Dynamics of lysozyme structure network: probing the process of unfolding

Network and atomistic simulations unveil the structural determinants of mutations linked to retinal diseases

A number of incurable retinal diseases causing vision impairments derive from alterations in visual phototransduction. Unraveling the structural determinants of even monogenic retinal diseases would require network-centered approaches combined with atomistic simulations. The transducin G38D mutant associated with the Nougaret Congenital Night Blindness (NCNB) was thoroughly investigated by both mathematical modeling of visual phototransduction and atomistic simulations on the major targets of the mutational effect. Mathematical modeling, in line with electrophysiological recordings, indicates reduction of phosphodiesterase 6 (PDE) recognition and activation as the main determinants of the pathological phenotype. Sub-microsecond molecular dynamics (MD) simulations coupled with Functional Mode Analysis improve the resolution of information, showing that such impairment is likely due to disruption of the PDEγ binding cavity in transducin. Protein Structure Network analyses additionally suggest that the observed slight reduction of theRGS9-catalyzed GTPase activity of transducin depends on perturbed communication between RGS9 and GTP binding site. These findings provide insights into the structural fundamentals of abnormal functioning of visual phototransduction caused by a missense mutation in one component of the signaling network. This combination of network-centered modeling with atomistic simulations represents a paradigm for future studies aimed at thoroughly deciphering the structural determinants of genetic retinal diseases. Analogous approaches are suitable to unveil the mechanism of information transfer in any signaling network either in physiological or pathological conditions.

A Mixed Protein Structure Network and Elastic Network Model Approach to Predict the Structural Communication in Biomolecular Systems: The PDZ2 Domain from Tyrosine Phosphatase 1E As a Case Study

Graph theory is being increasingly used to study the structural communication in biomolecular systems. This requires incorporating information on the system's dynamics, which is time-consuming and not suitable for high-throughput investigations. We propose a mixed Protein Structure Network (PSN) and Elastic Network Model (ENM)-based strategy, i.e., PSN-ENM, for fast investigation of allosterism in biological systems. PSN analysis and ENM-Normal Mode Analysis (ENM-NMA) are implemented in the structural analysis software Wordom, freely available at http://wordom.sourceforge.net/ . The method performs a systematic search of the shortest communication pathways that traverse a protein structure. A number of strategies to compare the structure networks of a protein in different functional states and to get a global picture of communication pathways are presented as well. The approach was validated on the PDZ2 domain from tyrosine phosphatase 1E (PTP1E) in its free (APO) and peptide-bound states. PDZ domains are, indeed, the systems whose structural communication and allosteric features are best characterized both in vitro and in silico. The agreement between predictions by the PSN-ENM method and in vitro evidence is remarkable and comparable to or higher than that reached by more time-consuming computational approaches tested on the same biological system. Finally, the PSN-ENM method was able to reproduce the salient communication features of unbound and bound PTP1E inferred from molecular dynamics simulations. High speed makes this method suitable for high throughput investigation of the communication pathways in large sets of biomolecular systems in different functional states.

Light on the structural communication in Ras GTPases

The graph theory was combined with fluctuation dynamics to investigate the structural communication in four small G proteins, Arf1, H-Ras, RhoA, and Sec4. The topology of small GTPases is such that it requires the presence of the nucleotide to acquire a persistent structural network. The majority of communication paths involves the nucleotide and does not exist in the unbound forms. The latter are almost devoid of high-frequency paths. Thus, small Ras GTPases acquire the ability to transfer signals in the presence of nucleotide, suggesting that it modifies the intrinsic dynamics of the protein through the establishment of regions of hyperlinked nodes with high occurrence of correlated motions. The analysis of communication paths in the inactive (S(GDP)) and active (S(GTP)) states of the four G proteins strengthened the separation of the Ras-like domain into two dynamically distinct lobes, i.e. lobes 1 and 2, representing, respectively, the N-terminal and C-terminal halves of the domain. In the framework of this separation, interfunctional states and interfamily differences could be inferred. The structure network undergoes a reshaping depending on the bound nucleotide. Nucleotide-dependent divergences in structural communication reach the maximum in Arf1 and the minimum in RhoA. In Arf1, the nucleotide-dependent paths essentially express a communication between the G box 4 (G4) and distal portions of lobe 1. In the S(GDP) state, the G4 communicates with the N-term, while, in the S(GTP) state, the G4 communicates with the switch II. Clear differences could be also found between Arf1 and the other three G proteins. In Arf1, the nucleotide tends to communicate with distal portions of lobe 1, whereas in H-Ras, RhoA, and Sec4 it tends to communicate with a cluster of aromatic/hydrophobic amino acids in lobe 2. These differences may be linked, at least in part, to the divergent membrane anchoring modes that would involve the N-term for the Arf family and the C-term for the Rab/Ras/Rho families.

Role of long- and short-range hydrophobic, hydrophilic and charged residues contact network in protein's structural organization

Background

The three-dimensional structure of a protein can be described as a graph where nodes represent residues and the strength of non-covalent interactions between them are edges. These protein contact networks can be separated into long and short-range interactions networks depending on the positions of amino acids in primary structure. Long-range interactions play a distinct role in determining the tertiary structure of a protein while short-range interactions could largely contribute to the secondary structure formations. In addition, physico chemical properties and the linear arrangement of amino acids of the primary structure of a protein determines its three dimensional structure. Here, we present an extensive analysis of protein contact subnetworks based on the London van der Waals interactions of amino acids at different length scales. We further subdivided those networks in hydrophobic, hydrophilic and charged residues networks and have tried to correlate their influence in the overall topology and organization of a protein.

Results

The largest connected component (LCC) of long (LRN)-, short (SRN)- and all-range (ARN) networks within proteins exhibit a transition behaviour when plotted against different interaction strengths of edges among amino acid nodes. While short-range networks having chain like structures exhibit highly cooperative transition; long- and all-range networks, which are more similar to each other, have non-chain like structures and show less cooperativity. Further, the hydrophobic residues subnetworks in long- and all-range networks have similar transition behaviours with all residues all-range networks, but the hydrophilic and charged residues networks don’t. While the nature of transitions of LCC’s sizes is same in SRNs for thermophiles and mesophiles, there exists a clear difference in LRNs. The presence of larger size of interconnected long-range interactions in thermophiles than mesophiles, even at higher interaction strength between amino acids, give extra stability to the tertiary structure of the thermophiles. All the subnetworks at different length scales (ARNs, LRNs and SRNs) show assortativity mixing property of their participating amino acids. While there exists a significant higher percentage of hydrophobic subclusters over others in ARNs and LRNs; we do not find the assortative mixing behaviour of any the subclusters in SRNs. The clustering coefficient of hydrophobic subclusters in long-range network is the highest among types of subnetworks. There exist highly cliquish hydrophobic nodes followed by charged nodes in LRNs and ARNs; on the other hand, we observe the highest dominance of charged residues cliques in short-range networks. Studies on the perimeter of the cliques also show higher occurrences of hydrophobic and charged residues’ cliques.

Conclusions

The simple framework of protein contact networks and their subnetworks based on London van der Waals force is able to capture several known properties of protein structure as well as can unravel several new features. The thermophiles do not only have the higher number of long-range interactions; they also have larger cluster of connected residues at higher interaction strengths among amino acids, than their mesophilic counterparts. It can reestablish the significant role of long-range hydrophobic clusters in protein folding and stabilization; at the same time, it shed light on the higher communication ability of hydrophobic subnetworks over the others. The results give an indication of the controlling role of hydrophobic subclusters in determining protein’s folding rate. The occurrences of higher perimeters of hydrophobic and charged cliques imply the role of charged residues as well as hydrophobic residues in stabilizing the distant part of primary structure of a protein through London van der Waals interaction.

Allosteric communication in cysteinyl tRNA synthetase: a network of direct and indirect readout

Protein structure networks are constructed for the identification of long-range signaling pathways in cysteinyl tRNA synthetase (CysRS). Molecular dynamics simulation trajectory of CysRS-ligand complexes were used to determine conformational ensembles in order to gain insight into the allosteric signaling paths. Communication paths between the anticodon binding region and the aminoacylation region have been identified. Extensive interaction between the helix bundle domain and the anticodon binding domain, resulting in structural rigidity in the presence of tRNA, has been detected. Based on the predicted model, six residues along the communication paths have been examined by mutations (single and double) and shown to mediate a coordinated coupling between anticodon recognition and activation of amino acid at the active site. This study on CysRS clearly shows that specific key residues, which are involved in communication between distal sites in allosteric proteins but may be elusive in direct structure analysis, can be identified from dynamics of protein structure networks.

A molecular dynamics study of the interprotein interactions in collagen fibrils

Molecular dynamics simulations of collagen are used to investigate at the atomistic level the nature of the interprotein interactions that are present within a collagen fibril, and which are responsible for the fibril's thermodynamic stability. Simulations both of a collagen fibril and of a fully solvated tropcollagen are compared in order to study the interactions that arise between the proteins upon the process of fibrillogenesis. The interactions studied include direct interprotein hydrogen bonds, water-mediated interprotein hydrogen bonds, and hydrophobic interactions. The simulations are used to quantify the number of interprotein interactions that form; to study which functional groups contribute most towards the interactions; and to study the spatial distribution of interprotein interactions throughout the fibril's D period. The processes of collagen fibrillogenesis and protein folding are then compared with each other, because these two physical processes share many similarities in concept, and the latter has been more widely studied. Molecular dynamics simulations of a bacteriophage T4 lysozyme protein, both in its native state and in and unfolded state, are used as an illustrative example of a typical protein folding process, for direct comparison with the collagen simulations.

Study on the interactions between ginsenosides and lysozyme under acidic condition by ESI-MS and molecular docking

In order to study the different effects of ginsenosides with similar structures, research on interactions between ginsenoside Rg1, Re and lysozyme was carried out by electrospray ionization mass spectrometry (ESI-MS) and molecular docking. The 1:1 and 2:1 noncovalent complexes of ginsenosides and lysozyme were observed in the mass spectra and the dissociation constants for them were directly calculated based on peak intensities of lysozyme and its noncovalent complexes with ginsenosides. The results showed that the 1:1 complex of ginsenoside Rg1 and lysozyme was more stable than that of ginsenoside Re and lysozyme. As the acidity increased, the stabilities of the 1:1 complexes of Rg1, Re and lysozyme both decreased. Interestingly, as the acidity increased, the stability of the 2:1 complex of Rg1 and lysozyme increased while that of Re decreased. From the result of molecular docking, ginsenosides interacted with the active sites of lysozyme. And the stability of the complexes could be affected by the conformation changes of lysozyme as acidity increased.

A topological description of hubs in amino Acid interaction networks

We represent proteins by amino acid interaction networks. This is a graph whose vertices are the proteins amino acids and whose edges are the interactions between them. Once we have compared this type of graphs to the general model of scale-free networks, we analyze the existence of nodes which highly interact, the hubs. We describe these nodes taking into account their position in the primary structure to study their apparition frequency in the folded proteins. Finally, we observe that their interaction level is a consequence of the general rules which govern the folding process.

Structure and activity of lysozyme on binding to ZnO nanoparticles

The interaction between ZnO nanoparticles (NPs) and lysozyme has been studied using calorimetric as well as spectrophotometric techniques, and interpreted in terms of the three-dimensional structure. The circular dichroism spectroscopic data show an increase in alpha-helical content on interaction with ZnO NPs. Glutaraldehyde cross-linking studies indicate that the monomeric form occurs to a greater extent than the dimer when lysozyme is conjugated with ZnO NPs. The enthalpy-driven binding between lysozyme and ZnO possibly involves the region encompassing the active site in the molecule, which is also the site for the dimer formation in a homologous structure. The enzyme retains high fraction of its native structure with negligible effect on its activity upon attachment to NPs. Compared to the free protein, lysozyme-ZnO conjugates are more stable in the presence of chaotropic agents (guanidine hydrochloride and urea) and also at elevated temperatures. The possible site of binding of NP to lysozyme has been proposed to explain these observations. The stability and the retention of a higher level of activity in the presence of the denaturing agent of the NP-conjugated protein may find useful applications in biotechnology ranging from diagnostic to drug delivery.

Comparative analysis of thermophilic and mesophilic proteins using Protein Energy Networks

Background

Thermophilic proteins sustain themselves and function at higher temperatures. Despite their structural and functional similarities with their mesophilic homologues, they show enhanced stability. Various comparative studies at genomic, protein sequence and structure levels, and experimental works highlight the different factors and dominant interacting forces contributing to this increased stability.

Methods

In this comparative structure based study, we have used interaction energies between amino acids, to generate structure networks called as Protein Energy Networks (PENs). These PENs are used to compute network, sub-graph, and node specific parameters. These parameters are then compared between the thermophile-mesophile homologues.

Results

The results show an increased number of clusters and low energy cliques in thermophiles as the main contributing factors for their enhanced stability. Further more, we see an increase in the number of hubs in thermophiles. We also observe no community of electrostatic cliques forming in PENs.

Conclusion

In this study we were able to take an energy based network approach, to identify the factors responsible for enhanced stability of thermophiles, by comparative analysis. We were able to point out that the sub-graph parameters are the prominent contributing factors. The thermophiles have a better-packed hydrophobic core. We have also discussed how thermophiles, although increasing stability through higher connectivity retains conformational flexibility, from a cliques and communities perspective.

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.

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.