established pathways.

CONCLUSIONS

We conclude that severe downsizing of the leprae genome has not significantly altered the global structure of its reaction network but has reduced the total number of alternate paths between its reactions while keeping the shortest paths between them intact. The hubs in the mycobacterial networks that are absent in the human metabolome can be explored as potential drug targets. This work demonstrates the usefulness of constructing metabolome based networks of organisms and the feasibility of their analyses through graph spectral methods. The insights obtained from such studies provide a broad overview of the similarities and differences between organisms, taking comparative genomics studies to a higher dimension.

Protein sequence design based on the topology of the native state structure

Computational design of sequences for a given structure is generally studied by exhaustively enumerating the sequence space or by searching in such a large space, which is prohibitively expensive. However, we point out that the protein topology has a wealth of information, which can be exploited to design sequences for a chosen structure. In this paper, we present a computationally efficient method for ranking the residue sites in a given native-state structure, which enables us to design sequences for a chosen structure. The premise for the method is that the topology of the graph representing the energetically interacting neighbours in a protein plays an important role in the inverse-folding problem. While our previous work (which was also based on topology) used eigenspectral analysis of the adjacency matrix of interactions for ranking the residue sites in a given chain, here we use a simple but effective way of assigning weights to the nodes on the basis of secondary connections, along with primary connections. This indirectly accounts for the edge weight in the graph and removes degeneracy in the degree. The new scheme needs only a few multiplications and additions to compute the preferred ranking of the residue sites even for structures of real proteins of sizes of a few hundred amino acid residues. We use HP lattice model examples (for which exhaustive enumeration of sequences is practical) to validate our ranking approach in obtaining sequences of lowest energy for any H-P residue composition for a given native-state structure. Some examples of native structures of real proteins are also included. Quantitative comparison of the efficacy of the new scheme with the earlier schemes is made. The new scheme consistently performs better and with much lower computational cost. An optimization procedure is added to work with the new scheme in a few rare cases wherein the new scheme fails to provide the best sequence, an optimization procedure is added to work with the new scheme.

Structure networks of E. coli glutaminyl-tRNA synthetase: Effects of ligand binding

It is well known that proteins undergo backbone as well as side chain conformational changes upon ligand binding, which is not necessarily confined to the active site. Both the local and the global conformational changes brought out by ligand-binding have been extensively studied earlier. However, the global changes have been reported mainly at the protein backbone level. Here we present a method that explicitly takes into account the side chain interactions, yet providing a global view of the ligand-induced conformational changes. This is achieved through the analysis of Protein Structure Networks (PSN), constructed from the noncovalent side chain interactions in the protein. Here, E. coli Glutaminyl-tRNA synthetase (GlnRS) in the ligand-free and different ligand-bound states is used as a case study to assess the effect of binding of tRNA, ATP, and the amino acid Gln to GlnRS. The PSNs are constructed on the basis of the strength of noncovalent interactions existing between the side chains of amino acids. The parameters like the size of the largest cluster, edge to node ratio, and the total number of hubs are used to quantitatively assess the structure network changes. These network parameters have effectively captured the ligand-induced structural changes at a global structure network level. Hubs, the highly connected amino acids, are also identified from these networks. Specifically, we are able to characterize different types of hubs based on the comparison of structure networks of the GlnRS system. The differences in the structure networks in both the presence and the absence of the ligands are reflected in these hubs. For instance, the characterization of hubs that are present in both the ligand-free and all the ligand-bound GlnRS (the invariant hubs) might implicate their role in structural integrity. On the other hand, identification of hubs unique to a particular ligand-bound structure (the exclusive hubs) not only highlights the structural differences mediated by ligand-binding at the structure network level, but also highlights significance of these amino acids hubs in binding to the ligand and catalyzing the biochemical function. Further, the hubs identified from this study could be ideal targets for mutational studies to ascertain the ligand-induced structure-function relationships in E. coli GlnRS. The formalism used in this study is simple and can be applied to other protein-ligands in general to understand the allosteric changes mediated by the binding of ligands.

Dynamics of lysozyme structure network: probing the process of unfolding

Recently we showed that the three-dimensional structure of proteins can be investigated from a network perspective, where the amino acid residues represent the nodes in the network and the noncovalent interactions between them are considered for the edge formation. In this study, the dynamical behavior of such networks is examined by considering the example of T4 lysozyme. The equilibrium dynamics and the process of unfolding are followed by simulating the protein at 300 K and at higher temperatures (400 K and 500 K), respectively. The snapshots of the protein structure from the simulations are represented as protein structure networks in which the strength of the noncovalent interactions is considered an important criterion in the construction of edges. The profiles of the network parameters, such as the degree distribution and the size of the largest cluster (giant component), were examined as a function of interaction strength at different temperatures. Similar profiles are seen at all the temperatures. However, the critical strength of interaction (Icritical) and the size of the largest cluster at all interaction strengths shift to lower values at 500 K. Further, the folding/unfolding transition is correlated with contacts evaluated at Icritical and with the composition of the top large clusters obtained at interaction strengths greater than Icritical. Finally, the results are compared with experiments, and predictions are made about the residues, which are important for stability and folding. To summarize, the network analysis presented in this work provides insights into the details of the changes occurring in the protein tertiary structure at the level of amino acid side-chain interactions, in both the equilibrium and the unfolding simulations. The method can also be employed as a valuable tool in the analysis of molecular dynamics simulation data, since it captures the details at a global level, which may elude conventional pairwise interaction analysis.

Characterization of the backbone geometry of protein native state structures

We present a simple method for analyzing the geometry of noncovalent residue-residue interactions stabilizing the protein structure, which takes into account the constraints on the local backbone geometry. We find that the principal geometrical constraints are amino acid aspecific and are associated with hydrogen bond formation in helices and sheets. In contrast, amino acid residues in nonhelical and nonextended conformations, which make noncovalent interactions stabilizing the protein tertiary structure, display greater flexibility. We apply the method to an analysis of the packing of helices in helical bundle proteins requiring an efficient packing of amino acid side-chains of the interacting helices.

A graph spectral analysis of the structural similarity network of protein chains

We present a simple method for the analysis of large networks based on their graph spectral properties. One of the advantages of this method is that it uses a single numerical computation to identify subclusters in a connected graph, which can significantly simplify the complexity involved in analyzing large graphs. This is illustrated using a network of protein chains constructed on the basis of their structural similarities. The large-scale network properties and the cluster and subcluster organization of the protein chain network are presented. We summarize the results of structural and functional analyses of the nodes present in these clusters and elucidate the implications of structural similarity in the protein chain universe.

Identification of domains and domain interface residues in multidomain proteins from graph spectral method

We present a novel method for the identification of structural domains and domain interface residues in proteins by graph spectral method. This method converts the three-dimensional structure of the protein into a graph by using atomic coordinates from the PDB file. Domain definitions are obtained by constructing either a protein backbone graph or a protein side-chain graph. The graph is constructed based on the interactions between amino acid residues in the three-dimensional structure of the proteins. The spectral parameters of such a graph contain information regarding the domains and subdomains in the protein structure. This is based on the fact that the interactions among amino acids are higher within a domain than across domains. This is evident in the spectra of the protein backbone and the side-chain graphs, thus differentiating the structural domains from one another. Further, residues that occur at the interface of two domains can also be easily identified from the spectra. This method is simple, elegant, and robust. Moreover, a single numeric computation yields both the domain definitions and the interface residues.

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.

RESULTS

A variety of interactions such as hydrogen bond, salt bridges, aromatic and hydrophobic interactions, which occur at the interfaces are identified in a consolidated manner as amino acid clusters at the interface, from this study. Moreover, the characterization of the highly connected hub-forming residues at the interfaces and their comparison with the hubs from the non-interface regions and the non-hubs in the interface regions show that there is a predominance of charged interactions at the interfaces. Further, strong and weak interfaces are identified on the basis of the interaction strength between amino acid residues and the sizes of the interface clusters, which also show that many protein interfaces are stronger than their monomeric protein cores. The interface strengths evaluated based on the interface clusters and hubs also correlate well with experimentally determined dissociation constants for known complexes. Finally, the interface hubs identified using the present method correlate very well with experimentally determined hotspots in the interfaces of protein complexes obtained from the Alanine Scanning Energetics database (ASEdb). A few predictions of interface hot spots have also been made based on the results obtained from this analysis, which await experimental verification.

CONCLUSION

The construction and analysis of oligomeric protein structure networks and their comparison with monomeric protein structure networks provide insights into protein association. Further, the interface hubs identified using the present method can be effective targets for interface de-stabilizing mutations. We believe this analysis will significantly enhance our knowledge of the principles behind protein association and also aid in protein design.

A network representation of protein structures: implications for protein stability

This study views each protein structure as a network of noncovalent connections between amino acid side chains. Each amino acid in a protein structure is a node, and the strength of the noncovalent interactions between two amino acids is evaluated for edge determination. The protein structure graphs (PSGs) for 232 proteins have been constructed as a function of the cutoff of the amino acid interaction strength at a few carefully chosen values. Analysis of such PSGs constructed on the basis of edge weights has shown the following: 1), The PSGs exhibit a complex topological network behavior, which is dependent on the interaction cutoff chosen for PSG construction. 2), A transition is observed at a critical interaction cutoff, in all the proteins, as monitored by the size of the largest cluster (giant component) in the graph. Amazingly, this transition occurs within a narrow range of interaction cutoff for all the proteins, irrespective of the size or the fold topology. And 3), the amino acid preferences to be highly connected (hub frequency) have been evaluated as a function of the interaction cutoff. We observe that the aromatic residues along with arginine, histidine, and methionine act as strong hubs at high interaction cutoffs, whereas the hydrophobic leucine and isoleucine residues get added to these hubs at low interaction cutoffs, forming weak hubs. The hubs identified are found to play a role in bringing together different secondary structural elements in the tertiary structure of the proteins. They are also found to contribute to the additional stability of the thermophilic proteins when compared to their mesophilic counterparts and hence could be crucial for the folding and stability of the unique three-dimensional structure of proteins. Based on these results, we also predict a few residues in the thermophilic and mesophilic proteins that can be mutated to alter their thermal stability.

Correlation of the Side-Chain Hubs with the Functional Residues in DNA Binding Protein Structures

The structure networks of DNA-binding proteins have been constructed and analyzed. The detailed analysis of the networks indicates a strong relation between the positions of the residues interacting with DNA and those that form extensive interactions within the protein structure (called hubs). This study shows that the functional residues in these proteins are held in place by efficient scaffolding of the structure using side-chain interactions, thus highlighting the role of these side-chain hubs with respect to the functional residues in the protein structure.

Ab initio studies on the tri- and diphosphate fragments of adenosine triphosphate

Pyrophosphate prototypes such as methyl triphosphate and methyl diphosphate molecules in their different protonation states have been investigated at high levels of quantum chemical calculations. The optimized geometries, the thermochemistry of the hydrolysis and the molecular orbitals contributing to the high energy of these compounds have been analyzed. These investigations provide insights into the "high energy" character of ATP molecule. Further, the dependence of vibrational frequencies on the number of phosphate groups and the charged states has also been presented. These results can aid the interpretation of spectra obtained by experiments on complexes containing pyrophosphate prototypes.

Dynamics of the native and the ligand-bound structures of eosinophil cationic protein: network of hydrogen bonds at the catalytic site

Eosinophil Cationic Protein (ECP) is sequentially and structurally similar to ribonuclease A (RNase A). It belongs to the RNase A family of proteins and the RNA catalysis is essential to its biological function. In the present study, we have generated the dinucleotide-bound structures of ECP by docking the dinucleotides to a number of molecular dynamics (MD) generated ECP structures. The stability of the docked enzyme-ligand complexes was ascertained by extensive MD simulations. The modes of ligand binding are explored by essential dynamics studies. The role of water molecules in the stability of the complex and in the catalysis was investigated. The active site residues form a complex network of connections with the ligand and with a water molecule. The catalytic mechanism of the RNA cleavage is examined on the basis of the active site geometry obtained by the simulations.

Short hydrogen bonds in proteins

Short hydrogen bonds are present in many chemical and biological systems. It is well known that these short hydrogen bonds are found in the active site of enzymes and aid enzyme catalysis. This study aims to systematically characterize all short hydrogen bonds from a nonredundant dataset of protein structures. The study has revealed that short hydrogen bonds are commonly found in proteins and are widely present in different regions of the protein chain, such as the backbone or side chain, and in different secondary structural regions such as helices, strands and turns. The frequency of occurrence of donors and acceptors from the charged side chains as well as from the neutral backbone atoms is equally high. This suggests that short hydrogen bonds in proteins occur either due to increased strength or due to geometrical constraints and this has been illustrated from several examples.

Determinants of backbone packing in globular proteins: an analysis of spatial neighbours

This study attempts to examine the pattern and variability of backbone packing density in protein structures. A carefully selected non-redundant data set of known protein structures is analyzed in terms of amino-acid composition and the preference of individual amino acids to fall into regions of low, medium or high density depending on the number of observed non-sequence spatial neighbours. The relationship of the backbone packing density to a number of properties such as the hydrophobicity, non-bonded energies and secondary structural features of the amino acids are examined. The correlation between the average percentage composition and the percentage composition in regions corresponding to different levels of packing density of the proteins is evaluated. These studies are extended to the family of globins whose amino-acid sequences have diverged retaining the same three-dimensional structure during evolution. The significance of high-backbone-density regions in this family has become apparent as due to helix/helix packing. Further, the variation in the amino-acid composition in different contact regions of globin proteins follows the same pattern found for the general data set.

Determinants of quaternary association in legume lectins

It is well known that the sequence of amino acids in proteins code for its tertiary structure. It is also known that there exists a relationship between sequence and the quaternary structure of proteins. The question addressed here is whether the nature of quaternary association can be predicted from the sequence, similar to the three-dimensional structure prediction from the sequence. The class of proteins called legume lectins is an interesting model system to investigate this problem, because they have very high sequence and tertiary structure homology, with diverse forms of quaternary association. Hence, we have used legume lectins as a probe in this paper to (1) gain novel insights about the relationship between sequence and quaternary structure; (2) identify the sequence motifs that are characteristic of a given type of quaternary association; and (3) predict the quaternary association from the sequence motif.

Conformational Transitions in Eosinophil Cationic Protein: A Molecular Dynamics Study in Aqueous Environment

Extensive molecular dynamics simulations have been performed on eosinophil cationic protein (ECP). The two structures found in the crystallographic dimer (ECPA and ECPB) have been independently simulated. A small difference in the pattern of the sidechain hydrogen bonds in the starting structure has resulted in interesting differences in the conformations accessed during the simulations. In one simulation (ECPB), a stable equilibrium conformation was obtained and in the other (ECPA), conformational transitions at the level of sidechain interactions were observed. The conformational transitions exhibit the involvement of the solvent (water) molecules with a pore-like construct in the equilibrium conformation and an opening for a large number of water molecules during the transition phase. The details of these transitions are examined in terms of intra-protein hydrogen bonds, protein-water networks and the residence times of water molecules on the polar atoms of the protein. These properties show some significant differences in the region between the N-terminal helix and the loop before the C-terminal strand as a function of different conformations accessed during the simulations. However, the stable hydrogen bonds, the protein-water networks, and the hydration patterns in most part of the protein including the active site are very much similar in both the simulations, indicating the fact that these are intrinsic properties of proteins.