InterProSurf: a web server for predicting interacting sites on protein surfaces

Identification of binding residues between periplasmic adapter protein (PAP) and RND efflux pumps explains PAP-pump promiscuity and roles in antimicrobial resistance

Active efflux due to tripartite RND efflux pumps is an important mechanism of clinically relevant antibiotic resistance in Gram-negative bacteria. These pumps are also essential for Gram-negative pathogens to cause infection and form biofilms. They consist of an inner membrane RND transporter; a periplasmic adaptor protein (PAP), and an outer membrane channel. The role of PAPs in assembly, and the identities of specific residues involved in PAP-RND binding, remain poorly understood. Using recent high-resolution structures, four 3D sites involved in PAP-RND binding within each PAP protomer were defined that correspond to nine discrete linear binding sequences or "binding boxes" within the PAP sequence. In the important human pathogen Salmonella enterica, these binding boxes are conserved within phylogenetically-related PAPs, such as AcrA and AcrE, while differing considerably between divergent PAPs such as MdsA and MdtA, despite overall conservation of the PAP structure. By analysing these binding sequences we created a predictive model of PAP-RND interaction, which suggested the determinants that may allow promiscuity between certain PAPs, but discrimination of others. We corroborated these predictions using direct phenotypic data, confirming that only AcrA and AcrE, but not MdtA or MsdA, can function with the major RND pump AcrB. Furthermore, we provide functional validation of the involvement of the binding boxes by disruptive site-directed mutagenesis. These results directly link sequence conservation within identified PAP binding sites with functional data providing mechanistic explanation for assembly of clinically relevant RND-pumps and explain how Salmonella and other pathogens maintain a degree of redundancy in efflux mediated resistance. Overall, our study provides a novel understanding of the molecular determinants driving the RND-PAP recognition by bridging the available structural information with experimental functional validation thus providing the scientific community with a predictive model of pump-contacts that could be exploited in the future for the development of targeted therapeutics and efflux pump inhibitors.

Structure and redox properties of the diheme electron carrier cytochrome c4 from Pseudomonas aeruginosa

At low oxygen concentrations, respiration of Pseudomonas aeruginosa (Pa) and other bacteria relies on activity of cytochrome cbb₃ oxidases. A diheme cytochrome c₄ (cyt c₄) donates electrons to Pa cbb₃ oxidases to enable oxygen reduction and proton pumping by these enzymes. Given the importance of this redox pathway for bacterial pathogenesis, both cyt c₄ and cbb₃ oxidase are potential targets for new antibacterial strategies. The structural information about these two proteins, however, is scarce, and functional insights for Pa and other bacteria have been primarily drawn from analyses of the analogous system from Pseudomonas stutzeri (Ps). Herein, we describe characterization of structural and redox properties of cyt c₄ from Pa. The crystal structure of Pa cyt c₄ has revealed that this protein is organized in two monoheme domains. The interdomain interface is more hydrophobic in Pa cyt c₄, and the protein surface does not show the dipolar distribution of charges found in Ps cyt c₄. The reduction potentials of the two hemes are similar in Pa cyt c₄ but differ by about 100 mV in Ps cyt c₄. Analyses of structural models of these and other cyt c₄ proteins suggest that multiple factors contribute to the potential difference of the two hemes in these proteins, including solvent accessibility of the heme group, the distribution of surface charges, and the nature of the interdomain interface. The distinct properties of cyt c₄ proteins from closely-related Pa and Ps bacteria emphasize the importance of examining the cbb₃/cyt c₄ redox pathway in multiple species.

Assessing the performance of the MM/PBSA and MM/GBSA methods. 10. Impacts of enhanced sampling and variable dielectric model on protein-protein Interactions

Enhanced sampling has been extensively used to capture the conformational transitions in protein folding, but it attracts much less attention in the studies of protein-protein recognition. In this study, we evaluated the impact of enhanced sampling methods and solute dielectric constants on the overall accuracy of the molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) and molecular mechanics/generalized Born surface area (MM/GBSA) approaches for the protein-protein binding free energy calculations. Here, two widely used enhanced sampling methods, including aMD and GaMD, and conventional molecular dynamics (cMD) simulations with two AMBER force fields (ff03 and ff14SB) were used to sample the conformations for 21 protein-protein complexes. The MM/PBSA and MM/GBSA calculation results illustrate that the standard MM/GBSA based on the cMD simulations yields the best Pearson correlation (r_p = -0.523) between the predicted binding affinities and the experimental data, which is much higher than that given by MM/PBSA (r_p = -0.212). Two enhanced sampling methods (aMD and GaMD) are indeed more efficient for conformational sampling, but they did not improve the binding affinity predictions for protein-protein systems, suggesting that the aMD or GaMD sampling (at least in short timescale simulations) may not be a good choice for the MM/PBSA and MM/GBSA predictions of protein-protein complexes. The solute dielectric constant of 1.0 is recommended to MM/GBSA, but a higher solute dielectric constant is recommended to MM/PBSA, especially for the systems with higher polarity on the protein-protein binding interfaces. Then, a preliminary assessment of the MM/GBSA calculations based on a variable dielectric generalized Born (VDGB) model was conducted. The results highlight the potential power of VDGB in the free energy predictions for protein-protein systems, but more thorough studies should be done in the future.

Specific inter-domain interactions stabilize a compact HIV-1 Gag conformation

HIV-1 Gag is a large multidomain poly-protein with flexible unstructured linkers connecting its globular subdomains. It is compact when in solution but assumes an extended conformation when assembled within the immature HIV-1 virion. Here, we use molecular dynamics (MD) simulations to quantitatively characterize the intra-domain interactions of HIV-1 Gag. We find that the matrix (MA) domain and the C-terminal subdomain CA_ctd of the CA capsid domain can form a bound state. The bound state, which is held together primarily by interactions between complementary charged and polar residues, stabilizes the compact state of HIV-1 Gag. We calculate the depth of the attractive free energy potential between the MA/ CA_ctd sites and find it to be about three times larger than the dimerization interaction between the CA_ctd domains. Sequence analysis shows high conservation within the newly-found intra-Gag MA/CA_ctd binding site, as well as its spatial proximity to other well known elements of Gag –such as CA_ctd’s SP1 helix region, its inositol hexaphosphate (IP6) binding site and major homology region (MHR), as well as the MA trimerization site. Our results point to a high, but yet undetermined, functional significance of the intra-Gag binding site. Recent biophysical experiments that address the binding specificity of Gag are interpreted in the context of the MA/CA_ctd bound state, suggesting an important role in selective packaging of genomic RNA by Gag.

CaMPK9 increases the stability of CaWRKY40 transcription factor which triggers defense response in chickpea upon Fusarium oxysporum f. sp. ciceri Race1 infection

Physical interaction and phosphorylation by CaMPK9 protects the degradation of CaWRKY40 that induces resistance response in chickpea to Fusarium wilt disease by modulating the transcription of defense responsive genes. WRKY transcription factors (TFs) are the global regulators of plant defense signaling that modulate immune responses in host plants by regulating transcription of downstream target genes upon challenged by pathogens. However, very little is known about immune responsive role of Cicer arietinum L. (Ca) WRKY TFs particularly. Using two contrasting chickpea genotypes with respect to resistance against Fusarium oxysporum f. sp. ciceri Race1 (Foc1), we demonstrate transcript accumulation of different CaWRKYs under multiple stresses and establish that CaWRKY40 triggers defense. CaWRKY40 overexpressing chickpea mounts resistance to Foc1 by positively modulating the defense related gene expression. EMSA, ChIP assay and real-time PCR analyses suggest CaWRKY40 binds at the promoters and positively regulates transcription of CaDefensin and CaWRKY33. Further studies revealed that mitogen Activated Protein Kinase9 (CaMPK9) phosphorylates CaWRKY40 by directly interacting with its two canonical serine residues. Interestingly, CaMPK9 is unable to interact with CaWRKY40 when the relevant two serine residues were replaced by alanine. Overexpression of serine mutated WRKY40 isoform in chickpea fails to provide resistance against Foc1. Mutated WRKY40^{Ser.224/225 to AA} overexpressing chickpea resumes its ability to confer resistance against Foc1 after application of 26S proteasomal inhibitor MG132, suggests that phosphorylation is essential to protect CaWRKY40 from proteasomal degradation. CaMPK9 silencing also led to susceptibility in chickpea to Foc1. Altogether, our results elucidate positive regulatory roles of CaMPK9 and CaWRKY40 in modulating defense response in chickpea upon Foc1 infection.

Dengue virus nonstructural 3 protein interacts directly with human glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and reduces its glycolytic activity

Dengue is an important mosquito-borne disease and a global public health problem. The disease is caused by dengue virus (DENV), which is a member of the Flaviviridae family and contains a positive single-stranded RNA genome that encodes a single precursor polyprotein that is further cleaved into structural and non-structural proteins. Among these proteins, the non-structural 3 (NS3) protein is very important because it forms a non-covalent complex with the NS2B cofactor, thereby forming the functional viral protease. NS3 also contains a C-terminal ATPase/helicase domain that is essential for RNA replication. Here, we identified 47 NS3-interacting partners using the yeast two-hybrid system. Among those partners, we highlight several proteins involved in host energy metabolism, such as apolipoprotein H, aldolase B, cytochrome C oxidase and glyceraldehyde-3-phosphate dehydrogenase (GAPDH). GAPDH directly binds full-length NS3 and its isolated helicase and protease domains. Moreover, we observed an intense colocalization between the GAPDH and NS3 proteins in DENV2-infected Huh7.5.1 cells, in NS3-transfected BHK-21 cells and in hepatic tissue from a fatal dengue case. Taken together, these results suggest that the human GAPDH-DENV NS3 interaction is involved in hepatic metabolic alterations, which may contribute to the appearance of steatosis in dengue-infected patients. The interaction between GAPDH and full-length NS3 or its helicase domain in vitro as well as in NS3-transfected cells resulted in decreased GAPDH glycolytic activity. Reduced GAPDH glycolytic activity may lead to the accumulation of metabolic intermediates, shifting metabolism to alternative, non-glycolytic pathways. This report is the first to identify the interaction of the DENV2 NS3 protein with the GAPDH protein and to demonstrate that this interaction may play an important role in the molecular mechanism that triggers hepatic alterations.

Sequence analysis of the cDNA encoding for SpCTx: a lethal factor from scorpionfish venom (Scorpaena plumieri)

Background

Lethal factors are multifunctional oligomeric proteins found in the venomous apparatus of Scorpaeniformes fish. These toxins elicit not only an array of biological responses in vitro but also cardiovascular disorders and strong hemolytic, nociceptive and edematogenic activities in vivo. This work describes the cloning and molecular identification of two toxin subunits, denominated Sp-CTx-α and Sp-CTx-β, from scorpionfish venom (Scorpaena plumieri).

Methods

The primary structures were deduced after cDNA amplification by PCR with primers from conserved sequences described in Scorpaeniformes toxins. Following DNA sequencing and bioinformatic analysis, the tridimensional structures of both subunits were modeled.

Results

The translated sequences (702 amino acids, each subunit) show homology with other lethal factors, while alignment between Sp-CTx-α and Sp-CTx-β shows 54% identity. The subunits lack N-terminal signal sequences and display masses of approximately 80 kDa each. Both Sp-CTx subunits display a B30.2/SPRY domain at the C-terminal region with typically conserved motifs as described in these toxins. Secondary structure prediction identified six α-helices 18 residues long in both α and β subunits, some of them amphiphilic with their N-terminal flanked by many basic residues, creating a cationic site associated with the cytolytic activity of these toxins. Antimicrobial potential sites were identified in Sp-CTx and share some features with other peptides presenting variable and broad-spectrum activity. A phylogenetic tree built to represent these toxins supports the proximity between scorpionfish, lionfish and stonefish.

Conclusion

The study identified a putative toxin protein whose primary structure is similar to other fish toxins and with potential for production of antivenom against scorpionfish envenomation in Brazil. As a prelude to structure-function studies, we propose that the toxin is structurally related to pore-forming marine toxins.

Electronic supplementary material

The online version of this article (10.1186/s40409-018-0158-7) contains supplementary material, which is available to authorized users.

Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery

The advent of advanced molecular modeling software, big data analytics, and high-speed processing units has led to the exponential evolution of modern drug discovery and better insights into complex biological processes and disease networks. This has progressively steered current research interests to understanding protein-protein interaction (PPI) systems that are related to a number of relevant diseases, such as cancer, neurological illnesses, metabolic disorders, etc. However, targeting PPIs are challenging due to their "undruggable" binding interfaces. In this review, we focus on the current obstacles that impede PPI drug discovery, and how recent discoveries and advances in in silico approaches can alleviate these barriers to expedite the search for potential leads, as shown in several exemplary studies. We will also discuss about currently available information on PPI compounds and systems, along with their usefulness in molecular modeling. Finally, we conclude by presenting the limits of in silico application in drug discovery and offer a perspective in the field of computer-aided PPI drug discovery.

A Hyperthermophilic Phage Decoration Protein Suggests Common Evolutionary Origin with Herpesvirus Triplex Proteins and an Anti-CRISPR Protein

Virus capsids are protein shells that protect the viral genome from environmental assaults, while maintaining the high internal pressure of the tightly packaged genome. To elucidate how capsids maintain stability under harsh conditions, we investigated the capsid components of the hyperthermophilic phage P74-26. We determined the structure of capsid protein gp87 and show that it has the same fold as decoration proteins in many other phages, despite lacking significant sequence homology. We also find that gp87 is significantly more stable than mesophilic homologs. Our analysis of the gp87 structure reveals that the core "β tulip" domain is conserved in trimeric capsid components across numerous double-stranded DNA viruses, including Herpesviruses. Moreover, this β barrel domain is found in anti-CRISPR protein AcrIIC1, suggesting a mechanism for the evolution of this Cas9 inhibitor. Our work illustrates the principles for increased stability of gp87, and extends the evolutionary reach of the β tulip domain.

Structural insight into the rearrangement of the switch I region in GTP-bound G12A K-Ras

K-Ras, a molecular switch that regulates cell growth, apoptosis and metabolism, is activated when it undergoes a conformation change upon binding GTP and is deactivated following the hydrolysis of GTP to GDP. Hydrolysis of GTP in water is accelerated by coordination to K-Ras, where GTP adopts a high-energy conformation approaching the transition state. The G12A mutation reduces intrinsic K-Ras GTP hydrolysis by an unexplained mechanism. Here, crystal structures of G12A K-Ras in complex with GDP, GTP, GTPγS and GppNHp, and of Q61A K-Ras in complex with GDP, are reported. In the G12A K-Ras-GTP complex, the switch I region undergoes a significant reorganization such that the Tyr32 side chain points towards the GTP-binding pocket and forms a hydrogen bond to the GTP γ-phosphate, effectively stabilizing GTP in its precatalytic state, increasing the activation energy required to reach the transition state and contributing to the reduced intrinsic GTPase activity of G12A K-Ras mutants.

Linear epitope prediction in HPV type 16 E7 antigen and their docked interaction with human TMEM 50A structural model

Human Papilloma Virus (HPV) HPV type 16 E7 antigen is a known target in cervical cancer. We report the predicted potential epitopes in the E7 antigen. We further describe the subsequent interaction of these linear epitope peptides with the human TMEM 50 A structural model using molecular docking. This data finds application in the development of components towards HPV associated disease prevention.

Cross-React: a new structural bioinformatics method for predicting allergen cross-reactivity

The phenomenon of cross-reactivity between allergenic proteins plays an important role to understand how the immune system recognizes different antigen proteins. Allergen proteins are known to cross-react if their sequence comparison shows a high sequence identity which also implies that the proteins have a similar 3D fold. In such cases, linear sequence alignment methods are frequently used to predict cross-reactivity between allergenic proteins. However, the prediction of cross-reactivity between distantly related allergens continues to be a challenging task. To overcome this problem, we developed a new structure-based computational method, Cross-React, to predict cross-reactivity between allergenic proteins available in the Structural Database of Allergens (SDAP). Our method is based on the hypothesis that we can find surface patches on 3D structures of potential allergens with amino acid compositions similar to an epitope in a known allergen. We applied the Cross-React method to a diverse set of seven allergens, and successfully identified several cross-reactive allergens with high to moderate sequence identity which have also been experimentally shown to cross-react. Based on these findings, we suggest that Cross-React can be used as a predictive tool to assess protein allergenicity and cross-reactivity.

Availability and Implementation

: Cross-React is available at: http://curie.utmb.edu/Cross-React.html.

Contact

ssnegi@utmb.edu.

Network analysis and in silico prediction of protein-protein interactions with applications in drug discovery

Protein-protein interactions (PPIs) are vital to maintaining cellular homeostasis. Several PPI dysregulations have been implicated in the etiology of various diseases and hence PPIs have emerged as promising targets for drug discovery. Surface residues and hotspot residues at the interface of PPIs form the core regions, which play a key role in modulating cellular processes such as signal transduction and are used as starting points for drug design. In this review, we briefly discuss how PPI networks (PPINs) inferred from experimentally characterized PPI data have been utilized for knowledge discovery and how in silico approaches to PPI characterization can contribute to PPIN-based biological research. Next, we describe the principles of in silico PPI prediction and survey the existing PPI and PPI site prediction servers that are useful for drug discovery. Finally, we discuss the potential of in silico PPI prediction in drug discovery.

Role of Structural Bioinformatics in Drug Discovery by Computational SNP Analysis: Analyzing Variation at the Protein Level

With the completion of the human genome project at the beginning of the 21st century, the biological sciences entered an unprecedented age of data generation, and made its first steps toward an era of personalized medicine. This abundance of sequence data has led to the proliferation of numerous sequence-based techniques for associating variation with disease, such as genome-wide association studies and candidate gene association studies. However, these statistical methods do not provide an understanding of the functional effects of variation. Structure-based drug discovery and design is increasingly incorporating structural bioinformatics techniques to model and analyze protein targets, perform large scale virtual screening to identify hit to lead compounds, and simulate molecular interactions. These techniques are fast, cost-effective, and complement existing experimental techniques such as high throughput sequencing. In this paper, we discuss the contributions of structural bioinformatics to drug discovery, focusing particularly on the analysis of nonsynonymous single nucleotide polymorphisms. We conclude by suggesting a protocol for future analyses of the structural effects of nonsynonymous single nucleotide polymorphisms on proteins and protein complexes.

JET2 Viewer: a database of predicted multiple, possibly overlapping, protein-protein interaction sites for PDB structures

The database JET2 Viewer, openly accessible at http://www.jet2viewer.upmc.fr/, reports putative protein binding sites for all three-dimensional (3D) structures available in the Protein Data Bank (PDB). This knowledge base was generated by applying the computational method JET² at large-scale on more than 20 000 chains. JET² strategy yields very precise predictions of interacting surfaces and unravels their evolutionary process and complexity. JET2 Viewer provides an online intelligent display, including interactive 3D visualization of the binding sites mapped onto PDB structures and suitable files recording JET² analyses. Predictions were evaluated on more than 15 000 experimentally characterized protein interfaces. This is, to our knowledge, the largest evaluation of a protein binding site prediction method. The overall performance of JET² on all interfaces are: Sen = 52.52, PPV = 51.24, Spe = 80.05, Acc = 75.89. The data can be used to foster new strategies for protein-protein interactions modulation and interaction surface redesign.

Modeling and Design of Peptidomimetics to Modulate Protein-Protein Interactions

We describe a modular approach to identify and inhibit protein-protein interactions (PPIs) that are mediated by protein secondary and tertiary structures with rationally designed peptidomimetics. Our analysis begins with entries of high-resolution complexes in the Protein Data Bank and utilizes conformational sampling, scoring, and design capabilities of advanced biomolecular modeling software to develop peptidomimetics.

Computational Approaches for Predicting Binding Partners, Interface Residues, and Binding Affinity of Protein-Protein Complexes

Studying protein-protein interactions leads to a better understanding of the underlying principles of several biological pathways. Cost and labor-intensive experimental techniques suggest the need for computational methods to complement them. Several such state-of-the-art methods have been reported for analyzing diverse aspects such as predicting binding partners, interface residues, and binding affinity for protein-protein complexes with reliable performance. However, there are specific drawbacks for different methods that indicate the need for their improvement. This review highlights various available computational algorithms for analyzing diverse aspects of protein-protein interactions and endorses the necessity for developing new robust methods for gaining deep insights about protein-protein interactions.

Elucidating the druggable interface of protein-protein interactions using fragment docking and coevolutionary analysis

Protein-protein interactions play a central role in cellular function. Improving the understanding of complex formation has many practical applications, including the rational design of new therapeutic agents and the mechanisms governing signal transduction networks. The generally large, flat, and relatively featureless binding sites of protein complexes pose many challenges for drug design. Fragment docking and direct coupling analysis are used in an integrated computational method to estimate druggable protein-protein interfaces. (i) This method explores the binding of fragment-sized molecular probes on the protein surface using a molecular docking-based screen. (ii) The energetically favorable binding sites of the probes, called hot spots, are spatially clustered to map out candidate binding sites on the protein surface. (iii) A coevolution-based interface interaction score is used to discriminate between different candidate binding sites, yielding potential interfacial targets for therapeutic drug design. This approach is validated for important, well-studied disease-related proteins with known pharmaceutical targets, and also identifies targets that have yet to be studied. Moreover, therapeutic agents are proposed by chemically connecting the fragments that are strongly bound to the hot spots.

Structural Dynamics Investigation of Human Family 1 & 2 Cystatin-Cathepsin L1 Interaction: A Comparison of Binding Modes

Cystatin superfamily is a large group of evolutionarily related proteins involved in numerous physiological activities through their inhibitory activity towards cysteine proteases. Despite sharing the same cystatin fold, and inhibiting cysteine proteases through the same tripartite edge involving highly conserved N-terminal region, L1 and L2 loop; cystatins differ widely in their inhibitory affinity towards C1 family of cysteine proteases and molecular details of these interactions are still elusive. In this study, inhibitory interactions of human family 1 & 2 cystatins with cathepsin L1 are predicted and their stability and viability are verified through protein docking & comparative molecular dynamics. An overall stabilization effect is observed in all cystatins on complex formation. Complexes are mostly dominated by van der Waals interaction but the relative participation of the conserved regions varied extensively. While van der Waals contacts prevail in L1 and L2 loop, N-terminal segment chiefly acts as electrostatic interaction site. In fact the comparative dynamics study points towards the instrumental role of L1 loop in directing the total interaction profile of the complex either towards electrostatic or van der Waals contacts. The key amino acid residues surfaced via interaction energy, hydrogen bonding and solvent accessible surface area analysis for each cystatin-cathepsin L1 complex influence the mode of binding and thus control the diverse inhibitory affinity of cystatins towards cysteine proteases.

Molecular dynamics simulations and docking enable to explore the biophysical factors controlling the yields of engineered nanobodies

Nanobodies (VHHs) have proved to be valuable substitutes of conventional antibodies for molecular recognition. Their small size represents a precious advantage for rational mutagenesis based on modelling. Here we address the problem of predicting how Camelidae nanobody sequences can tolerate mutations by developing a simulation protocol based on all-atom molecular dynamics and whole-molecule docking. The method was tested on two sets of nanobodies characterized experimentally for their biophysical features. One set contained point mutations introduced to humanize a wild type sequence, in the second the CDRs were swapped between single-domain frameworks with Camelidae and human hallmarks. The method resulted in accurate scoring approaches to predict experimental yields and enabled to identify the structural modifications induced by mutations. This work is a promising tool for the in silico development of single-domain antibodies and opens the opportunity to customize single functional domains of larger macromolecules.

Thermodynamic Basis of Selectivity in the Interactions of Tissue Inhibitors of Metalloproteinases N-domains with Matrix Metalloproteinases-1, -3, and -14

The four tissue inhibitors of metalloproteinases (TIMPs) are potent inhibitors of the many matrixins (MMPs), except that TIMP1 weakly inhibits some MMPs, including MMP14. The broad-spectrum inhibition of MMPs by TIMPs and their N-domains (NTIMPs) is consistent with the previous isothermal titration calorimetric finding that their interactions are entropy-driven but differ in contributions from solvent and conformational entropy (ΔSsolv, ΔSconf), estimated using heat capacity changes (ΔCp). Selective engineered NTIMPs have potential applications for treating MMP-related diseases, including cancer and cardiomyopathy. Here we report isothermal titration calorimetric studies of the effects of selectivity-modifying mutations in NTIMP1 and NTIMP2 on the thermodynamics of their interactions with MMP1, MMP3, and MMP14. The weak inhibition of MMP14 by NTIMP1 reflects a large conformational entropy penalty for binding. The T98L mutation, peripheral to the NTIMP1 reactive site, enhances binding by increasing ΔSsolv but also reduces ΔSconf However, the same mutation increases NTIMP1 binding to MMP3 in an interaction that has an unusual positive ΔCp This indicates a decrease in solvent entropy compensated by increased conformational entropy, possibly reflecting interactions involving alternative conformers. The NTIMP2 mutant, S2D/S4A is a selective MMP1 inhibitor through electrostatic effects of a unique MMP-1 arginine. Asp-2 increases reactive site polarity, reducing ΔCp, but increases conformational entropy to maintain strong binding to MMP1. There is a strong negative correlation between ΔSsolv and ΔSconf for all characterized interactions, but the data for each MMP have characteristic ranges, reflecting intrinsic differences in the structures and dynamics of their free and inhibitor-bound forms.

Progress and challenges in predicting protein interfaces

The majority of biological processes are mediated via protein-protein interactions. Determination of residues participating in such interactions improves our understanding of molecular mechanisms and facilitates the development of therapeutics. Experimental approaches to identifying interacting residues, such as mutagenesis, are costly and time-consuming and thus, computational methods for this purpose could streamline conventional pipelines. Here we review the field of computational protein interface prediction. We make a distinction between methods which address proteins in general and those targeted at antibodies, owing to the radically different binding mechanism of antibodies. We organize the multitude of currently available methods hierarchically based on required input and prediction principles to provide an overview of the field.

Cysteine redox state plays a key role in the inter-domain movements of HMGB1: a molecular dynamics simulation study

We have modelled and simulated different states of HMGB1, suggesting that the fully reduced HMGB1 maintains the inter-domain movements during the activity.

PPCheck: A Webserver for the Quantitative Analysis of Protein-Protein Interfaces and Prediction of Residue Hotspots

BACKGROUND

Modeling protein-protein interactions (PPIs) using docking algorithms is useful for understanding biomolecular interactions and mechanisms. Typically, a docking algorithm generates a large number of docking poses, and it is often challenging to select the best native-like pose. A further challenge is to recognize key residues, termed as hotspots, at protein-protein interfaces, which contribute more in stabilizing a protein-protein interface.

RESULTS

We had earlier developed a computer algorithm, called PPCheck, which ascribes pseudoenergies to measure the strength of PPIs. Native-like poses could be successfully identified in 27 out of 30 test cases, when applied on a separate set of decoys that were generated using FRODOCK. PPCheck, along with conservation and accessibility scores, was able to differentiate 'native-like and non-native-like poses from 1883 decoys of Critical Assessment of Prediction of Interactions (CAPRI) targets with an accuracy of 60%. PPCheck was trained on a 10-fold mixed dataset and tested on a 10-fold mixed test set for hotspot prediction. We obtain an accuracy of 72%, which is in par with other methods, and a sensitivity of 59%, which is better than most existing methods available for hotspot prediction that uses similar datasets. Other relevant tests suggest that PPCheck can also be reliably used to identify conserved residues in a protein and to perform computational alanine scanning.

CONCLUSIONS

PPCheck webserver can be successfully used to differentiate native-like and non-native-like docking poses, as generated by docking algorithms. The webserver can also be a convenient platform for calculating residue conservation, for performing computational alanine scanning, and for predicting protein-protein interface hotspots. While PPCheck can differentiate the generated decoys into native-like and non-native-like decoys with a fairly good accuracy, the results improve dramatically when features like conservation and accessibility are included. The method can be successfully used in ranking/scoring the decoys, as obtained from docking algorithms.

Structure and function of the N-terminal domain of the human mitochondrial calcium uniporter

The mitochondrial calcium uniporter (MCU) is responsible for mitochondrial calcium uptake and homeostasis. It is also a target for the regulation of cellular anti-/pro-apoptosis and necrosis by several oncogenes and tumour suppressors. Herein, we report the crystal structure of the MCU N-terminal domain (NTD) at a resolution of 1.50 Å in a novel fold and the S92A MCU mutant at 2.75 Å resolution; the residue S92 is a predicted CaMKII phosphorylation site. The assembly of the mitochondrial calcium uniporter complex (uniplex) and the interaction with the MCU regulators such as the mitochondrial calcium uptake-1 and mitochondrial calcium uptake-2 proteins (MICU1 and MICU2) are not affected by the deletion of MCU NTD. However, the expression of the S92A mutant or a NTD deletion mutant failed to restore mitochondrial Ca(2+) uptake in a stable MCU knockdown HeLa cell line and exerted dominant-negative effects in the wild-type MCU-expressing cell line. These results suggest that the NTD of MCU is essential for the modulation of MCU function, although it does not affect the uniplex formation.

Direct and Propagated Effects of Small Molecules on Protein-Protein Interaction Networks

Networks of protein–protein interactions (PPIs) link all aspects of cellular biology. Dysfunction in the assembly or dynamics of PPI networks is a hallmark of human disease, and as such, there is growing interest in the discovery of small molecules that either promote or inhibit PPIs. PPIs were once considered undruggable because of their relatively large buried surface areas and difficult topologies. Despite these challenges, recent advances in chemical screening methodologies, combined with improvements in structural and computational biology have made some of these targets more tractable. In this review, we highlight developments that have opened the door to potent chemical modulators. We focus on how allostery is being used to produce surprisingly robust changes in PPIs, even for the most challenging targets. We also discuss how interfering with one PPI can propagate changes through the broader web of interactions. Through this analysis, it is becoming clear that a combination of direct and propagated effects on PPI networks is ultimately how small molecules re-shape biology.

A hybrid method for protein-protein interface prediction

The growing structural coverage of proteomes is making structural comparison a powerful tool for function annotation. Such template-based approaches are based on the observation that structural similarity is often sufficient to infer similar function. However, it seems clear that, in addition to structural similarity, the specific characteristics of a given protein should also be taken into account in predicting function. Here we describe PredUs 2.0, a method to predict regions on a protein surface likely to bind other proteins, that is, interfacial residues. PredUs 2.0 is based on the PredUs method that is entirely template-based and uses known binding sites in structurally similar proteins to predict interfacial residues. PredUs 2.0 uses a Bayesian approach to combine the template-based scoring of PredUs with a score that reflects the propensities of individual amino acids to be in interfaces. PredUs 2.0 includes a novel protein size dependent metric to determine the number of residues that should be reported as interfacial. PredUs 2.0 significantly outperforms PredUs as well as other published interface prediction methods.

Functional Exposed Amino Acids of BauA as Potential Immunogen Against Acinetobacter baumannii

Multidrug-resistant Acinetobacter baumannii is recognized to be among the most difficult antimicrobial-resistant gram negative bacilli to control and treat. One of the major challenges that the pathogenic bacteria face in their host is the scarcity of freely available iron. To survive under such conditions, bacteria express new proteins on their outer membrane and also secrete iron chelators called siderophores. Antibodies directed against these proteins associated with iron uptake exert a bacteriostatic or bactericidal effect against A. baumanii in vitro, by blocking siderophore mediated iron uptake pathways. Attempts should be made to discover peptides that could mimic protein epitopes and possess the same immunogenicity as the whole protein. Subsequently, theoretical methods for epitope prediction have been developed leading to synthesis of such peptides that are important for development of immunodiagnostic tests and vaccines. The present study was designed to in silico resolving the major obstacles in the control or in prevention of the diseases caused by A. baumannii. We exploited bioinformatic tools to better understand and characterize the Baumannii acinetobactin utilization structure of A. baumannii and select appropriate regions as effective B cell epitopes. In conclusion, amino acids 26-191 of cork domain and 321-635 of part of the barrel domain including L4-L9, were selected as vaccine candidates. These two regions contain functional exposed amino acids with higher score of B cell epitopes properties. Majority of amino acids are hydrophilic, flexible, accessible, and favorable for B cells from secondary structure point of view.

Predicting protein interface residues using easily accessible on-line resources

It has been more than a decade since the completion of the Human Genome Project that provided us with a complete list of human proteins. The next obvious task is to figure out how various parts interact with each other. On that account, we review 10 methods for protein interface prediction, which are freely available as web servers. In addition, we comparatively evaluate their performance on a common data set comprising different quality target structures. We find that using experimental structures and high-quality homology models, structure-based methods outperform those using only protein sequences, with global template-based approaches providing the best performance. For moderate-quality models, sequence-based methods often perform better than those structure-based techniques that rely on fine atomic details. We note that post-processing protocols implemented in several methods quantitatively improve the results only for experimental structures, suggesting that these procedures should be tuned up for computer-generated models. Finally, we anticipate that advanced meta-prediction protocols are likely to enhance interface residue prediction. Notwithstanding further improvements, easily accessible web servers already provide the scientific community with convenient resources for the identification of protein-protein interaction sites.

Algorithmic approaches to protein-protein interaction site prediction

Interaction sites on protein surfaces mediate virtually all biological activities, and their identification holds promise for disease treatment and drug design. Novel algorithmic approaches for the prediction of these sites have been produced at a rapid rate, and the field has seen significant advancement over the past decade. However, the most current methods have not yet been reviewed in a systematic and comprehensive fashion. Herein, we describe the intricacies of the biological theory, datasets, and features required for modern protein-protein interaction site (PPIS) prediction, and present an integrative analysis of the state-of-the-art algorithms and their performance. First, the major sources of data used by predictors are reviewed, including training sets, evaluation sets, and methods for their procurement. Then, the features employed and their importance in the biological characterization of PPISs are explored. This is followed by a discussion of the methodologies adopted in contemporary prediction programs, as well as their relative performance on the datasets most recently used for evaluation. In addition, the potential utility that PPIS identification holds for rational drug design, hotspot prediction, and computational molecular docking is described. Finally, an analysis of the most promising areas for future development of the field is presented.

Studies on the interactions of SAP-1 (an N-terminal truncated form of cystatin S) with its binding partners by CD-spectroscopic and molecular docking methods

SAP-1 is a 113 amino acid long single-chain protein which belongs to the type 2 cystatin gene family. In our previous study, we have purified SAP-1 from human seminal plasma and observed its cross-class inhibitory property. At this time, we report the interaction of SAP-1 with diverse proteases and its binding partners by CD-spectroscopic and molecular docking methods. The circular dichroism (CD) spectroscopic studies demonstrate that the conformation of SAP-1 is changed after its complexation with proteases, and the alterations in protein secondary structure are quantitatively calculated with increase of α-helices and reduction of β-strand content. To get insight into the interactions between SAP-1 and proteases, we make an effort to model the three-dimensional structure of SAP-1 by molecular modeling and verify its stability and viability through molecular dynamics simulations and finally complexed with different proteases using ClusPro 2.0 Server. A high degree of shape complementarity is examined within the complexes, stabilized by a number of hydrogen bonds (HBs) and hydrophobic interactions. Using HB analyses in different protein complexes, we have identified a series of key residues that may be involved in the interactions between SAP-1 and proteases. These findings will assist to understand the mechanism of inhibition of SAP-1 for different proteases and provide intimation for further research.

Allele variants of enterotoxigenic Escherichia coli heat-labile toxin are globally transmitted and associated with colonization factors

Enterotoxigenic Escherichia coli (ETEC) is a significant cause of morbidity and mortality in the developing world. ETEC-mediated diarrhea is orchestrated by heat-labile toxin (LT) and heat-stable toxins (STp and STh), acting in concert with a repertoire of more than 25 colonization factors (CFs). LT, the major virulence factor, induces fluid secretion after delivery of a monomeric ADP-ribosylase (LTA) and its pentameric carrier B subunit (LTB). A study of ETEC isolates from humans in Brazil reported the existence of natural LT variants. In the present study, analysis of predicted amino acid sequences showed that the LT amino acid polymorphisms are associated with a geographically and temporally diverse set of 192 clinical ETEC strains and identified 12 novel LT variants. Twenty distinct LT amino acid variants were observed in the globally distributed strains, and phylogenetic analysis showed these to be associated with different CF profiles. Notably, the most prevalent LT1 allele variants were correlated with major ETEC lineages expressing CS1 + CS3 or CS2 + CS3, and the most prevalent LT2 allele variants were correlated with major ETEC lineages expressing CS5 + CS6 or CFA/I. LTB allele variants generally exhibited more-stringent amino acid sequence conservation (2 substitutions identified) than LTA allele variants (22 substitutions identified). The functional impact of LT1 and LT2 polymorphisms on virulence was investigated by measuring total-toxin production, secretion, and stability using GM1-enzyme-linked immunosorbent assays (GM1-ELISA) and in silico protein modeling. Our data show that LT2 strains produce 5-fold more toxin than LT1 strains (P < 0.001), which may suggest greater virulence potential for this genetic variant. Our data suggest that functionally distinct LT-CF variants with increased fitness have persisted during the evolution of ETEC and have spread globally.

Communication routes in ARID domains between distal residues in helix 5 and the DNA-binding loops

ARID is a DNA-binding domain involved in several transcriptional regulatory processes, including cell-cycle regulation and embryonic development. ARID domains are also targets of the Human Cancer Protein Interaction Network. Little is known about the molecular mechanisms related to conformational changes in the family of ARID domains. Thus, we have examined their structural dynamics to enrich the knowledge on this important family of regulatory proteins. In particular, we used an approach that integrates atomistic simulations and methods inspired by graph theory. To relate these properties to protein function we studied both the free and DNA-bound forms. The interaction with DNA not only stabilizes the conformations of the DNA-binding loops, but also strengthens pre-existing paths in the native ARID ensemble for long-range communication to those loops. Residues in helix 5 are identified as critical mediators for intramolecular communication to the DNA-binding regions. In particular, we identified a distal tyrosine that plays a key role in long-range communication to the DNA-binding loops and that is experimentally known to impair DNA-binding. Mutations at this tyrosine and in other residues of helix 5 are also demonstrated, by our approach, to affect the paths of communication to the DNA-binding loops and alter their native dynamics. Overall, our results are in agreement with a scenario in which ARID domains exist as an ensemble of substates, which are shifted by external perturbation, such as the interaction with DNA. Conformational changes at the DNA-binding loops are transmitted long-range by intramolecular paths, which have their heart in helix 5.

Computational Prediction of Protein-Protein Interaction Networks: Algo-rithms and Resources

Protein interactions play an important role in the discovery of protein functions and pathways in biological processes. This is especially true in case of the diseases caused by the loss of specific protein-protein interactions in the organism. The accuracy of experimental results in finding protein-protein interactions, however, is rather dubious and high throughput experimental results have shown both high false positive beside false negative information for protein interaction. Computational methods have attracted tremendous attention among biologists because of the ability to predict protein-protein interactions and validate the obtained experimental results. In this study, we have reviewed several computational methods for protein-protein interaction prediction as well as describing major databases, which store both predicted and detected protein-protein interactions, and the tools used for analyzing protein interaction networks and improving protein-protein interaction reliability.

Structural bioinformatics and protein docking analysis of the molecular chaperone-kinase interactions: towards allosteric inhibition of protein kinases by targeting the hsp90-cdc37 chaperone machinery

A fundamental role of the Hsp90-Cdc37 chaperone system in mediating maturation of protein kinase clients and supporting kinase functional activity is essential for the integrity and viability of signaling pathways involved in cell cycle control and organism development. Despite significant advances in understanding structure and function of molecular chaperones, the molecular mechanisms and guiding principles of kinase recruitment to the chaperone system are lacking quantitative characterization. Structural and thermodynamic characterization of Hsp90-Cdc37 binding with protein kinase clients by modern experimental techniques is highly challenging, owing to a transient nature of chaperone-mediated interactions. In this work, we used experimentally-guided protein docking to probe the allosteric nature of the Hsp90-Cdc37 binding with the cyclin-dependent kinase 4 (Cdk4) kinase clients. The results of docking simulations suggest that the kinase recognition and recruitment to the chaperone system may be primarily determined by Cdc37 targeting of the N-terminal kinase lobe. The interactions of Hsp90 with the C-terminal kinase lobe may provide additional "molecular brakes" that can lock (or unlock) kinase from the system during client loading (release) stages. The results of this study support a central role of the Cdc37 chaperone in recognition and recruitment of the kinase clients. Structural analysis may have useful implications in developing strategies for allosteric inhibition of protein kinases by targeting the Hsp90-Cdc37 chaperone machinery.

Release of halide ions from the buried active site of the haloalkane dehalogenase LinB revealed by stopped-flow fluorescence analysis and free energy calculations

Release of halide ions is an essential step of the catalytic cycle of haloalkane dehalogenases. Here we describe experimentally and computationally the process of release of a halide anion from the buried active site of the haloalkane dehalogenase LinB. Using stopped-flow fluorescence analysis and umbrella sampling free energy calculations, we show that the anion binding is ion-specific and follows the ordering I(-) > Br(-) > Cl(-). We also address the issue of the protonation state of the catalytic His272 residue and its effect on the process of halide release. While deprotonation of His272 increases binding of anions in the access tunnel, we show that the anionic ordering does not change with the switch of the protonation state. We also demonstrate that a sodium cation could relatively easily enter the active site, provided the His272 residue is singly protonated, and replace thus the missing proton. In contrast, Na(+) is strongly repelled from the active site containing the doubly protonated His272 residue. Our study contributes toward understanding of the reaction mechanism of haloalkane dehalogenase enzyme family. Determination of the protonation state of the catalytic histidine throughout the catalytic cycle remains a challenge for future studies.

Molecular interactions of Bcl-2 and Bcl-xL with mortalin: identification and functional characterization

Bcl-2 family of proteins consists of both pro-apoptotic and anti-apoptotic members that control cellular apoptosis. They predominantly reside in the mitochondria and control the release of apoptotic factors from the mitochondria to the cytosol by regulating its membrane potential and opening the PT (permeability transition) pore. Here we report bioinformatics and biochemical evidence to demonstrate the interaction between Bcl-2 and Bcl-xL with a stress chaperone, mortalin. We demonstrate that such interaction results in the abrogation of mortalin-p53 interaction leading to nuclear translocation and transcriptional reactivation of p53 function that results in an induction of senescence in cancer cells.

Structural characteristics of thermostable immunogenic outer membrane protein from Salmonella enterica serovar Typhi

In this work, we explored the acid-induced unfolding pathway of non-porin outer membrane protein (OMP), an immunogenic protein from Salmonella Typhi, by monitoring the conformational changes over a pH range of 1.0-7.0 by circular dichroism, intrinsic fluorescence, ANS binding, acrylamide quenching, and dynamic light scattering. The spectroscopic measurements showed that OMP in its native state at pH 7.0 exists in more stable and compact conformation. In contrast, at pH 2.0, OMP retains substantial amount of secondary structure, disrupted side chain interactions, increased hydrodynamic radii, and nearly four-fold increase in ANS fluorescence with respect to the native state, indicating that MG state exists at pH 2.0. Quenching of tryptophan fluorescence by acrylamide further confirmed the accumulation of a partially unfolded state between native and unfolded state. The effect of pH on the conformation and thermostability of OMP points towards its heat resistance at neutral pH (T m ~ 69 °C at pH 7.0, monitored by change in MRE222 nm). Acid unfolded state was also characterized by the lack of a cooperative thermal transition. All these results suggested that acid-induced unfolded state of OMP at pH 2.0 represented the molten globule state. The chemical denaturation studies with GuHCl and urea as denaturants showed dissimilar results. The chemical unfolding experiments showed that in both far-UV CD and fluorescence measurements, GuHCl is more efficient than urea. GuHCl is characterized by low C m (~1 M), while urea is characterized by high C m (~3 M). The fully unfolded states were reached at 2 M GuHCl and 4 M urea concentration, respectively. This study adds to several key considerations of importance in the development of therapeutic agents against typhoid fever for clinical purposes.

Predictions of Protein-Protein Interfaces within Membrane Protein Complexes

BACKGROUND

Prediction of interaction sites within the membrane protein complexes using the sequence data is of a great importance, because it would find applications in modification of molecules transport through membrane, signaling pathways and drug targets of many diseases. Nevertheless, it has gained little attention from the protein structural bioinformatics community.

METHODS

In this study, a wide variety of prediction and classification tools were applied to distinguish the residues at the interfaces of membrane proteins from those not in the interfaces.

RESULTS

The tuned SVM model achieved the high accuracy of 86.95% and the AUC of 0.812 which outperforms the results of the only previous similar study. Nevertheless, prediction performances obtained using most employed models cannot be used in applied fields and needs more effort to improve.

CONCLUSION

Considering the variety of the applied tools in this study, the present investigation could be a good starting point to develop more efficient tools to predict the membrane protein interaction site residues.

Molecular cloning, sequencing and structural studies of granulocyte-macrophage colony-stimulating factor (GM-CSF) from Indian water buffalo (Bubalus bubalis)

Granulocyte-macrophage colony-stimulating factor (GM-CSF) is a cytokine that is essential for growth and development of progenitors of granulocytes and monocytes/macrophages. In this study, we report molecular cloning, sequencing and characterization of GM-CSF from Indian water buffalo, Bubalus bubalis. In addition, we performed sequence and structural analysis for buffalo GM-CSF. Buffalo GM-CSF has been compared with 17 mammalian GM-CSFs using multiple sequence alignment and phylogenetic tree. Three-dimensional model for buffalo GM-CSF and human receptor complex was built using homology modelling to study cross-reactivity between two species. Detailed analysis was performed to study GM-CSF interface and various interactions at the interface.

Mutually exclusive binding of APPL(PH) to BAR domain and Reptin regulates β-catenin dependent transcriptional events

Reptin functions in a wide range of biological processes including chromatin remodelling, nucleolar organization and transcriptional regulation of WNT signalling. As β-catenin dependent transcriptional repression and activation events involve binding of Reptin and histone deacetylase 1 to APPL endocytic proteins, this complex has become an important target to identify molecules governing endocytic processes and WNT signalling. Here, we describe the structural basis of APPL binding to Reptin to explore their mode of binding in context with APPL1/APPL2 dimerization. There is an evidence that both PH and BAR domains of APPL proteins exhibit alternately conserved regions involved in hetero-dimerization process and our in-silico data also corroborate this fact. Moreover, APPL2(PH) domain binds to the BAR domain region encompassing a nuclear localization signal. We conclude that APPL(PH) binding to BAR domain and Reptin is mutually exclusive which regulates the nucleocytoplasmic shuttling of Reptin. Furthermore, Reptin is unable to bind with membrane-associated APPL proteins. These observations were further expanded by experimental approaches where we identified a novel point mutation D316N lying in the APPL1(PH) domain which resulted in a significantly reduced binding with Reptin. By luciferase assays, we observed that overexpression of APPL1(D316N) and APPL1(WT) stimulated β-catenin/TCF dependent transcriptional activity in a similar manner which suggested that binding of Reptin to APPL1 is not necessary for β-catenin dependent target gene expression. Overall, our data attempt to highlight a comparative role of APPL proteins in controlling β-catenin dependent transcription mechanism which may improve our understanding of gene regulation.

Towards a better understanding of the specificity of protein-protein interaction

In order to predict interaction interface for proteins, it is crucial to identify their characteristic features controlling the interaction process. We present analysis of 69 crystal structures of dimer protein complexes that provides a basis for reasonable description of the phenomenon. Interaction interfaces of two proteins at amino acids level were localized and described in terms of their chemical composition, binding preferences, and residue interaction energies utilizing Amber empirical force field. The characteristic properties of the interaction interface were compared against set of corresponding intramolecular binding parameters for amino acids in proteins. It has been found that geometrically distinct clusters of large hydrophobic amino acids (leucine, valine, isoleucine, and phenylalanine) as well as polar tyrosines and charged arginines are signatures of the protein-protein interaction interface. At some extent, we can generalize that protein-protein interaction (seen through interaction between amino acids) is very similar to the intramolecular arrangement of amino acids, although intermolecular pairs have generally lower interaction energies with their neighbors. Interfaces, therefore, possess high degree of complementarity suggesting also high selectivity of the process. The utilization of our results can improve interface prediction algorithms and improve our understanding of protein-protein recognition.