Oligomeric protein structure networks: insights into protein-protein interactions

Experimental modification in thermal stability of oligomers by alanine substitution and site saturation mutagenesis of interfacial residues

For certain industrial applications, the stability of protein oligomers is important. In this study, we demonstrated an efficient method to improve the thermal stability of oligomers using the trimeric protein chloramphenicol acetyltransferase (CAT) as the model. We substituted all interfacial residues of CAT with alanine to detect residues critical for oligomer stability. Mutation of six of the forty-nine interfacial residues enhanced oligomer thermal stability. Site saturation mutagenesis was performed on these six residues to optimize the side chains. About 15% of mutations enhanced thermal stability by more than 0.5 °C and most did not disrupt activity of CAT. Certain combinations of mutations further improved thermal stability and resistance against heat treatment. The quadruple mutant, H17V/N34S/F134A/D157C, retained the same activity as the wild-type after heat treatment at 9 °C higher temperature than the wild-type CAT. Furthermore, combinations with only alanine substitutions also improved thermal stability, suggesting the method we developed can be used for rapid modification of industrially important proteins.

Designing Cyclic-Constrained Peptides to Inhibit Human Phosphoglycerate Dehydrogenase

Although loop epitopes at protein-protein binding interfaces often play key roles in mediating oligomer formation and interaction specificity, their binding sites are underexplored as drug targets owing to their high flexibility, relatively few hot spots, and solvent accessibility. Prior attempts to develop molecules that mimic loop epitopes to disrupt protein oligomers have had limited success. In this study, we used structure-based approaches to design and optimize cyclic-constrained peptides based on loop epitopes at the human phosphoglycerate dehydrogenase (PHGDH) dimer interface, which is an obligate homo-dimer with activity strongly dependent on the oligomeric state. The experimental validations showed that these cyclic peptides inhibit PHGDH activity by directly binding to the dimer interface and disrupting the obligate homo-oligomer formation. Our results demonstrate that loop epitope derived cyclic peptides with rationally designed affinity-enhancing substitutions can modulate obligate protein homo-oligomers, which can be used to design peptide inhibitors for other seemingly intractable oligomeric proteins.

M Protein from Dengue virus oligomerizes to pentameric channel protein: in silico analysis study

The Dengue virus M protein is a 75 amino acid polypeptide with two helical transmembranes (TM). The TM domain oligomerizes to form an ion channel, facilitating viral release from the host cells. The M protein has a critical role in the virus entry and life cycle, making it a potent drug target. The oligomerization of the monomeric protein was studied using ab initio modeling and molecular dynamics (MD) simulation in an implicit membrane environment. The representative structures obtained showed pentamer as the most stable oligomeric state, resembling an ion channel. Glutamic acid, threonine, serine, tryptophan, alanine, isoleucine form the pore-lining residues of the pentameric channel, conferring an overall negative charge to the channel with approximate length of 51.9 Å. Residue interaction analysis (RIN) for M protein shows that Ala94, Leu95, Ser112, Glu124, and Phe155 are the central hub residues representing the physicochemical interactions between domains. The virtual screening with 165 different ion channel inhibitors from the ion channel library shows monovalent ion channel blockers, namely lumacaftor, glipizide, gliquidone, glisoxepide, and azelnidipine to be the inhibitors with high docking scores. Understanding the three-dimensional structure of M protein will help design therapeutics and vaccines for Dengue infection.

Comparative analysis of allergenicity and predicted linear epitopes in α and β parvalbumin from turbot (Scophthalmus maximus)

BACKGROUND

Parvalbumin (PV) can be subdivided into two phylogenetic lineages, αPV and βPV. The bony fish βPV is considered a major fish allergen. However, there is no available report on the immunological property and epitope mapping of bony fish αPV.

RESULTS

To characterize the allergenic property of bony fish αPV and investigate the difference in allergenic property of bony fish αPV and βPV, turbot (Scophthalmus maximus) αPV and βPV were identified by mass spectrometry and were expressed in Escherichia coli system in this study. Spectra analysis and three-dimensional (3D) modeling showed the similar structure between αPV and βPV. However, αPV exhibited lower immunoglobulin E/immunoglobulin G (IgE/IgG) binding capacity than βPV. Three identified βPV epitopes possessed higher IgE reactivity and more hydrophobic residues than three identified αPV epitopes. In addition, less similarity in sequence homology of αPV epitopes was observed with allergen sequences in database.

CONCLUSION

These finding expanded information on fish PV epitopes and substantiated the difference in allergenicity and epitope mapping between fish αPV and βPV, which will improve the epitope-based detection tools of PV and diagnostic of PV induced fish allergy. © 2023 Society of Chemical Industry.

In silico study to predict promiscuous peptides for immunodiagnosis of cystic echinococcosis

Background

Cystic echinococcosis (CE), caused by Echinococcus granulosus, is a major zoonotic disease that causes significant human morbidity and mortality. This cosmopolitan disease is difficult to diagnose, treat, and control. So far, crude extracts of hydatid cyst fluid containing antigen B or antigen 5 have been used as the primary antigenic source for its immunodiagnosis. The main issue is that it reacts with sera from people infected with other helminths. There is currently no standard, specific, or sensitive test for disease diagnosis, and no human vaccine has been reported.

Aims and Objectives

Considering the need for efficient immunization and/or immunodiagnosis, six E. granulosus antigens, antigen 5, antigen B, heat shock proteins such as Hsp-8 and Hsp-90, phosphoenolpyruvate carboxykinase, and tetraspanin-1, were chosen.

Materials and Methods

Using various in silico tools, T cell and B cell epitopes (promiscuous peptides) were predicted by targeting antigen 5, antigen B, heat shock proteins such as Hsp-8 and Hsp-90, phosphoenolpyruvate carboxykinase, and tetraspanin-1.

Results

There are twelve promiscuous peptides with overlapping human leukocyte antigen (HLA) class-I, class-II, and conformational B cell epitopes. Such immunodominant peptides could be useful as subunit vaccines. Furthermore, six peptides specific for E. granulosus were also discovered, which may prove to be important markers in the diagnosis of CE, potentially preventing misdiagnosis and mismanagement.

Conclusion

These epitopes may be the most important vaccine targets in E. granulosus because they have the most promiscuous peptides and B cell epitopes, as well as the highest affinity for different alleles, as determined by docking scores. However, additional research using in vitro and in vivo models is undertaken.

Head or tail? A molecular dynamics approach to the complex structure of TNF-associated factor TRAF2

Tumor necrosis factor receptor-associated factor proteins (TRAFs) are trimeric proteins that play a fundamental role in signaling, acting as intermediaries between the tumor necrosis factor (TNF) receptors and the proteins that transmit the downstream signal. The monomeric subunits of all the TRAF family members share a common tridimensional structure: a C-terminal globular domain and a long coiled-coil tail characterizing the N-terminal section. In this study, the dependence of the TRAF2 dynamics on the length of its tail was analyzed in silico. In particular, we used the available crystallographic structure of a C-terminal fragment of TRAF2 (168 out of 501 a.a.), TRAF2-C, and that of a longer construct, addressed as TRAF2-plus, that we have re-constructed using the AlphaFold2 code. The results indicate that the longer N-terminal tail of TRAF2-plus has a strong influence on the dynamics of the globular regions in the protein C-terminal head. In fact, the quaternary interactions among the TRAF2-C subunits change asymmetrically in time, while the movements of TRAF2-plus monomers are rather limited and more ordered than those of the shorter construct. Such findings shed a new light on the dynamics of TRAF subunits and on the protein mechanism in vivo, since TRAF monomer-trimer equilibrium is crucial for several reasons (receptor recognition, membrane binding, hetero-oligomerization).

Identification and Amino Acid Analysis of Allergenic Epitopes of a Novel Allergen Paramyosin (Rap v 2) from Rapana venosa

Besides tropomyosin (TM) that is widely recognized as a major allergen in molluscs, a 99-kDa novel allergen (Rap v 2) was recently found in the sea snail Rapana venosa and identified as paramyosin (PM). However, the allergenic epitopes of PM in any molluscs have not been identified yet. In the present study, seven allergenic epitopes of Rap v 2 were identified by immunoinformatics tools, dot-blot inhibition assay, and basophil degranulation assay. Based on the analysis of PM and allergenic epitope amino acids, it was found that highly hydrophobic and positively charged amino acid residues play an important role in the formation of Rap v 2 epitopes. In addition, three potential critical amino acids that may account for TM and PM cross-reactivity in molluscs were found by sequence- and structure-based methods. These findings could be of major importance for improving the understanding of relevant paramyosin epitopes and the prevention and therapy of mollusc allergy.

Bcl-xL Dynamics under the Lens of Protein Structure Networks

Understanding the finely orchestrated interactions leading to or preventing programmed cell death (apoptosis) is of utmost importance in cancer research because the failure of these systems could eventually lead to the onset of the disease. In this regard, the maintenance of a delicate balance between the promoters and inhibitors of mitochondrial apoptosis is crucial, as demonstrated by the interplay among the Bcl-2 family members. In particular, B-cell lymphoma extra-large (Bcl-x_L) is a target of interest due to the forefront role of its dysfunctions in cancer development. Bcl-x_L prevents apoptosis by binding both the pro-apoptotic BH3-only proteins, like PUMA, and the noncanonical partners, such as p53, at different sites. An allosteric communication between the BH3-only protein binding pocket and the p53 binding site, mediating the release of p53 from Bcl-x_L upon PUMA binding, has been postulated and supported by nuclear magnetic resonance and other biophysical data. The molecular details of this mechanism, especially at the residue level, remain unclear. In this work, we investigated the distal communication between these two sites in Bcl-x_L in its free state and when bound to PUMA. We also evaluated how missense mutations of Bcl-x_L found in cancer samples might impair this communication and therefore the allosteric mechanism. We employed all-atom explicit solvent microsecond molecular dynamics simulations, analyzed through a Protein Structure Network approach and integrated with calculations of changes in free energies upon cancer-related mutations identified by genomics studies. We found a subset of candidate residues responsible for both maintaining protein stability and for conveying structural information between the two binding sites and hypothesized possible communication routes between specific residues at both sites.

Dynamic Community Composition Unravels Allosteric Communication in PDZ3

The third domain of PSD-95 (PDZ3) is a model for investigating allosteric communication in protein and ligand interactions. While motifs contributing to its binding specificity have been scrutinized, a conformational dynamical basis is yet to be established. Despite the miniscule structural changes due to point mutants, the observed significant binding affinity differences have previously been assessed with a focus on two α-helices located at the binding groove (α₂) and the C-terminus (α₃). Here, we employ a new computational approach to develop a generalized view on the molecular basis of PDZ3 binding selectivity and interaction communication for a set of point mutants of the protein (G330T, H372A, G330T-H372A) and its ligand (CRIPT, named L₁, and its T-2F variant, L₂) along with the wild type (WT). To analyze the dynamical aspects hidden in the conformations that are produced by molecular dynamics simulations, we utilize variations in community composition calculated based on the betweenness centrality measure from graph theory. We find that the highly charged N-terminus, which is located far from the ligand, has the propensity to share the same community with the ligand in the biologically functional complexes, indicating a distal segment might mediate the binding dynamics. N- and C-termini of PDZ3 share communities, and α₃ acts as a hub for the whole protein by sustaining the communication with all structural segments, albeit being a trait not unique to the functional complexes. Moreover, α₂ which lines the binding cavity frequently parts communities with the ligand and is not a controller of the binding but is rather a slave to the overall dynamics coordinated by the N-terminus. Thus, ligand binding fate in PDZ3 is traced to the population of community compositions extracted from dynamics despite the lack of significant conformational changes.

Structure, Function, and Thermal Adaptation of the Biotin Carboxylase Domain Dimer from Hydrogenobacter thermophilus 2-Oxoglutarate Carboxylase

2-Oxoglutarate carboxylase (OGC), a unique member of the biotin-dependent carboxylase family from the order Aquificales, captures dissolved CO₂ via the reductive tricarboxylic acid (rTCA) cycle. Structure and function studies of OGC may facilitate adaptation of the rTCA cycle to increase the level of carbon fixation for biofuel production. Here we compare the biotin carboxylase (BC) domain of Hydrogenobacter thermophilus OGC with the well-studied mesophilic homologues to identify features that may contribute to thermal stability and activity. We report three OGC BC X-ray structures, each bound to bicarbonate, ADP, or ADP-Mg²⁺, and propose that substrate binding at high temperatures is facilitated by interactions that stabilize the flexible subdomain B in a partially closed conformation. Kinetic measurements with varying ATP and biotin concentrations distinguish two temperature-dependent steps, consistent with biotin's rate-limiting role in organizing the active site. Transition state thermodynamic values derived from the Eyring equation indicate a larger positive ΔH^⧧ and a less negative ΔS^⧧ compared to those of a previously reported mesophilic homologue. These thermodynamic values are explained by partially rate limiting product release. Phylogenetic analysis of BC domains suggests that OGC diverged prior to Aquificales evolution. The phylogenetic tree identifies mis-annotations of the Aquificales BC sequences, including the Aquifex aeolicus pyruvate carboxylase structure. Notably, our structural data reveal that the OGC BC dimer comprises a "wet" dimerization interface that is dominated by hydrophilic interactions and structural water molecules common to all BC domains and likely facilitates the conformational changes associated with the catalytic cycle. Mutations in the dimerization domain demonstrate that dimerization contributes to thermal stability.

Surveying the Side-Chain Network Approach to Protein Structure and Dynamics: The SARS-CoV-2 Spike Protein as an Illustrative Case

Network theory-based approaches provide valuable insights into the variations in global structural connectivity between different dynamical states of proteins. Our objective is to review network-based analyses to elucidate such variations, especially in the context of subtle conformational changes. We present technical details of the construction and analyses of protein structure networks, encompassing both the non-covalent connectivity and dynamics. We examine the selection of optimal criteria for connectivity based on the physical concept of percolation. We highlight the advantages of using side-chain-based network metrics in contrast to backbone measurements. As an illustrative example, we apply the described network approach to investigate the global conformational changes between the closed and partially open states of the SARS-CoV-2 spike protein. These conformational changes in the spike protein is crucial for coronavirus entry and fusion into human cells. Our analysis reveals global structural reorientations between the two states of the spike protein despite small changes between the two states at the backbone level. We also observe some differences at strategic locations in the structures, correlating with their functions, asserting the advantages of the side-chain network analysis. Finally, we present a view of allostery as a subtle synergistic-global change between the ligand and the receptor, the incorporation of which would enhance drug design strategies.

Identification of Functional Interactome of Gastric Cancer Cells with Helicobacter pylori Outer Membrane Protein HpaA by HPLC-MS/MS

HpaA as an outer membrane protein of Helicobacter pylori (H. pylori) plays a significant role in the adhesion to the human stomach, but the functional relation between HpaA and gastric epithelial cells is still not clear. To screen the interaction between HpaA and cellular proteins in gastric epithelial cells, the HpaA protein from H. pylori 26695 fused with a tag (6× His) was expressed and purified successfully, the secondary structure was estimated by the Circular Dichroism (CD) spectrum, and the purified recombinant protein was used to perform the pull-down assays with gastric cancer cell lines (AGS and SGC-7901) lysates, respectively. The pull-down proteins were identified by high-performance liquid chromatography tandem mass spectrometry system (HPLC-MS/MS). A total of 9 and 13 proteins related were analyzed from AGS and SGC-7901 cell lysates, respectively. ANXA2 was considered as putative HpaA functional partner discovered from lysates of both cell lines with high score and coverage. It is hypothesized that HpaA may be involved in the biological process of regulation of transcription and nucleic acid metabolism during the adhesion of H. pylori to human gastric epithelial cells, and HpaA-binding proteins also be used as targets for the development of antiadhesion drugs against H. pylori.

Non-symmetrical structural behavior of a symmetric protein: the case of homo-trimeric TRAF2 (tumor necrosis factor-receptor associated factor 2)

The oligomeric state of TRAF2 (tumor necrosis factor-receptor associated factor 2), a TNF (tumor necrosis factor) receptor-associated factor, is crucial for membrane binding and probably plays a fundamental role in regulating the protein function in vivo. In this study we have combined molecular dynamics with the protein contact network approach to characterize the interaction of the three identical subunits of TRAF2. The average structure obtained after a 225 ns simulation reveals that two clusters of different size are formed, one of which includes almost completely two subunits, while the third monomer appears to be more independent. This picture is also confirmed by the estimated average number of inter-subunit contacts and by the comparison of side chains mobility in each monomer. The analysis of equilibrium pressure-induced dissociation measurements supports such findings, indicating that the dimeric-monomeric (2 + 1) might be prevalent with respect to the trimeric configuration, especially in the case of more diluted samples. These findings suggest that the formation of monomeric species, which is crucial for the formation of intra-luminal vesicles, might depend on preferential asymmetric interactions among the three subunits.Communicated by Ramaswamy H. Sarma.

T54R mutation destabilizes the dimer of superoxide dismutase 1T54R by inducing steric clashes at the dimer interface

Mutations cause abnormalities in protein structure, function and oligomerization. Different mutations in the superoxide dismutase 1 (SOD1) protein cause its misfolding, loss of dimerization and aggravate its aggregation in the amyotrophic lateral sclerosis disease. In this study, we report the mechanistic details of how a threonine-to-arginine mutation at the 54^th position (T54R) of SOD1 results in destabilization of the dimer interface of SOD1^T54R. Using computational and experimental methods, we show that the T54R mutation increases fluctuation of the mutation-harboring loop (R54-loop) of SOD1^T54R. Fluctuation of this loop causes steric clashes that involve arginine-54 (R54) and other residues of SOD1^T54R, resulting in loss of inter-subunit contacts at the dimer interface. Since the T54 residue-containing loop is necessary for the dimerization of wild-type SOD1, fluctuation of the R54-loop, steric clashes involving R54 and loss of inter-subunit contacts give rise to the loss of SOD1^T54R dimer stability. This correlates to energetically unfavorable tethering of the monomers of SOD1^T54R. The outcome is gradual splitting of SOD1^T54R dimers into monomers, thereby exposing the previously buried hydrophobic interface residues to the aqueous environment. This event finally leads to aggregation of SOD1^T54R. T54R mutation has no effect in altering the relative positions of copper and zinc ion binding residues of SOD1^T54R. The native SOD1 structure is stable, and there is no destabilizing effect at its dimer interface. Overall, our study reveals the intricate mechanism of T54R mutation-associated destabilization of the dimer of the SOD1^T54R protein.

T54R mutation destabilizes the dimer of SOD1^T54R.

Dynamic properties of oligomers that characterize low-frequency normal modes

Dynamics of oligomeric proteins (one trimer, two tetramers, and one hexamer) were studied by elastic network model-based normal mode analysis to characterize their large-scale concerted motions. First, the oligomer motions were simplified by considering rigid-body motions of individual subunits. The subunit motions were resolved into three components in a cylindrical coordinate system: radial, tangential, and axial ones. Single component is dominant in certain normal modes. However, more than one component is mixed in others. The subunits move symmetrically in certain normal modes and as a standing wave with several wave nodes in others. Secondly, special attention was paid to atoms on inter-subunit interfaces. Their displacement vectors were decomposed into intra-subunit deformative (internal) and rigid-body (external) motions in individual subunits. The fact that most of the cosines of the internal and external motion vectors were negative for the atoms on the inter-subunit interfaces, indicated their opposing movements. Finally, a structural network of residues defined for each normal mode was investigated; the network was constructed by connecting two residues in contact and moving coherently. The centrality measure “betweenness” of each residue was calculated for the networks. Several residues with significantly high betweenness were observed on the inter-subunit interfaces. The results indicate that these residues are responsible for oligomer dynamics. It was also observed that amino acid residues with significantly high betweenness were more conservative. This supports that the betweenness is an effective characteristic for identifying an important residue in protein dynamics.

Discovery of Functional Motifs from the Interface Region of Oligomeric Proteins Using Frequent Subgraph Mining

Modeling the interface region of a protein complex paves the way for understanding its dynamics and functionalities. Existing works model the interface region of a complex by using different approaches, such as, the residue composition at the interface region, the geometry of the interface residues, or the structural alignment of interface regions. These approaches are useful for ranking a set of docked conformation or for building scoring function for protein-protein docking, but they do not provide a generic and scalable technique for the extraction of interface patterns leading to functional motif discovery. In this work, we model the interface region of a protein complex by graphs and extract interface patterns of the given complex in the form of frequent subgraphs. To achieve this, we develop a scalable algorithm for frequent subgraph mining. We show that a systematic review of the mined subgraphs provides an effective method for the discovery of functional motifs that exist along the interface region of a given protein complex. In our experiments, we use three PDB protein structure datasets. The first two datasets are composed of PDB structures from different conformations of two dimeric protein complexes: HIV-1 protease (329 structures), and triosephosphate isomerase (TIM) (86 structures). The third dataset is a collection of different enzyme structures protein structures from the six top-level enzyme classes, namely: Oxydoreductase, Transferase, Hydrolase, Lyase, Isomerase, and Ligase. We show that for the first two datasets, our method captures the locking mechanism at the dimeric interface by taking into account the spatial positioning of the interfacial residues through graphs. Indeed, our frequent subgraph mining based approach discovers the patterns representing the dimerization lock which is formed at the base of the structure in 323 of the 329 HIV-1 protease structures. Similarly, for 86 TIM structures, our approach discovers the dimerization lock formation in 50 structures. For the enzyme structures, we show that we are able to capture the functional motifs (active sites) that are specific to each of the six top-level classes of enzymes through frequent subgraphs.

Conformational Dynamics and Allosteric Regulation Landscapes of Germline PTEN Mutations Associated with Autism Compared to Those Associated with Cancer

Individuals with germline PTEN tumor-suppressor variants have PTEN hamartoma tumor syndrome (PHTS). Clinically, PHTS has variable presentations; there are distinct subsets of PHTS-affected individuals, such as those diagnosed with autism spectrum disorder (ASD) or cancer. It remains unclear why mutations in one gene can lead to such seemingly disparate phenotypes. Therefore, we sought to determine whether it is possible to predict a given PHTS-affected individual's a priori risk of ASD, cancer, or the co-occurrence of both phenotypes. By integrating network proximity analysis performed on the human interactome, molecular simulations, and residue-interaction networks, we demonstrate the role of conformational dynamics in the structural communication and long-range allosteric regulation of germline PTEN variants associated with ASD or cancer. We show that the PTEN interactome shares significant overlap with the ASD and cancer interactomes, providing network-based evidence that PTEN is a crucial player in the biology of both disorders. Importantly, this finding suggests that a germline PTEN variant might perturb the ASD or cancer networks differently, thus favoring one disease outcome at any one time. Furthermore, protein-dynamic structural-network analysis reveals small-world structural communication mediated by highly conserved functional residues and potential allosteric regulation of PTEN. We identified a salient structural-communication pathway that extends across the inter-domain interface for cancer-only mutations. In contrast, the structural-communication pathway is predominantly restricted to the phosphatase domain for ASD-only mutations. Our integrative approach supports the prediction and potential modulation of the relevant conformational states that influence structural communication and long-range perturbations associated with mutational effects that lead to PTEN-ASD or PTEN-cancer phenotypes.

Defining the architecture of KPC-2 Carbapenemase: identifying allosteric networks to fight antibiotics resistance

The rise of multi-drug resistance in bacterial pathogens is one of the grand challenges facing medical science. A major concern is the speed of development of β-lactamase-mediated resistance in Gram-negative species, thus putting at risk the efficacy of the most recently approved antibiotics and inhibitors, including carbapenems and avibactam, respectively. New strategies to overcome resistance are urgently required, which will ultimately be facilitated by a deeper understanding of the mechanisms that regulate the function of β-lactamases such as the Klebsiella Pneumoniae carbapenemases (KPCs). Using enhanced sampling computational methods together with site-directed mutagenesis, we report the identification of two “hydrophobic networks” in the KPC-2 enzyme, the integrity of which has been found to be essential for protein stability and corresponding resistance. Present throughout the structure, these networks are responsible for the structural integrity and allosteric signaling. Disruption of the networks leads to a loss of the KPC-2 mediated resistance phenotype, resulting in restored susceptibility to different classes of β-lactam antibiotics including carbapenems and cephalosporins. The ”hydrophobic networks” were found to be highly conserved among class-A β-lactamases, which implies their suitability for exploitation as a potential target for therapeutic intervention.

Profilin Negatively Regulates Formin-Mediated Actin Assembly to Modulate PAMP-Triggered Plant Immunity

Profilin functions with formin in actin assembly, a process that regulates multiple aspects of plant development and immune responses. High-level eukaryotes contain multiple isoforms of profilin, formin, and actin, whose partner-specific interactions in actin assembly are not completely understood in plant development and defense responses. To examine the functionally distinct interactions between profilin and formin, we studied all five Arabidopsis profilins and their interactions with formin by using both in vitro biochemical and in vivo cell biology approaches. Unexpectedly, we found a previously undescribed negative regulatory function of AtPRF3 in AtFH1-mediated actin polymerization. The N-terminal 37 residues of AtPRF3 were identified to play a predominant role in inhibiting formin-mediated actin nucleation via their high affinity for the formin polyproline region and their triggering of the oligomerization of AtPRF3. Both in vivo and in vitro mechanistic studies of AtPRF3 revealed a universal mechanism in which the weak interaction between profilin and formin positively regulates actin assembly by ensuring rapid recycling of profilin, whereas profilin oligomerization negatively regulates actin polymerization. Upon recognition of the pathogen-associated molecular pattern, the gene transcription and protein degradation of AtPRF3 are modulated for actin assembly during plant innate immunity. The prf3 Arabidopsis plants show higher sensitivity to the bacterial flagellum peptide in both the plant growth and ROS responses. These findings demonstrate a profilin-mediated actin assembly mechanism underlying the plant immune responses.

Effect of astragaloside IV on diabetic gastric mucosa in vivo and in vitro

This study evaluated the effects of AS-IV on high glucose induced-gastric mucosal lesions compared to the effects of the Bu-zhong-yi-qi pill and the Xiaoke pill, which are already in clinical use. STZ-induced diabetic SD rats were treated with drugs for 12 weeks. Diabetes serum (DS) was used to mimic high glucose conditions in GES-1 cells in vitro at different concentrations and time points. The drugs were set at three concentration gradients for 24, 48 and 72 h before being added to DS-induced GES-1 cells. The proliferation activity and inhibition ratio of cells were measured by the CCK-8 assay. Gastric tissues were examined by H&E staining. Cell morphology was observed by inverted phase contrast microscopy. Apoptosis of cells was detected by annexin V-FITC/PI. In addition, expression levels of inducible nitric oxide synthase (iNOS), cyclooxygenase-2 (COX-2) and mucin1 (MUC1) were measured by Western blots. We found that the drugs significantly alleviated the pathological damage in STZ-induced gastric mucosal lesions. DS inhibited the viability of the cells in a dose and time-dependent manner, while pretreatment with drugs reversed these effects. Pretreatment with drugs also ameliorated the changes in cell morphology and inhibited cell apoptosis. Furthermore, the drugs decreased the expression levels of iNOS, COX-2 and MUC1. AS-IV showed the most beneficial effect compared with buzhong and xiaoke. These results suggest that AS-IV had a significant effect on high glucose-induce gastric mucosal lesions compares with buzhong and xiaoke. We speculate that this is in part through restoring the balance of iNOS, COX-2 and MUC1 expressions. Thus, AS-IV may be a potential antioxidant drug for treating diabetic gastropathy.

Uncovering GPCR and G Protein Function by Protein Structure Network Analysis

Protein structure network (PSN) analysis is one of the graph theory-based approaches currently used for investigating structural communication in biomolecular systems. Information on the system's dynamics can be provided by atomistic molecular dynamics (MD) simulations or coarse grained elastic network models paired with normal mode analysis (ENM-NMA). This chapter reports on selected applications of PSN analysis to uncover the structural communication in G protein coupled receptors (GPCRs) and G proteins. Strategies to highlight changes in structural communication caused by mutations, ligand and protein binding are described. Conserved amino acids, sites of misfolding mutations, or ligands acting as functional switches tend to behave as hubs in the native structure networks. Densely linked regions in the protein structure graphs could be identified as playing central roles in protein stability and function. Changes in the communication pathway fingerprints depending on the bound ligand or following amino acid mutation could be highlighted as well. A bridge between misfolding and misrouting could be established in rhodopsin mutants linked to inherited blindness. The analysis of native network perturbations by misfolding mutations served to infer key structural elements of protein responsiveness to small chaperones with implications for drug discovery.

Prediction of interface residue based on the features of residue interaction network

Protein-protein interaction plays a crucial role in the cellular biological processes. Interface prediction can improve our understanding of the molecular mechanisms of the related processes and functions. In this work, we propose a classification method to recognize the interface residue based on the features of a weighted residue interaction network. The random forest algorithm is used for the prediction and 16 network parameters and the B-factor are acting as the element of the input feature vector. Compared with other similar work, the method is feasible and effective. The relative importance of these features also be analyzed to identify the key feature for the prediction. Some biological meaning of the important feature is explained. The results of this work can be used for the related work about the structure-function relationship analysis via a residue interaction network model.

Prediction and analysis of promiscuous T cell-epitopes derived from the vaccine candidate antigens of Leishmania donovani binding to MHC class-II alleles using in silico approach

Visceral leishmaniasis is a dreadful infectious disease and caused by the intracellular protozoan parasites, Leishmania donovani and Leishmania infantum. Despite extensive efforts for developing effective prophylactic vaccine, still no vaccine is available against leishmaniasis. However, advancement in immunoinformatics methods generated new dimension in peptide based vaccine development. The present study was aimed to identify T-cell epitopes from the vaccine candidate antigens like Lipophosphogylcan-3(LPG-3) and Nucleoside hydrolase (NH) from the L. donovani using in silico methods. Available best tools were used for the identification of promiscuous peptides for MHC class-II alleles. A total of 34 promiscuous peptides from LPG-3, 3 from NH were identified on the basis of their 100% binding affinity towards all six HLA alleles, taken in this study. These peptides were further checked computationally to know their IFN-γ and IL4 inducing potential and nine peptides were identified. Peptide binding interactions with predominant HLA alleles were done by docking. Out of nine docked promiscuous peptides, only two peptides (QESRILRVIKKKLVR, RILRVIKKKLVRKTL), from LPG-3 and one peptide (FDKFWCLVIDALKRI) from NH showed lowest binding energy with all six alleles. These promiscuous T-cell epitopes were predicted on the basis of their antigenicity, hydrophobicity, potential immune response and docking scores. The immunogenicity of predicted promiscuous peptides might be used for subunit vaccine development with immune-modulating adjuvants.

Unwinding the Novel Genes Involved in the Differentiation of Embryonic Stem Cells into Insulin-Producing Cells: A Network-Based Approach

Diabetes is one of the main causes of death in the world. Diabetes is marked by high blood glucose levels and develops when the body doesn't produce enough insulin or is not able to use insulin effectively, or both. Type I diabetes is a chronic sickness caused by lack of insulin due to the autoimmune destruction of pancreatic insulin-producing beta cells. Research on permanent cure for diabetes is in progress with several remarkable findings in the past few decades among which stem cell therapy has turned out to be a promising way to cure diabetes. Stem cells have the remarkable potential to differentiate into glucose-responsive beta cells through controlled differentiation protocols. Discovering novel targets that could potentially influence the differentiation to specific cell type will help in disease therapy. The present work focuses on finding novel genes or transcription factors involved in the human embryonic stem cell differentiation into insulin-producing beta cells using network biology approach. The interactome of 321 genes and their associated molecules involved in human embryonic stem cell differentiation into beta cells was constructed, which includes 1937 nodes and 8105 edges with a scale-free topology. Pathway analysis for the hubs obtained through MCODE revealed that four highly interactive hubs were relevant to embryonic stem cell differentiation into insulin-producing cells. Their role in different pathways and stem cell differentiation was studied. Centrality parameters were applied to identify the potential controllers of the differentiation processes: BMP4, SALL4, ZIC1, NTS, RNF2, FOXO1, AKT1 and GATA4. This type of approach gives an insight to identify potential genes/transcription factors which may play influential role in many complex biological processes.

Protein-Protein Interface and Disease: Perspective from Biomolecular Networks

Protein-protein interactions are involved in many important biological processes and molecular mechanisms of disease association. Structural studies of interfacial residues in protein complexes provide information on protein-protein interactions. Characterizing protein-protein interfaces, including binding sites and allosteric changes, thus pose an imminent challenge. With special focus on protein complexes, approaches based on network theory are proposed to meet this challenge. In this review we pay attention to protein-protein interfaces from the perspective of biomolecular networks and their roles in disease. We first describe the different roles of protein complexes in disease through several structural aspects of interfaces. We then discuss some recent advances in predicting hot spots and communication pathway analysis in terms of amino acid networks. Finally, we highlight possible future aspects of this area with respect to both methodology development and applications for disease treatment.

Characterization of Protein-Protein Interfaces through a Protein Contact Network Approach

Anthrax toxin comprises three different proteins, jointly acting to exert toxic activity: a non-toxic protective agent (PA), toxic edema factor (EF), and lethal factor (LF). Binding of PA to anthrax receptors promotes oligomerization of PA, binding of EF and LF, and then endocytosis of the complex. Homomeric forms of PA, complexes of PA bound to LF and to the endogenous receptor capillary morphogenesis gene 2 (CMG2) were analyzed. In this work, we characterized protein–protein interfaces (PPIs) and identified key residues at PPIs of complexes, by means of a protein contact network (PCN) approach. Flexibility and global and local topological properties of each PCN were computed. The vulnerability of each PCN was calculated using different node removal strategies, with reference to specific PCN topological descriptors, such as participation coefficient, contact order, and degree. The participation coefficient P, the topological descriptor of the node’s ability to intervene in protein inter-module communication, was the key descriptor of PCN vulnerability of all structures. High P residues were localized both at PPIs and other regions of complexes, so that we argued an allosteric mechanism in protein–protein interactions. The identification of residues, with key role in the stability of PPIs, has a huge potential in the development of new drugs, which would be designed to target not only PPIs but also residues localized in allosteric regions of supramolecular complexes.

The G protein-coupled receptor heterodimer network (GPCR-HetNet) and its hub components

G protein-coupled receptors (GPCRs) oligomerization has emerged as a vital characteristic of receptor structure. Substantial experimental evidence supports the existence of GPCR-GPCR interactions in a coordinated and cooperative manner. However, despite the current development of experimental techniques for large-scale detection of GPCR heteromers, in order to understand their connectivity it is necessary to develop novel tools to study the global heteroreceptor networks. To provide insight into the overall topology of the GPCR heteromers and identify key players, a collective interaction network was constructed. Experimental interaction data for each of the individual human GPCR protomers was obtained manually from the STRING and SCOPUS databases. The interaction data were used to build and analyze the network using Cytoscape software. The network was treated as undirected throughout the study. It is comprised of 156 nodes, 260 edges and has a scale-free topology. Connectivity analysis reveals a significant dominance of intrafamily versus interfamily connections. Most of the receptors within the network are linked to each other by a small number of edges. DRD2, OPRM, ADRB2, AA2AR, AA1R, OPRK, OPRD and GHSR are identified as hubs. In a network representation 10 modules/clusters also appear as a highly interconnected group of nodes. Information on this GPCR network can improve our understanding of molecular integration. GPCR-HetNet has been implemented in Java and is freely available at http://www.iiia.csic.es/~ismel/GPCR-Nets/index.html.

Molecular dynamics study of HIV-1 RT-DNA-nevirapine complexes explains NNRTI inhibition and resistance by connection mutations

HIV-1 reverse transcriptase (RT) is a multifunctional enzyme that is targeted by nucleoside analogs (NRTIs) and non-nucleoside RT inhibitors (NNRTIs). NNRTIs are allosteric inhibitors of RT, and constitute an integral part of several highly active antiretroviral therapy regimens. Under selective pressure, HIV-1 acquires resistance against NNRTIs primarily by selecting mutations around the NNRTI pocket. Complete RT sequencing of clinical isolates revealed that spatially distal mutations arising in connection and the RNase H domain also confer NNRTI resistance and contribute to NRTI resistance. However, the precise structural mechanism by which the connection domain mutations confer NNRTI resistance is poorly understood. We performed 50-ns molecular dynamics (MD) simulations, followed by essential dynamics, free-energy landscape analyses, and network analyses of RT-DNA, RT-DNA-nevirapine (NVP), and N348I/T369I mutant RT-DNA-NVP complexes. MD simulation studies revealed altered global motions and restricted conformational landscape of RT upon NVP binding. Analysis of protein structure network parameters demonstrated a dissortative hub pattern in the RT-DNA complex and an assortative hub pattern in the RT-DNA-NVP complex suggesting enhanced rigidity of RT upon NVP binding. The connection subdomain mutations N348I/T369I did not induce any significant structural change; rather, these mutations modulate the conformational dynamics and alter the long-range allosteric communication network between the connection subdomain and NNRTI pocket. Insights from the present study provide a structural basis for the biochemical and clinical findings on drug resistance caused by the connection and RNase H mutations.

DrugScorePPI knowledge-based potentials used as scoring and objective function in protein-protein docking

The distance-dependent knowledge-based DrugScore^PPI potentials, previously developed for in silico alanine scanning and hot spot prediction on given structures of protein-protein complexes, are evaluated as a scoring and objective function for the structure prediction of protein-protein complexes. When applied for ranking “unbound perturbation” (“unbound docking”) decoys generated by Baker and coworkers a 4-fold (1.5-fold) enrichment of acceptable docking solutions in the top ranks compared to a random selection is found. When applied as an objective function in FRODOCK for bound protein-protein docking on 97 complexes of the ZDOCK benchmark 3.0, DrugScore^PPI/FRODOCK finds up to 10% (15%) more high accuracy solutions in the top 1 (top 10) predictions than the original FRODOCK implementation. When used as an objective function for global unbound protein-protein docking, fair docking success rates are obtained, which improve by ∼2-fold to 18% (58%) for an at least acceptable solution in the top 10 (top 100) predictions when performing knowledge-driven unbound docking. This suggests that DrugScore^PPI balances well several different types of interactions important for protein-protein recognition. The results are discussed in view of the influence of crystal packing and the type of protein-protein complex docked. Finally, a simple criterion is provided with which to estimate a priori if unbound docking with DrugScore^PPI/FRODOCK will be successful.

Improving predictions of protein-protein interfaces by combining amino acid-specific classifiers based on structural and physicochemical descriptors with their weighted neighbor averages

Protein-protein interactions are involved in nearly all regulatory processes in the cell and are considered one of the most important issues in molecular biology and pharmaceutical sciences but are still not fully understood. Structural and computational biology contributed greatly to the elucidation of the mechanism of protein interactions. In this paper, we present a collection of the physicochemical and structural characteristics that distinguish interface-forming residues (IFR) from free surface residues (FSR). We formulated a linear discriminative analysis (LDA) classifier to assess whether chosen descriptors from the BlueStar STING database (http://www.cbi.cnptia.embrapa.br/SMS/) are suitable for such a task. Receiver operating characteristic (ROC) analysis indicates that the particular physicochemical and structural descriptors used for building the linear classifier perform much better than a random classifier and in fact, successfully outperform some of the previously published procedures, whose performance indicators were recently compared by other research groups. The results presented here show that the selected set of descriptors can be utilized to predict IFRs, even when homologue proteins are missing (particularly important for orphan proteins where no homologue is available for comparative analysis/indication) or, when certain conformational changes accompany interface formation. The development of amino acid type specific classifiers is shown to increase IFR classification performance. Also, we found that the addition of an amino acid conservation attribute did not improve the classification prediction. This result indicates that the increase in predictive power associated with amino acid conservation is exhausted by adequate use of an extensive list of independent physicochemical and structural parameters that, by themselves, fully describe the nano-environment at protein-protein interfaces. The IFR classifier developed in this study is now integrated into the BlueStar STING suite of programs. Consequently, the prediction of protein-protein interfaces for all proteins available in the PDB is possible through STING_interfaces module, accessible at the following website: (http://www.cbi.cnptia.embrapa.br/SMS/predictions/index.html).

Residue interaction network analysis of Dronpa and a DNA clamp

Topology is an essential aspect of protein structure. The network paradigm is increasingly used to describe the topology and dynamics of proteins. In this paper, the effect of topology on residue interaction network was investigated for two different proteins: Dronpa and a DNA clamp, which have cylindrical and toroidal topologies, respectively. Network metrics including characteristic path lengths, clustering coefficients, and diameters were calculated to investigate their global topology parameters such as small-world properties and packing density. Measures of centrality including betweenness, closeness, and residue centrality were computed to predict residues critical to function. Additionally, the detailed topology of the hydrophobic pocket in Dronpa, and communication pathways across the interface in the DNA clamp, were investigated using the network. The results are presented and discussed with regard to existing residue interaction network properties of globular proteins and elastic network models on Dronpa and the DNA clamp. The topological principle underlying residue interaction networks provided insight into the architectural organization of proteins.

Druggable orthosteric and allosteric hot spots to target protein-protein interactions

Drug designing targeting protein-protein interactions is challenging. Because structural elucidation and computational analysis have revealed the importance of hot spot residues in stabilizing these interactions, there have been on-going efforts to develop drugs which bind the hot spots and out-compete the native protein partners. The question arises as to what are the key 'druggable' properties of hot spots in protein-protein interactions and whether these mimic the general hot spot definition. Identification of orthosteric (at the protein- protein interaction site) and allosteric (elsewhere) druggable hot spots is expected to help in discovering compounds that can more effectively modulate protein-protein interactions. For example, are there any other significant features beyond their location in pockets in the interface? The interactions of protein-protein hot spots are coupled with conformational dynamics of protein complexes. Currently increasing efforts focus on the allosteric drug discovery. Allosteric drugs bind away from the native binding site and can modulate the native interactions. We propose that identification of allosteric hot spots could similarly help in more effective allosteric drug discovery. While detection of allosteric hot spots is challenging, targeting drugs to these residues has the potential of greatly increasing the hot spot and protein druggability.

Structural functionality, catalytic mechanism modeling and molecular allergenicity of phenylcoumaran benzylic ether reductase, an olive pollen (Ole e 12) allergen

Isoflavone reductase-like proteins (IRLs) are enzymes with key roles in the metabolism of diverse flavonoids. Last identified olive pollen allergen (Ole e 12) is an IRL relevant for allergy amelioration, since it exhibits high prevalence among atopic patients. The goals of this study are the characterization of (A) the structural-functionality of Ole e 12 with a focus in its catalytic mechanism, and (B) its molecular allergenicity by extensive analysis using different molecular computer-aided approaches covering (1) physicochemical properties and functional-regulatory motifs, (2) sequence analysis, 2-D and 3D structural homology modeling comparative study and molecular docking, (3) conservational and evolutionary analysis, (4) catalytic mechanism modeling, and (5) sequence, structure-docking based B-cell epitopes prediction, while T-cell epitopes were predicted by inhibitory concentration and binding score methods. Structural-based detailed features, phylogenetic and sequences analysis have identified Ole e 12 as phenylcoumaran benzylic ether reductase. A catalytic mechanism has been proposed for Ole e 12 which display Lys133 as one of the conserved residues of the IRLs catalytic tetrad (Asn-Ser-Tyr-Lys). Structure characterization revealed a conserved protein folding among plants IRLs. However, sequence polymorphism significantly affected residues involved in the catalytic pocket structure and environment (cofactor and substrate interaction-recognition). It might also be responsible for IRLs isoforms functionality and regulation, since micro-heterogeneities affected physicochemical and posttranslational motifs. This polymorphism might have large implications for molecular differences in B- and T-cells epitopes of Ole e 12, and its identification may help designing strategies to improve the component-resolving diagnosis and immunotherapy of pollen and food allergy through development of molecular tools.

Protein-protein interactions between the bilirubin-conjugating UDP-glucuronosyltransferase UGT1A1 and its shorter isoform 2 regulatory partner derived from alternative splicing

The oligomerization of UGTs [UDP (uridine diphosphate)-glucuronosyltransferases] modulates their enzyme activities. Recent findings also indicate that glucuronidation is negatively regulated by the formation of inactive oligomeric complexes between UGT1A enzymes [i1 (isoform 1)] and an enzymatically inactive alternatively spliced i2 (isoform 2). In the present paper, we assessed whether deletion of the UGT-interacting domains previously reported to be critical for enzyme function might be involved in i1-i2 interactions. The bilirubin-conjugating UGT1A1 was used as a prototype. We also explored whether intermolecular disulfide bonds are involved in i1-i2 interactions and the potential role of selected cysteine residues. Co-immunoprecipitation assays showed that UGT1A1 lacking the SP (signal peptide) alone or also lacking the transmembrane domain (absent from i2) did not self-interact, but still interacted with i2. The deletion of other N- or C-terminal domains did not compromise i1-i2 complex formation. Under non-reducing conditions, we also observed formation of HMWCs (high-molecular-mass complexes) for cells overexpressing i1 and i2. The presence of UGTs in these complexes was confirmed by MS. Mutation of individual cysteine residues throughout UGT1A1 did not compromise i1-i1 or i1-i2 complex formation. These findings are compatible with the hypothesis that the interaction between i1 and i2 proteins (either transient or stable) involves binding of more than one domain that probably differs from those involved in i1-i1 interactions.

Homoisocitrate dehydrogenase from Candida albicans: properties, inhibition, and targeting by an antifungal pro-drug

The LYS12 gene from Candida albicans, coding for homoisocitrate dehydrogenase was cloned and expressed as a His-tagged protein in Escherichia coli. The purified gene product catalyzes the Mg(2+)- and K(+)-dependent oxidative decarboxylation of homoisocitrate to α-ketoadipate. The recombinant enzyme demonstrates strict specificity for homoisocitrate. SDS-PAGE of CaHIcDH revealed its molecular mass of 42.6 ± 1 kDa, whereas in size-exclusion chromatography, the enzyme eluted in a single peak corresponding to a molecular mass of 158 ± 3 kDa. Native electrophoresis showed that CaHIcDH may exist as a monomer and as a tetramer and the latter form is favored by homoisocitrate binding. CaHIcDH is an hysteretic enzyme. The K(M) values of the purified His-tagged enzyme for NAD(+) and homoisocitrate were 1.09 mM and 73.7 μM, respectively, and k(cat) was 0.38 s(-1). Kinetic parameters determined for the wild-type CaHIcDH were very similar. The enzyme activity was inhibited by (2R,3S)-3-(p-carboxybenzyl)malate (CBMA), with IC(50) = 3.78 mM. CBMA demonstrated some moderate antifungal activity in minimal media that could be enhanced upon conversion of the enzyme inhibitor into its trimethyl ester derivative (TMCBMA). TMCBMA is the first reported antifungal for which an enzyme of the AAP was identified as a molecular target.

Quantum clustering and network analysis of MD simulation trajectories to probe the conformational ensembles of protein-ligand interactions

In this article, we present a novel application of a quantum clustering (QC) technique to objectively cluster the conformations, sampled by molecular dynamics simulations performed on different ligand bound structures of the protein. We further portray each conformational population in terms of dynamically stable network parameters which beautifully capture the ligand induced variations in the ensemble in atomistic detail. The conformational populations thus identified by the QC method and verified by network parameters are evaluated for different ligand bound states of the protein pyrrolysyl-tRNA synthetase (DhPylRS) from D. hafniense. The ligand/environment induced re-distribution of protein conformational ensembles forms the basis for understanding several important biological phenomena such as allostery and enzyme catalysis. The atomistic level characterization of each population in the conformational ensemble in terms of the re-orchestrated networks of amino acids is a challenging problem, especially when the changes are minimal at the backbone level. Here we demonstrate that the QC method is sensitive to such subtle changes and is able to cluster MD snapshots which are similar at the side-chain interaction level. Although we have applied these methods on simulation trajectories of a modest time scale (20 ns each), we emphasize that our methodology provides a general approach towards an objective clustering of large-scale MD simulation data and may be applied to probe multistate equilibria at higher time scales, and to problems related to protein folding for any protein or protein-protein/RNA/DNA complex of interest with a known structure.

Identification of B cell epitopes of alcohol dehydrogenase allergen of Curvularia lunata

Background/Objective

Epitope identification assists in developing molecules for clinical applications and is useful in defining molecular features of allergens for understanding structure/function relationship. The present study was aimed to identify the B cell epitopes of alcohol dehydrogenase (ADH) allergen from Curvularia lunata using in-silico methods and immunoassay.

Method

B cell epitopes of ADH were predicted by sequence and structure based methods and protein-protein interaction tools while T cell epitopes by inhibitory concentration and binding score methods. The epitopes were superimposed on a three dimensional model of ADH generated by homology modeling and analyzed for antigenic characteristics. Peptides corresponding to predicted epitopes were synthesized and immunoreactivity assessed by ELISA using individual and pooled patients' sera.

Result

The homology model showed GroES like catalytic domain joined to Rossmann superfamily domain by an alpha helix. Stereochemical quality was confirmed by Procheck which showed 90% residues in most favorable region of Ramachandran plot while Errat gave a quality score of 92.733%. Six B cell (P1–P6) and four T cell (P7–P10) epitopes were predicted by a combination of methods. Peptide P2 (epitope P2) showed E(X)₂GGP(X)₃KKI conserved pattern among allergens of pathogenesis related family. It was predicted as high affinity binder based on electronegativity and low hydrophobicity. The computational methods employed were validated using Bet v 1 and Der p 2 allergens where 67% and 60% of the epitope residues were predicted correctly. Among B cell epitopes, Peptide P2 showed maximum IgE binding with individual and pooled patients' sera (mean OD 0.604±0.059 and 0.506±0.0035, respectively) followed by P1, P4 and P3 epitopes. All T cell epitopes showed lower IgE binding.

Conclusion

Four B cell epitopes of C. lunata ADH were identified. Peptide P2 can serve as a potential candidate for diagnosis of allergic diseases.

Modeling allosteric signal propagation using protein structure networks

Allosteric communication in proteins can be induced by the binding of effective ligands, mutations or covalent modifications that regulate a site distant from the perturbed region. To understand allosteric regulation, it is important to identify the remote sites that are affected by the perturbation-induced signals and how these allosteric perturbations are transmitted within the protein structure. In this study, by constructing a protein structure network and modeling signal transmission with a Markov random walk, we developed a method to estimate the signal propagation and the resulting effects. In our model, the global perturbation effects from a particular signal initiation site were estimated by calculating the expected visiting time (EVT), which describes the signal-induced effects caused by signal transmission through all possible routes. We hypothesized that the residues with high EVT values play important roles in allosteric signaling. We applied our model to two protein structures as examples, and verified the validity of our model using various types of experimental data. We also found that the hot spots in protein binding interfaces have significantly high EVT values, which suggests that they play roles in mediating signal communication between protein domains.

Assortative mixing in close-packed spatial networks

Background

In recent years, there is aroused interest in expressing complex systems as networks of interacting nodes. Using descriptors from graph theory, it has been possible to classify many diverse systems derived from social and physical sciences alike. In particular, folded proteins as examples of self-assembled complex molecules have also been investigated intensely using these tools. However, we need to develop additional measures to classify different systems, in order to dissect the underlying hierarchy.

Methodology and Principal Findings

In this study, a general analytical relation for the dependence of nearest neighbor degree correlations on degree is derived. Dependence of local clustering on degree is shown to be the sole determining factor of assortative versus disassortative mixing in networks. The characteristics of networks constructed from spatial atomic/molecular systems exemplified by self-organized residue networks built from folded protein structures and block copolymers, atomic clusters and well-compressed polymeric melts are studied. Distributions of statistical properties of the networks are presented. For these densely-packed systems, assortative mixing in the network construction is found to apply, and conditions are derived for a simple linear dependence.

Conclusions

Our analyses (i) reveal patterns that are common to close-packed clusters of atoms/molecules, (ii) identify the type of surface effects prominent in different close-packed systems, and (iii) associate fingerprints that may be used to classify networks with varying types of correlations.

Insights into pH-induced conformational transition of β-galactosidase from Pisum sativum leading to its multimerization

Although β-galactosidases are physiologically a very important enzyme and have may therapeutics applications, very little is known about the stability and the folding aspects of the enzyme. We have used β-galactosidase from Pisum sativum (PsBGAL) as model system to investigate stability, folding, and function relationship of β-galactosidases. PsBGAL is a vacuolar protein which has a tendency to multimerize at acidic pH with protein concentration ≥100 μg mL⁻¹ and dissociates into its subunits above neutral pH. It exhibits maximum activity as well as stability under acidic conditions. Further, it has different conformational orientations and core secondary structures at different pH. Substantial predominance of β-content and interfacial interactions through Trp residues play crucial role in pH-dependent multimerization of enzyme. Equilibrium unfolding of PsBGAL at acidic pH follows four-state model when monitored by changes in the secondary structure with two intermediates: one resembling to molten globule-like state while unfolding seen from activity and tertiary structure of PsBGAL fits to two-state model. Unfolding of PsBGAL at higher pH always follows two-state model. Furthermore, unfolding of PsBGAL reveals that it has at least two domains: α/β barrel containing catalytic site and the other is rich in β-content responsible for enzyme multimerization.

The role of oligomerization and cooperative regulation in protein function: the case of tryptophan synthase

The oligomerization/co-localization of protein complexes and their cooperative regulation in protein function is a key feature in many biological systems. The synergistic regulation in different subunits often enhances the functional properties of the multi-enzyme complex. The present study used molecular dynamics and Brownian dynamics simulations to study the effects of allostery, oligomerization and intermediate channeling on enhancing the protein function of tryptophan synthase (TRPS). TRPS uses a set of α/β–dimeric units to catalyze the last two steps of L-tryptophan biosynthesis, and the rate is remarkably slower in the isolated monomers. Our work shows that without their binding partner, the isolated monomers are stable and more rigid. The substrates can form fairly stable interactions with the protein in both forms when the protein reaches the final ligand–bound conformations. Our simulations also revealed that the α/β–dimeric unit stabilizes the substrate–protein conformation in the ligand binding process, which lowers the conformation transition barrier and helps the protein conformations shift from an open/inactive form to a closed/active form. Brownian dynamics simulations with a coarse-grained model illustrate how protein conformations affect substrate channeling. The results highlight the complex roles of protein oligomerization and the fine balance between rigidity and dynamics in protein function.

Conformational changes of enzymes are often related to regulating and creating an optimal environment for efficient chemistry. An increasing number of evidences also indicate that oligomerization/co-localization of proteins contributes to the efficiency of metabolic pathways. Although static structures have been available for many multi-enzyme complexes, their efficiency is also governed by the synergistic regulation between the multi-units. Our study applies molecular dynamics and Brownian dynamics simulations to the model system, the tryptophan synthase complex. The multi-enzyme complex is a bienzyme nanomachine and its catalytic activity is intimately related to the allosteric signaling and the metabolite transfer between its α– and β–subunits connected by a 25-Å long channel. Our studies suggest that the binding partner is crucial for the ligand binding processes. Although the isolated monomers are stable in the ligand–free state and can form stable interaction if the substrate is in the final bound conformation, it has higher energy barrier when ligand binds to the active site. We also show that the channel does not always exist, but it may be blocked before the enzyme reaches its final bound conformation. The results highlight the importance of forming protein complexes and the cooperative changes during different states.

Elucidation of the conformational free energy landscape in H.pylori LuxS and its implications to catalysis

Background

One of the major challenges in understanding enzyme catalysis is to identify the different conformations and their populations at detailed molecular level in response to ligand binding/environment. A detail description of the ligand induced conformational changes provides meaningful insights into the mechanism of action of enzymes and thus its function.

Results

In this study, we have explored the ligand induced conformational changes in H.pylori LuxS and the associated mechanistic features. LuxS, a dimeric protein, produces the precursor (4,5-dihydroxy-2,3-pentanedione) for autoinducer-2 production which is a signalling molecule for bacterial quorum sensing. We have performed molecular dynamics simulations on H.pylori LuxS in its various ligand bound forms and analyzed the simulation trajectories using various techniques including the structure network analysis, free energy evaluation and water dynamics at the active site. The results bring out the mechanistic details such as co-operativity and asymmetry between the two subunits, subtle changes in the conformation as a response to the binding of active and inactive forms of ligands and the population distribution of different conformations in equilibrium. These investigations have enabled us to probe the free energy landscape and identify the corresponding conformations in terms of network parameters. In addition, we have also elucidated the variations in the dynamics of water co-ordination to the Zn²⁺ ion in LuxS and its relation to the rigidity at the active sites.

Conclusions

In this article, we provide details of a novel method for the identification of conformational changes in the different ligand bound states of the protein, evaluation of ligand-induced free energy changes and the biological relevance of our results in the context of LuxS structure-function. The methodology outlined here is highly generalized to illuminate the linkage between structure and function in any protein of known structure.

Allostery and conformational free energy changes in human tryptophanyl-tRNA synthetase from essential dynamics and structure networks

The interdependence of the concept of allostery and enzymatic catalysis, and they being guided by conformational mobility is gaining increased prominence. However, to gain a molecular level understanding of allostery and hence of enzymatic catalysis, it is of utter importance that the networks of amino acids participating in allostery be deciphered. Our lab has been exploring the methods of network analysis combined with molecular dynamics simulations to understand allostery at molecular level. Earlier we had outlined methods to obtain communication paths and then to map the rigid/flexible regions of proteins through network parameters like the shortest correlated paths, cliques, and communities. In this article, we advance the methodology to estimate the conformational populations in terms of cliques/communities formed by interactions including the side-chains and then to compute the ligand-induced population shift. Finally, we obtain the free-energy landscape of the protein in equilibrium, characterizing the free-energy minima accessed by the protein complexes. We have chosen human tryptophanyl-tRNA synthetase (hTrpRS), a protein responsible for charging tryptophan to its cognate tRNA during protein biosynthesis for this investigation. This is a multidomain protein exhibiting excellent allosteric communication. Our approach has provided valuable structural as well as functional insights into the protein. The methodology adopted here is highly generalized to illuminate the linkage between protein structure networks and conformational mobility involved in the allosteric mechanism in any protein with known structure.