Accurate Prediction of Peptide Binding Sites on Protein Surfaces

Many important protein–protein interactions are mediated by the binding of a short peptide stretch in one protein to a large globular segment in another. Recent efforts have provided hundreds of examples of new peptides binding to proteins for which a three-dimensional structure is available (either known experimentally or readily modeled) but where no structure of the protein–peptide complex is known. To address this gap, we present an approach that can accurately predict peptide binding sites on protein surfaces. For peptides known to bind a particular protein, the method predicts binding sites with great accuracy, and the specificity of the approach means that it can also be used to predict whether or not a putative or predicted peptide partner will bind. We used known protein–peptide complexes to derive preferences, in the form of spatial position specific scoring matrices, which describe the binding-site environment in globular proteins for each type of amino acid in bound peptides. We then scan the surface of a putative binding protein for sites for each of the amino acids present in a peptide partner and search for combinations of high-scoring amino acid sites that satisfy constraints deduced from the peptide sequence. The method performed well in a benchmark and largely agreed with experimental data mapping binding sites for several recently discovered interactions mediated by peptides, including RG-rich proteins with SMN domains, Epstein-Barr virus LMP1 with TRADD domains, DBC1 with Sir2, and the Ago hook with Argonaute PIWI domain. The method, and associated statistics, is an excellent tool for predicting and studying binding sites for newly discovered peptides mediating critical events in biology.     

Discarding functional residues from the substitution table improves predictions of active sites within three-dimensional structures

Substitutions of individual amino acids in proteins may be under very different evolutionary restraints depending on their structural and functional roles. The Environment Specific Substitution Table (ESST) describes the pattern of substitutions in terms of amino acid location within elements of secondary structure, solvent accessibility, and the existence of hydrogen bonds between side chains and neighbouring amino acid residues. Clearly amino acids that have very different local environments in their functional state compared to those in the protein analysed will give rise to inconsistencies in the calculation of amino acid substitution tables. Here, we describe how the calculation of ESSTs can be improved by discarding the functional residues from the calculation of substitution tables. Four categories of functions are examined in this study: protein–protein interactions, protein–nucleic acid interactions, protein–ligand interactions, and catalytic activity of enzymes. Their contributions to residue conservation are measured and investigated. We test our new ESSTs using the program CRESCENDO, designed to predict functional residues by exploiting knowledge of amino acid substitutions, and compare the benchmark results with proteins whose functions have been defined experimentally. The new methodology increases the Z-score by 98% at the active site residues and finds 16% more active sites compared with the old ESST. We also find that discarding amino acids responsible for protein–protein interactions helps in the prediction of those residues although they are not as conserved as the residues of active sites. Our methodology can make the substitution tables better reflect and describe the substitution patterns of amino acids that are under structural restraints only.     

A novel strategy for the identification of protein–DNA contacts by photocrosslinking and mass spectrometry

Photochemical crosslinking is a method for studying the molecular details of protein–nucleic acid interactions. In this study, we describe a novel strategy to localize crosslinked amino acid residues that combines laser-induced photocrosslinking, proteolytic digestion, Fe³⁺-IMAC (immobilized metal affinity chromatography) purification of peptide–oligodeoxynucleotide heteroconjugates and hydrolysis of oligodeoxynucleotides by hydrogen fluoride (HF), with efficient matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS). The new method is illustrated by the identification of the DNA-binding site of the restriction endonuclease MboI. Photoactivatable 5-iododeoxyuridine was incorporated into a single site within the DNA recognition sequence (GATC) of MboI. Ultraviolet irradiation of the protein–DNA complex with a helium/cadmium laser at 325 nm resulted in 15% crosslinking yield. Proteolytic digestion with different proteases produced various peptide–oligodeoxynucleotide adducts that were purified together with free oligodeoxynucleotide by Fe³⁺-IMAC. A combination of MS analysis of the peptide–nucleosides obtained after hydrolysis by HF and their fragmentation by MS/MS revealed that Lys²⁰⁹ of MboI was crosslinked to the MboI recognition site at the position of the adenine, demonstrating that the region around Lys²⁰⁹ is involved in specific binding of MboI to its DNA substrate. This method is suitable for the fast identification of the site of contact between proteins and nucleic acids starting from picomole quantities of crosslinked complexes.     

A novel far-red bimolecular fluorescence complementation system that allows for efficient visualization of protein interactions under physiological conditions

Fluorescent protein (FP) has enabled the analysis of biomolecular interactions in living cells, and bimolecular fluorescence complementation (BiFC) represents one of the newly developed imaging technologies to directly visualize protein–protein interactions in living cells. Although 10 different FPs that cover a broad range of spectra have been demonstrated to support BiFC, only Cerulean (cyan FP variant), Citrine and Venus (yellow FP variants)-based BiFC systems can be used under 37 °C physiological temperature. The sensitivity of two mRFP-based red BiFC systems to higher temperatures (i.e., 37 °C) limits their applications in most mammalian cell-based studies. Here we report that mLumin, a newly isolated far-red fluorescent protein variant of mKate with an emission maximum of 621 nm, enables BiFC analysis of protein–protein interactions at 37 °C in living mammalian cells. Furthermore, the combination of mLumin with Cerulean- and Venus-based BiFC systems allows for simultaneous visualization of three pairs of protein–protein interactions in the same cell. The mLumin-based BiFC system will facilitate simultaneous visualization of multiple protein–protein interactions in living cells and offer the potential to visualize protein–protein interactions in living animals.     

Purification of MAP–kinase protein complexes and identification of candidate components by XL–TAP–MS

The purification of low-abundance protein complexes and detection of in vivo protein–protein interactions in complex biological samples remains a challenging task. Here, we devised crosslinking and tandem affinity purification coupled to mass spectrometry (XL–TAP–MS), a quantitative proteomics approach for analyzing tandem affinity-purified, crosslinked protein complexes from plant tissues. We exemplarily applied XL–TAP–MS to study the MKK2–Mitogen-activated protein kinase (MPK4) signaling module in Arabidopsis thaliana. A tandem affinity tag consisting of an in vivo-biotinylated protein domain flanked by two hexahistidine sequences was adopted to allow for the affinity-based isolation of formaldehyde–crosslinked protein complexes under fully denaturing conditions. Combined with ¹⁵N stable isotopic labeling and tandem MS we captured and identified a total of 107 MKK2–MPK4 module-interacting proteins. Consistent with the role of the MPK signaling module in plant immunity, many of the module-interacting proteins are involved in the biotic and abiotic stress response of Arabidopsis. Validation of binary protein–protein interactions by in planta split-luciferase assays and in vitro kinase assays disclosed several direct phosphorylation targets of MPK4. Together, the XL–TAP–MS approach purifies low abundance protein complexes from biological samples and discovers previously unknown protein–protein interactions.

XL–TAP–MS: a novel technique that allows purification of crosslinked, low abundant protein complexes from plant tissues under denatured conditions and detection of in vivo protein–protein interactions.     

Mass spectrometry‐based protein–protein interaction networks for the study of human diseases

A better understanding of the molecular mechanisms underlying disease is key for expediting the development of novel therapeutic interventions. Disease mechanisms are often mediated by interactions between proteins. Insights into the physical rewiring of protein–protein interactions in response to mutations, pathological conditions, or pathogen infection can advance our understanding of disease etiology, progression, and pathogenesis and can lead to the identification of potential druggable targets. Advances in quantitative mass spectrometry (MS)‐based approaches have allowed unbiased mapping of these disease‐mediated changes in protein–protein interactions on a global scale. Here, we review MS techniques that have been instrumental for the identification of protein–protein interactions at a system‐level, and we discuss the challenges associated with these methodologies as well as novel MS advancements that aim to address these challenges. An overview of examples from diverse disease contexts illustrates the potential of MS‐based protein–protein interaction mapping approaches for revealing disease mechanisms, pinpointing new therapeutic targets, and eventually moving toward personalized applications.     

Interaction of Saccharomyces Cdc13p with Pol1p, Imp4p, Sir4p and Zds2p is involved in telomere replication, telomere maintenance and cell growth control

Telomeres are the physical ends of eukaryotic chromosomes. They are important for maintaining the integrity of chromosomes and this function is mediated through a number of protein factors. In Saccharomyces cerevisiae, Cdc13p binds to telomeres and affects telomere maintenance, telomere position effects and cell cycle progression through G₂/M phase. We identified four genes encoding Pol1p, Sir4p, Zds2p and Imp4p that interact with amino acids 1–252 of Cdc13p using a yeast two-hybrid screening system. Interactions of these four proteins with Cdc13p were through direct protein–protein interactions as judged by in vitro pull-down assays. Direct protein–protein interactions were also observed between Pol1p–Imp4p, Pol1p–Sir4p and Sir4p–Zds2p, whereas no interaction was detected between Imp4p–Sir4p and Zds2p–Imp4p, suggesting that protein interactions were specific in the complex. Pol1p was shown to interact with Cdc13p. Here we show that Zds2p and Imp4p also form a stable complex with Cdc13p in yeast cells, because Zds2p and Imp4p co-immunoprecipitate with Cdc13p, whereas Sir4p does not. The function of the N-terminal 1–252 region of Cdc13p was also analyzed. Expressing Cdc13(252–924)p, which lacks amino acids 1–252 of Cdc13p, causes defects in progressive cell growth and eventually arrested in the G₂/M phase of the cell cycle. These growth defects were not caused by progressive shortening of telomeres because telomeres in these cells were long. Point mutants in the amino acids 1–252 region of Cdc13p that reduced the interaction between Cdc13p and its binding proteins resulted in varying level of defects in cell growth and telomeres. These results indicate that the interactions between Cdc13(1–252)p and its binding proteins are important for the function of Cdc13p in telomere regulation and cell growth. Together, our results provide evidence for the formation of a Cdc13p-mediated telosome complex through its N-terminal region that is involved in telomere maintenance, telomere length regulation and cell growth control.     

Structure-based method for analyzing protein–protein interfaces

Hydrogen bond, hydrophobic and vdW interactions are the three major non-covalent interactions at protein–protein interfaces. We have developed a method that uses only these properties to describe interactions between proteins, which can qualitatively estimate the individual contribution of each interfacial residue to the binding and gives the results in a graphic display way. This method has been applied to analyze alanine mutation data at protein–protein interfaces. A dataset containing 13 protein–protein complexes with 250 alanine mutations of interfacial residues has been tested. For the 75 hot-spot residues (G1.5 kcal mol^-1), 66 can be predicted correctly with a success rate of 88%. In order to test the tolerance of this method to conformational changes upon binding, we utilize a set of 26 complexes with one or both of their components available in the unbound form. The difference of key residues exported by the program is 11% between the results using complexed proteins and those from unbound ones. As this method gives the characteristics of the binding partner for a particular protein, in-depth studies on protein–protein recognition can be carried out. Furthermore, this method can be used to compare the difference between protein–protein interactions and look for correlated mutation. Figure Key interaction grids at the interface between barnase and barstar. Key interaction grid for barnase and barstar are presented in one figure according to their coordinates. In order to distinguish the two proteins, different icons were assigned. Crosses represent key grids for barstar and dots represent key grids for barnase. The four residues in ball and stick are Asp40 in barstar and Arg83, Arg87, His102 in barnase.     

Assessment of the optimization of affinity and specificity at protein–DNA interfaces

The biological functions of DNA-binding proteins often require that they interact with their targets with high affinity and/or high specificity. Here, we describe a computational method that estimates the extent of optimization for affinity and specificity of amino acids at a protein–DNA interface based on the crystal structure of the complex, by modeling the changes in binding-free energy associated with all individual amino acid and base substitutions at the interface. The extent to which residues are predicted to be optimal for specificity versus affinity varies within a given protein–DNA interface and between different complexes, and in many cases recapitulates previous experimental observations. The approach provides a complement to traditional methods of mutational analysis, and should be useful for rapidly formulating hypotheses about the roles of amino acid residues in protein–DNA interfaces.     

Role of ATP hydrolysis in the DNA translocase activity of the bovine papillomavirus (BPV-1) E1 helicase

The E1 protein of bovine papillomavirus type-1 is the viral replication initiator protein and replicative helicase. Here we show that the C-terminal ~300 amino acids of E1, that share homology with members of helicase superfamily 3 (SF3), can act as an autonomous helicase. E1 is monomeric in the absence of ATP but assembles into hexamers in the presence of ATP, single-stranded DNA (ssDNA) or both. A 16 base sequence is the minimum for efficient hexamerization, although the complex protects ~30 bases from nuclease digestion, supporting the notion that the DNA is bound within the protein complex. In the absence of ATP, or in the presence of ADP or the non–hydrolysable ATP analogue AMP–PNP, the interaction with short ssDNA oligonucleotides is exceptionally tight (T_1/2 > 6 h). However, in the presence of ATP, the interaction with DNA is destabilized (T_1/2 ~60 s). These results suggest that during the ATP hydrolysis cycle an internal DNA-binding site oscillates from a high to a low-affinity state, while protein–protein interactions switch from low to high affinity. This reciprocal change in protein–protein and protein–DNA affinities could be part of a mechanism for tethering the protein to its substrate while unidirectional movement along DNA proceeds.     

In Vitro Evolution Reveals Noncationic Protein–RNA Interaction Mediated by Metal Ions

RNA–peptide/protein interactions have been of utmost importance to life since its earliest forms, reaching even before the last universal common ancestor (LUCA). However, the ancient molecular mechanisms behind this key biological interaction remain enigmatic because extant RNA–protein interactions rely heavily on positively charged and aromatic amino acids that were absent (or heavily under-represented) in the early pre-LUCA evolutionary period. Here, an RNA-binding variant of the ribosomal uL11 C-terminal domain was selected from an approximately 10¹⁰ library of partially randomized sequences, all composed of ten prebiotically plausible canonical amino acids. The selected variant binds to the cognate RNA with a similar overall affinity although it is less structured in the unbound form than the wild-type protein domain. The variant complex association and dissociation are both slower than for the wild-type, implying different mechanistic processes involved. The profile of the wild-type and mutant complex stabilities along with molecular dynamics simulations uncovers qualitative differences in the interaction modes. In the absence of positively charged and aromatic residues, the mutant uL11 domain uses ion bridging (K⁺/Mg²⁺) interactions between the RNA sugar-phosphate backbone and glutamic acid residues as an alternative source of stabilization. This study presents experimental support to provide a new perspective on how early protein–RNA interactions evolved, where the lack of aromatic/basic residues may have been compensated by acidic residues plus metal ions.     

Amino acid–base interactions: a three-dimensional analysis of protein–DNA interactions at an atomic level

To assess whether there are universal rules that govern amino acid–base recognition, we investigate hydrogen bonds, van der Waals contacts and water-mediated bonds in 129 protein–DNA complex structures. DNA–backbone interactions are the most numerous, providing stability rather than specificity. For base interactions, there are significant base–amino acid type correlations, which can be rationalised by considering the stereochemistry of protein side chains and the base edges exposed in the DNA structure. Nearly two-thirds of the direct read-out of DNA sequences involves complex networks of hydrogen bonds, which enhance specificity. Two-thirds of all protein–DNA interactions comprise van der Waals contacts, compared to about one-sixth each of hydrogen and water-mediated bonds. This highlights the central importance of these contacts for complex formation, which have previously been relegated to a secondary role. Although common, water-mediated bonds are usually non-specific, acting as space-fillers at the protein–DNA interface. In conclusion, the majority of amino acid–base interactions observed follow general principles that apply across all protein–DNA complexes, although there are individual exceptions. Therefore, we distinguish between interactions whose specificities are ‘universal’ and ‘context-dependent’. An interactive Web-based atlas of side chain–base contacts provides access to the collected data, including analyses and visualisation of the three-dimensional geometry of the interactions.     

An ultra‐high affinity protein–protein interface displaying sequence‐robustness

Protein–protein interactions are crucial in biology and play roles in for example, the immune system, signaling pathways, and enzyme regulation. Ultra‐high affinity interactions (K _d <0.1 nM) occur in these systems, however, structures and energetics behind stability of ultra‐high affinity protein–protein complexes are not well understood. Regulation of the starch debranching barley limit dextrinase (LD) and its endogenous cereal type inhibitor (LDI) exemplifies an ultra‐high affinity complex (K _d of 42 pM). In this study the LD–LDI complex is investigated to unveil how robust the ultra‐high affinity is to LDI sequence variation at the protein–protein interface and whether alternative sequences can retain the ultra‐high binding affinity. The interface of LD–LDI was engineered using computational protein redesign aiming at identifying LDI variants predicted to retain ultra‐high binding affinity. These variants present a very diverse set of mutations going beyond conservative and alanine substitutions typically used to probe interfaces. Surface plasmon resonance analysis of the LDI variants revealed that high affinity of LD–LDI requires interactions of several residues at the rim of the protein interface, unlike the classical hotspot arrangement where key residues are found at the center of the interface. Notably, substitution of interface residues in LDI, including amino acids with functional groups different from the wild‐type, could occur without loss of affinity. This demonstrates that ultra‐high binding affinity can be conferred without hotspot residues, thus making complexes more robust to mutational drift in evolution. The present mutational analysis also demonstrates how energetic coupling can emerge between residues at large distances at the interface.     

Validation of a new restraint docking method for solution structure determinations of protein–ligand complexes

A new method is proposed for docking ligands into proteins in cases where an NMR-determined solution structure of a related complex is available. The method uses a set of experimentally determined values for protein–ligand, ligand–ligand, and protein–protein restraints for residues in or near to the binding site, combined with a set of protein–protein restraints involving all the other residues which is taken from the list of restraints previously used to generate the reference structure of a related complex. This approach differs from ordinary docking methods where the calculation uses fixed atomic coordinates from the reference structure rather than the restraints used to determine the reference structure. The binding site residues influenced by replacing the reference ligand by the new ligand were determined by monitoring differences in ¹H chemical shifts. The method has been validated by showing the excellent agreement between structures of L. casei dihydrofolate reductase.trimetrexate calculated by conventional methods using a full experimentally determined set of restraints and those using this new restraint docking method based on an L. casei dihydrofolate reductase.methotrexate reference structure.     

Localizing protein-protein interactions by bimolecular fluorescence complementation in planta

The application of novel assays for basic cell research is tightly linked to the development of easy-to-use and versatile tools and protocols for implementing such technologies for a wide range of applications and model species. The bimolecular fluorescence complementation (BiFC) assay is one such novel method for which tools and protocols for its application in plant cell research are still being developed. BiFC is a powerful tool which enables not only detection, but also visualization and subcellular localization of protein–protein interactions in living cells. Here we describe the application of BiFC in plant cells while focusing on the use of our versatile set of vectors which were specifically designed to facilitate the transformation, expression and imaging of protein–protein interactions in various plant species. We discuss the considerations of using our system in various plant model systems, the use of single versus multiple expression cassettes, the application of our vectors using various transformation methods and the use of internal fluorescent markers which can assist in signal localization and easy data acquisition in living cells.     

A rapid and sensitive high-throughput screening method to identify compounds targeting protein–nucleic acids interactions

DNA-binding and RNA-binding proteins are usually considered ‘undruggable’ partly due to the lack of an efficient method to identify inhibitors from existing small molecule repositories. Here we report a rapid and sensitive high-throughput screening approach to identify compounds targeting protein–nucleic acids interactions based on protein–DNA or protein–RNA interaction enzyme-linked immunosorbent assays (PDI-ELISA or PRI-ELISA). We validated the PDI-ELISA method using the mammalian high-mobility-group protein AT-hook 2 (HMGA2) as the protein of interest and netropsin as the inhibitor of HMGA2–DNA interactions. With this method we successfully identified several inhibitors and an activator for HMGA2–DNA interactions from a collection of 29 DNA-binding compounds. Guided by this screening excise, we showed that netropsin, the specific inhibitor of HMGA2–DNA interactions, strongly inhibited the differentiation of the mouse pre-adipocyte 3T3-L1 cells into adipocytes, most likely through a mechanism by which the inhibition is through preventing the binding of HMGA2 to the target DNA sequences. This method should be broadly applicable to identify compounds or proteins modulating many DNA-binding or RNA-binding proteins.     

A new hydrogen-bonding potential for the design of protein-RNA interactions predicts specific contacts and discriminates decoys

RNA-binding proteins play many essential roles in the regulation of gene expression in the cell. Despite the significant increase in the number of structures for RNA–protein complexes in the last few years, the molecular basis of specificity remains unclear even for the best-studied protein families. We have developed a distance and orientation-dependent hydrogen-bonding potential based on the statistical analysis of hydrogen-bonding geometries that are observed in high-resolution crystal structures of protein–DNA and protein–RNA complexes. We observe very strong geometrical preferences that reflect significant energetic constraints on the relative placement of hydrogen-bonding atom pairs at protein–nucleic acid interfaces. A scoring function based on the hydrogen-bonding potential discriminates native protein–RNA structures from incorrectly docked decoys with remarkable predictive power. By incorporating the new hydrogen-bonding potential into a physical model of protein–RNA interfaces with full atom representation, we were able to recover native amino acids at protein–RNA interfaces.     

A study of collective atomic fluctuations and cooperativity in the U1A-RNA complex based on molecular dynamics simulations

Cooperative interactions play an important role in recognition and binding in macromolecular systems. In this study, we find that cross-correlated atomic fluctuations can be used to identify cooperative networks in a protein–RNA system. The dynamics of the RRM-containing protein U1A–stem loop 2 RNA complex have been calculated theoretically from a 10 ns molecular dynamics (MD) simulation. The simulation was analyzed by calculating the covariance matrix of all atomic fluctuations. These matrix elements are then presented in the form of a two-dimensional grid, which displays fluctuations on a per residue basis. The results indicate the presence of strong, selective cross-correlated fluctuations throughout the RRM in U1A–RNA. The atomic fluctuations correspond well with previous biophysical studies in which a multiplicity of cooperative networks have been reported and indicate that the various networks identified in separate individual experiments are fluctuationally correlated into a hyper-network encompassing most of the RRM. The calculated results also correspond well with independent results from a statistical covariance analysis of 330 aligned RRM sequences. This method has significant implications as a predictive tool regarding cooperativity in the protein–nucleic acid recognition process.     

The role of positively charged amino acids and electrostatic interactions in the complex of U1A protein and U1 hairpin II RNA

Previous kinetic investigations of the N-terminal RNA recognition motif (RRM) domain of spliceosomal protein U1A, interacting with its RNA target U1 hairpin II, provided experimental evidence for a ‘lure and lock’ model of binding in which electrostatic interactions first guide the RNA to the protein, and close range interactions then lock the two molecules together. To further investigate the ‘lure’ step, here we examined the electrostatic roles of two sets of positively charged amino acids in U1A that do not make hydrogen bonds to the RNA: Lys20, Lys22 and Lys23 close to the RNA-binding site, and Arg7, Lys60 and Arg70, located on ‘top’ of the RRM domain, away from the RNA. Surface plasmon resonance-based kinetic studies, supplemented with salt dependence experiments and molecular dynamics simulation, indicate that Lys20 predominantly plays a role in association, while nearby residues Lys22 and Lys23 appear to be at least as important for complex stability. In contrast, kinetic analyses of residues away from the RNA indicate that they have a minimal effect on association and stability. Thus, well-positioned positively charged residues can be important for both initial complex formation and complex maintenance, illustrating the multiple roles of electrostatic interactions in protein–RNA complexes.