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

Mining minimal motif pair sets maximally covering interactions in a protein-protein interaction network

Correlated motif covering (CMC) is the problem of finding a set of motif pairs, i.e., pairs of patterns, in the sequences of proteins from a protein-protein interaction network (PPI-network) that describe the interactions in the network as concisely as possible. In other words, a perfect solution for CMC would be a minimal set of motif pairs that describes the interaction behavior perfectly in the sense that two proteins from the network interact if and only if their sequences match a motif pair in the minimal set. In this paper, we introduce and formally define CMC and show that it is closely related to the red-blue set cover (RBSC) problem and its weighted version (WRBSC)--both well-known NP-hard problems for that there exist several algorithms with known approximation factor guarantees. We prove the hardness of approximation of CMC by providing an approximation factor preserving reduction from RBSC to CMC. We show the existence of a theoretical approximation algorithm for CMC by providing an approximation factor preserving reduction from CMC to WRBSC. We adapt the latter algorithm into a functional heuristic for CMC, called CMC-approx, and experimentally assess its performance and biological relevance. The implementation in Java can be found at >http://bioinformatics.uhasselt.be.

In silico prediction of a disease-associated STIL mutant and its affect on the recruitment of centromere protein J (CENPJ)

Human STIL (SCL/TAL1 interrupting locus) protein maintains centriole stability and spindle pole localisation. It helps in recruitment of CENPJ (Centromere protein J)/CPAP (centrosomal P4.1-associated protein) and other centrosomal proteins. Mutations in STIL protein are reported in several disorders, especially in deregulation of cell cycle cascades. In this work, we examined the non-synonymous single nucleotide polymorphisms (nsSNPs) reported in STIL protein for their disease association. Different SNP prediction tools were used to predict disease-associated nsSNPs. Our evaluation technique predicted rs147744459 (R242C) as a highly deleterious disease-associated nsSNP and its interaction behaviour with CENPJ protein. Molecular modelling, docking and molecular dynamics simulation were conducted to examine the structural consequences of the predicted disease-associated mutation. By molecular dynamic simulation we observed structural consequences of R242C mutation which affects interaction of STIL and CENPJ functional domains. The result obtained in this study will provide a biophysical insight into future investigations of pathological nsSNPs using a computational platform.

Fine-tuning multiprotein complexes using small molecules

Multiprotein complexes such as the transcriptional machinery, signaling hubs, and protein folding machines are typically composed of at least one enzyme combined with multiple non-enzymes. Often the components of these complexes are incorporated in a combinatorial manner, in which the ultimate composition of the system helps dictate the type, location, or duration of cellular activities. Although drugs and chemical probes have traditionally targeted the enzyme components, emerging strategies call for controlling the function of protein complexes by modulation of protein-protein interactions (PPIs). However, the challenges of targeting PPIs have been well documented, and the diversity of PPIs makes a "one-size-fits-all" solution highly unlikely. These hurdles are particularly daunting for PPIs that encompass large buried surface areas and those with weak affinities. In this Review, we discuss lessons from natural systems, in which allostery and other mechanisms are used to overcome the challenge of regulating the most difficult PPIs. These systems may provide a blueprint for identifying small molecules that target challenging PPIs and affecting molecular decision-making within multiprotein systems.

Modelling family 2 cystatins and their interaction with papain

Cystatins are extensively studied cysteine protease inhibitors, found in wide range of organisms with highly conserved structural folds. S-type of cystatins is well known for their abundance in saliva, high selectivity and poorer activity towards host cysteine proteases in comparison to their immediate ancestor cystatin C. Despite more than 90% sequence similarity, the members of this group show highly dissimilar binding affinity towards papain. Cystatin M/E is a potent inhibitor of legumain and papain like cysteine proteases and recognized for its involvement in skin barrier formation and potential role as a tumor suppressor gene. However, the structures of these proteins and their complexes with papain or legumain are still unknown. In the present study, we have employed computational methods to get insight into the interactions between papain and cystatins. Three-dimensional structures of the cystatins are generated by homology modelling, refined with molecular dynamics simulation, validated through numerous web servers and finally complexed with papain using ZDOCK algorithm in Discovery Studio. A high degree of shape complementarity is observed within the complexes, stabilized by numerous hydrogen bonds (HB) and hydrophobic interactions. Using interaction energy, HB and solvent accessible surface area analyses, we have identified a series of key residues that may be involved in papain-cystatin interaction. Differential approaches of cystatins towards papain are also noticed which are possibly responsible for diverse inhibitory activity within the group. These findings will improve our understanding of fundamental inhibitory mechanisms of cystatin and provide clues for further research.

Base of the measles virus fusion trimer head receives the signal that triggers membrane fusion

The measles virus (MV) fusion (F) protein trimer executes membrane fusion after receiving a signal elicited by receptor binding to the hemagglutinin (H) tetramer. Where and how this signal is received is understood neither for MV nor for other paramyxoviruses. Because only the prefusion structure of the parainfluenza virus 5 (PIV5) F-trimer is available, to study signal receipt by the MV F-trimer, we generated and energy-refined a homology model. We used two approaches to predict surface residues of the model interacting with other proteins. Both approaches measured interface propensity values for patches of residues. The second approach identified, in addition, individual residues based on the conservation of physical chemical properties among F-proteins. Altogether, about 50 candidate interactive residues were identified. Through iterative cycles of mutagenesis and functional analysis, we characterized six residues that are required specifically for signal transmission; their mutation interferes with fusion, although still allowing efficient F-protein processing and cell surface transport. One residue is located adjacent to the fusion peptide, four line a cavity in the base of the F-trimer head, while the sixth residue is located near this cavity. Hydrophobic interactions in the cavity sustain the fusion process and contacts with H. The cavity is flanked by two different subunits of the F-trimer. Tetrameric H-stalks may be lodged in apposed cavities of two F-trimers. Because these insights are based on a PIV5 homology model, the signal receipt mechanism may be conserved among paramyxoviruses.

Structural insights of rohu TLR3, its binding site analysis with fish reovirus dsRNA, poly I:C and zebrafish TRIF

In response to double stranded RNA (dsRNA) viruses, toll-like receptor 3 (TLR3) in fish activates signaling like human, and induces innate immunity. This suggested the existence of dsRNA binding domains in fish TLR3 as reported in higher vertebrates. In in silico analysis, leucine rich repeat (LRR) regions (4-6, 13-14, 20-22), and LRR (8-15, 17-24) were identified as key domains in rohu TLR3 as poly I:C and dsRNA of fish reovirus (AGCRV,VHSV and IHNV) binding regions. 3D-models of rohu TLR3-TIR and zebrafish TRIF were generated by homology and ab initio modeling respectively, and their interacting domains were predicted. This is the first report of TLR3 modeling in fish.

Validation of a phage display and computational algorithm by mapping a conformational epitope of Bla g 2

BACKGROUND

Bla g 2, one of the major cockroach allergens, induces a strong IgE response against conformational epitopes, and on reexposure, sensitized individuals often display symptoms of allergic rhinitis and asthma. The aim of the current study was to perform a test of the efficacy of a modified phage display screening, characterization of selected phages and an automated algorithm, EpiSearch, in locating an important conformational epitope.

METHODS

The monoclonal antibody 7C11, which partially inhibits the binding of patient IgE antibodies to Bla g 2, was used to screen a random peptide phage library. After 3 rounds of panning, 32 phage clones were isolated and the amino acid sequences of their peptides were determined. The relative affinity and specificity of the binding of these peptides to 7C11 were tested in ELISAs. The amino acid composition of these peptides was then matched with clusters of residues on the surface of the 3-dimensional (3D) structure of Bla g 2, using our EpiSearch algorithm.

RESULTS

The amino acid sequences of the peptides on selected phages differed at only one position, occupied by 1 of 2 negatively charged residues. The two 12-mer sequences bound to 7C11 with similar avidity and specificity. There was good concordance between the residues in the 3D clusters identified from our phage display/computational method with the co-crystal structural analysis.

CONCLUSION

Conformational epitopes may be mapped through screening of clones from random peptide phage display libraries and EpiSearch.

COCOMAPS: a web application to analyze and visualize contacts at the interface of biomolecular complexes

SUMMARY

Herein we present COCOMAPS, a novel tool for analyzing, visualizing and comparing the interface in protein-protein and protein-nucleic acids complexes. COCOMAPS combines traditional analyses and 3D visualization of the interface with the effectiveness of intermolecular contact maps.

AVAILABILITY

COCOMAPS is accessible as a public web tool at http://www.molnac.unisa.it/BioTools/cocomaps

CONTACT

romina.oliva@uniparthenope.it; lcavallo@unisa.it.

i-Patch: interprotein contact prediction using local network information

Biological processes are commonly controlled by precise protein-protein interactions. These connections rely on specific amino acids at the binding interfaces. Here we predict the binding residues of such interprotein complexes. We have developed a suite of methods, i-Patch, which predict the interprotein contact sites by considering the two proteins as a network, with residues as nodes and contacts as edges. i-Patch starts with two proteins, A and B, which are assumed to interact, but for which the structure of the complex is not available. However, we assume that for each protein, we have a reference structure and a multiple sequence alignment of homologues. i-Patch then uses the propensities of patches of residues to interact, to predict interprotein contact sites. i-Patch outperforms several other tested algorithms for prediction of interprotein contact sites. It gives 59% precision with 20% recall on a blind test set of 31 protein pairs. Combining the i-Patch scores with an existing correlated mutation algorithm, McBASC, using a logistic model gave little improvement. Results from a case study, on bacterial chemotaxis protein complexes, demonstrate that our predictions can identify contact residues, as well as suggesting unknown interfaces in multiprotein complexes.

A holistic molecular docking approach for predicting protein-protein complex structure

A holistic protein-protein molecular docking approach, HoDock, was established, composed of such steps as binding site prediction, initial complex structure sampling, refined complex structure sampling, structure clustering, scoring and final structure selection. This article explains the detailed steps and applications for CAPRI Target 39. The CAPRI result showed that three predicted binding site residues, A191HIS, B512ARG and B531ARG, were correct, and there were five submitted structures with a high fraction of correct receptor-ligand interface residues, indicating that this docking approach may improve prediction accuracy for protein-protein complex structures.

Prediction of protein-protein interaction sites using electrostatic desolvation profiles

Protein-protein complex formation involves removal of water from the interface region. Surface regions with a small free energy penalty for water removal or desolvation may correspond to preferred interaction sites. A method to calculate the electrostatic free energy of placing a neutral low-dielectric probe at various protein surface positions has been designed and applied to characterize putative interaction sites. Based on solutions of the finite-difference Poisson equation, this method also includes long-range electrostatic contributions and the protein solvent boundary shape in contrast to accessible-surface-area-based solvation energies. Calculations on a large set of proteins indicate that in many cases (>90%), the known binding site overlaps with one of the six regions of lowest electrostatic desolvation penalty (overlap with the lowest desolvation region for 48% of proteins). Since the onset of electrostatic desolvation occurs even before direct protein-protein contact formation, it may help guide proteins toward the binding region in the final stage of complex formation. It is interesting that the probe desolvation properties associated with residue types were found to depend to some degree on whether the residue was outside of or part of a binding site. The probe desolvation penalty was on average smaller if the residue was part of a binding site compared to other surface locations. Applications to several antigen-antibody complexes demonstrated that the approach might be useful not only to predict protein interaction sites in general but to map potential antigenic epitopes on protein surfaces.

Computational approaches for protein function prediction: a combined strategy from multiple sequence alignment to molecular docking-based virtual screening

The functional characterization of proteins represents a daily challenge for biochemical, medical and computational sciences. Although finally proved on the bench, the function of a protein can be successfully predicted by computational approaches that drive the further experimental assays. Current methods for comparative modeling allow the construction of accurate 3D models for proteins of unknown structure, provided that a crystal structure of a homologous protein is available. Binding regions can be proposed by using binding site predictors, data inferred from homologous crystal structures, and data provided from a careful interpretation of the multiple sequence alignment of the investigated protein and its homologs. Once the location of a binding site has been proposed, chemical ligands that have a high likelihood of binding can be identified by using ligand docking and structure-based virtual screening of chemical libraries. Most docking algorithms allow building a list sorted by energy of the lowest energy docking configuration for each ligand of the library. In this review the state-of-the-art of computational approaches in 3D protein comparative modeling and in the study of protein-ligand interactions is provided. Furthermore a possible combined/concerted multistep strategy for protein function prediction, based on multiple sequence alignment, comparative modeling, binding region prediction, and structure-based virtual screening of chemical libraries, is described by using suitable examples. As practical examples, Abl-kinase molecular modeling studies, HPV-E6 protein multiple sequence alignment analysis, and some other model docking-based characterization reports are briefly described to highlight the importance of computational approaches in protein function prediction.

Amyloidogenic regions and interaction surfaces overlap in globular proteins related to conformational diseases

Protein aggregation underlies a wide range of human disorders. The polypeptides involved in these pathologies might be intrinsically unstructured or display a defined 3D-structure. Little is known about how globular proteins aggregate into toxic assemblies under physiological conditions, where they display an initially folded conformation. Protein aggregation is, however, always initiated by the establishment of anomalous protein-protein interactions. Therefore, in the present work, we have explored the extent to which protein interaction surfaces and aggregation-prone regions overlap in globular proteins associated with conformational diseases. Computational analysis of the native complexes formed by these proteins shows that aggregation-prone regions do frequently overlap with protein interfaces. The spatial coincidence of interaction sites and aggregating regions suggests that the formation of functional complexes and the aggregation of their individual subunits might compete in the cell. Accordingly, single mutations affecting complex interface or stability usually result in the formation of toxic aggregates. It is suggested that the stabilization of existing interfaces in multimeric proteins or the formation of new complexes in monomeric polypeptides might become effective strategies to prevent disease-linked aggregation of globular proteins.

The aggregation of proteins in tissues is associated with the pathogenesis of more than 40 human diseases. The polypeptides underlying disorders such as Alzheimer's and Parkinson's are devoid of any regular structure, whereas the polypeptides causing familial amyotrophic lateral sclerosis or nonneuropathic systemic amyloidosis correspond to globular proteins. Little is known about the mechanism by which globular proteins under physiological conditions aggregate from their initially folded and soluble conformations. Interestingly, several of these pathogenic proteins display quaternary structure or are bound to other proteins in their physiological context. In the present work, we show that protein-protein interaction surfaces and regions with high aggregation propensity significantly overlap in these polypeptides. This suggests that the formation of native complexes and self-aggregation reactions probably compete in the cell, explaining why point mutations affecting the interface or the stability of the protein complex lead in many cases to the formation of toxic aggregates. This study proposes general strategies to fight against diseases associated with the deposition of globular polypeptides.

Automated detection of conformational epitopes using phage display Peptide sequences

Background:

Precise determination of conformational epitopes of neutralizing antibodies represents a key step in the rational design of novel vaccines. A powerful experimental method to gain insights on the physical chemical nature of conformational epitopes is the selection of linear peptides that bind with high affinities to a monoclonal antibody of interest by phage display technology. However, the structural characterization of conformational epitopes from these mimotopes is not straightforward, and in the past the interpretation of peptide sequences from phage display experiments focused on linear sequence analysis to find a consensus sequence or common sequence motifs.

Results:

We present a fully automated search method, EpiSearch that predicts the possible location of conformational epitopes on the surface of an antigen. The algorithm uses peptide sequences from phage display experiments as input, and ranks all surface exposed patches according to the frequency distribution of similar residues in the peptides and in the patch. We have tested the performance of the EpiSearch algorithm for six experimental data sets of phage display experiments, the human epidermal growth factor receptor-2 (HER-2/neu), the antibody mAb Bo2C11 targeting the C₂ domain of FVIII, antibodies mAb 17b and mAb b12 of the HIV envelope protein gp120, mAb 13b5 targeting HIV-1 capsid protein and 80R of the SARS coronavirus spike protein. In all these examples the conformational epitopes as determined by the X-ray crystal structures of the antibody-antigen complexes, were found within the highest scoring patches of EpiSearch, covering in most cases more than 50% residues of experimental observed conformational epitopes. Input options of the program include mapping of a single peptide or a set of peptides on the antigen structure, and the results of the calculation can be visualized on our interactive web server.

Availability:

Users can access the EpiSearch from our web server http://curie.utmb.edu/episearch.html

Vaccinia virus G8R protein: a structural ortholog of proliferating cell nuclear antigen (PCNA)

Background

Eukaryotic DNA replication involves the synthesis of both a DNA leading and lagging strand, the latter requiring several additional proteins including flap endonuclease (FEN-1) and proliferating cell nuclear antigen (PCNA) in order to remove RNA primers used in the synthesis of Okazaki fragments. Poxviruses are complex viruses (dsDNA genomes) that infect eukaryotes, but surprisingly little is known about the process of DNA replication. Given our previous results that the vaccinia virus (VACV) G5R protein may be structurally similar to a FEN-1-like protein and a recent finding that poxviruses encode a primase function, we undertook a series of in silico analyses to identify whether VACV also encodes a PCNA-like protein.

Results

An InterProScan of all VACV proteins using the JIPS software package was used to identify any PCNA-like proteins. The VACV G8R protein was identified as the only vaccinia protein that contained a PCNA-like sliding clamp motif. The VACV G8R protein plays a role in poxvirus late transcription and is known to interact with several other poxvirus proteins including itself. The secondary and tertiary structure of the VACV G8R protein was predicted and compared to the secondary and tertiary structure of both human and yeast PCNA proteins, and a high degree of similarity between all three proteins was noted.

Conclusions

The structure of the VACV G8R protein is predicted to closely resemble the eukaryotic PCNA protein; it possesses several other features including a conserved ubiquitylation and SUMOylation site that suggest that, like its counterpart in T4 bacteriophage (gp45), it may function as a sliding clamp ushering transcription factors to RNA polymerase during late transcription.

A survey of available tools and web servers for analysis of protein-protein interactions and interfaces

The unanimous agreement that cellular processes are (largely) governed by interactions between proteins has led to enormous community efforts culminating in overwhelming information relating to these proteins; to the regulation of their interactions, to the way in which they interact and to the function which is determined by these interactions. These data have been organized in databases and servers. However, to make these really useful, it is essential not only to be aware of these, but in particular to have a working knowledge of which tools to use for a given problem; what are the tool advantages and drawbacks; and no less important how to combine these for a particular goal since usually it is not one tool, but some combination of tool-modules that is needed. This is the goal of this review.

Detection of functionally important regions in "hypothetical proteins" of known structure

Structural genomics initiatives provide ample structures of "hypothetical proteins" (i.e., proteins of unknown function) at an ever increasing rate. However, without function annotation, this structural goldmine is of little use to biologists who are interested in particular molecular systems. To this end, we used (an improved version of) the PatchFinder algorithm for the detection of functional regions on the protein surface, which could mediate its interactions with, e.g., substrates, ligands, and other proteins. Examination, using a data set of annotated proteins, showed that PatchFinder outperforms similar methods. We collected 757 structures of hypothetical proteins and their predicted functional regions in the N-Func database. Inspection of several of these regions demonstrated that they are useful for function prediction. For example, we suggested an interprotein interface and a putative nucleotide-binding site. A web-server implementation of PatchFinder and the N-Func database are available at http://patchfinder.tau.ac.il/.

Applications of bioinformatics to protein structures: how protein structure and bioinformatics overlap

In this chapter, we will focus on the role of bioinformatics to analyze a protein after its protein structure has been determined. First, we present how to validate protein structures for quality assurance. Then, we discuss how to analyze protein-protein interfaces and how to predict the biomolecule which is the biological oligomeric state of the protein. Finally, we discuss how to search for homologs based on the 3-D structure which is an essential step for understanding protein function.

Structural analysis of linear and conformational epitopes of allergens

In many countries regulatory agencies have adopted safety guidelines, based on bioinformatics rules from the WHO/FAO and EFSA recommendations, to prevent potentially allergenic novel foods or agricultural products from reaching consumers. We created the Structural Database of Allergenic Proteins (SDAP, http://fermi.utmb.edu/SDAP/) to combine data that had previously been available only as flat files on Web pages or in the literature. SDAP was designed to be user friendly, to be of maximum use to regulatory agencies, clinicians, as well as to scientists interested in assessing the potential allergenic risk of a protein. We developed methods, unique to SDAP, to compare the physicochemical properties of discrete areas of allergenic proteins to known IgE epitopes. We developed a new similarity measure, the property distance (PD) value that can be used to detect related segments in allergens with clinical observed cross-reactivity. We have now expanded this work to obtain experimental validation of the PD index as a quantitative predictor of IgE cross-reactivity, by designing peptide variants with predetermined PD scores relative to known IgE epitopes. In complementary work we show how sequence motifs characteristic of allergenic proteins in protein families can be used as fingerprints for allergenicity.

PilF is an outer membrane lipoprotein required for multimerization and localization of the Pseudomonas aeruginosa Type IV pilus secretin

Type IV pili (T4P) are retractile appendages that contribute to the virulence of bacterial pathogens. PilF is a Pseudomonas aeruginosa lipoprotein that is essential for T4P biogenesis. Phenotypic characterization of a pilF mutant confirmed that T4P-mediated functions are abrogated: T4P were no longer present on the cell surface, twitching motility was abolished, and the mutant was resistant to infection by T4P retraction-dependent bacteriophage. The results of cellular fractionation studies indicated that PilF is the outer membrane pilotin required for the localization and multimerization of the secretin, PilQ. Mutation of the putative PilF lipidation site untethered the protein from the outer membrane, causing secretin assembly in both inner and outer membranes. T4P-mediated twitching motility and bacteriophage susceptibility were moderately decreased in the lipidation site mutant, while cell surface piliation was substantially reduced. The tethering of PilF to the outer membrane promotes the correct localization of PilQ and appears to be required for the formation of stable T4P. Our 2.0-A structure of PilF revealed a superhelical arrangement of six tetratricopeptide protein-protein interaction motifs that may mediate the contacts with PilQ during secretin assembly. An alignment of pseudomonad PilF sequences revealed three highly conserved surfaces that may be involved in PilF function.

Dynamic interaction of the measles virus hemagglutinin with its receptor signaling lymphocytic activation molecule (SLAM, CD150)

The interaction of measles virus with its receptor signaling lymphocytic activation molecule (SLAM) controls cell entry and governs tropism. We predicted potential interface areas of the measles virus attachment protein hemagglutinin to begin the investigation. We then assessed the relevance of individual amino acids located in these areas for SLAM-binding and SLAM-dependent membrane fusion, as measured by surface plasmon resonance and receptor-specific fusion assays, respectively. These studies identified one hemagglutinin protein residue, isoleucine 194, which is essential for primary binding. The crystal structure of the hemagglutinin-protein localizes Ile-194 at the interface of propeller blades 5 and 6, and our data indicate that a small aliphatic side chain of residue 194 stabilizes a protein conformation conducive to binding. In contrast, a quartet of residues previously shown to sustain SLAM-dependent fusion is not involved in binding. Instead, our data prove that after binding, this quartet of residues on propeller blade 5 conducts conformational changes that are receptor-specific. Our study sets a structure-based stage for understanding how the SLAM-elicited conformational changes travel through the H-protein ectodomain before triggering fusion protein unfolding and membrane fusion.