Computational modeling suggests binding-induced expansion of Epsin disordered regions upon association with AP2.

Intrinsically disordered regions (IDRs) are prevalent in the eukaryotic proteome. Common functional roles of IDRs include forming flexible linkers or undergoing allosteric folding-upon-binding. Recent studies have suggested an additional functional role for IDRs: generating steric pressure on the plasma membrane during endocytosis, via molecular crowding. However, in order to accomplish useful functions, such crowding needs to be regulated in space (e.g., endocytic hotspots) and time (e.g., during vesicle formation). In this work, we explore binding-induced regulation of IDR steric volume. We simulate the IDRs of two proteins from Clathrin-mediated endocytosis (CME) to see if their conformational spaces are regulated via binding-induced expansion. Using Monte-Carlo computational modeling of excluded volumes, we generate large conformational ensembles (3 million) for the IDRs of Epsin and Eps15 and dock the conformers to the alpha subunit of Adaptor Protein 2 (AP2α), their CME binding partner. Our results show that as more molecules of AP2α are bound, the Epsin-derived ensemble shows a significant increase in global dimensions, measured as the radius of Gyration (RG) and the end-to-end distance (EED). Unlike Epsin, Eps15-derived conformers that permit AP2α binding at one motif were found to be more likely to accommodate binding of AP2α at other motifs, suggesting a tendency toward co-accessibility of binding motifs. Co-accessibility was not observed for any pair of binding motifs in Epsin. Thus, we speculate that the disordered regions of Epsin and Eps15 perform different roles during CME, with accessibility in Eps15 allowing it to act as a recruiter of AP2α molecules, while binding-induced expansion of the Epsin disordered region could impose steric pressure and remodel the plasma membrane during vesicle formation.

De novo ensemble modeling suggests that AP2-binding to disordered regions can increase steric volume of Epsin but not Eps15.

Proteins with intrinsically disordered regions (IDRs) have large hydrodynamic radii, compared with globular proteins of equivalent weight. Recent experiments showed that IDRs with large radii can create steric pressure to drive membrane curvature during Clathrin-mediated endocytosis (CME). Epsin and Eps15 are two CME proteins with IDRs that contain multiple motifs for binding the adaptor protein AP2, but the impact of AP2-binding on these IDRs is unknown. Some IDRs acquire binding-induced function by forming a folded quaternary structure, but we hypothesize that the IDRs of Epsin and/or Eps15 acquire binding-induced function by increasing their steric volume. We explore this hypothesis in silico by generating conformational ensembles of the IDRs of Epsin (4 million structures) or Eps15 (3 million structures), then estimating the impact of AP2-binding on Radius of Gyration (RG). Results show that the ensemble of Epsin IDR conformations that accommodate AP2 binding has a right-shifted distribution of RG (larger radii) than the unbound Epsin ensemble. In contrast, the ensemble of Eps15 IDR conformations has comparable RG distribution between AP2-bound and unbound. We speculate that AP2 triggers the Epsin IDR to function through binding-induced-expansion, which could increase steric pressure and membrane bending during CME.

Structural Basis for a Unique ATP Synthase Core Complex from Nanoarcheaum equitans.

ATP synthesis is a critical and universal life process carried out by ATP synthases. Whereas eukaryotic and prokaryotic ATP synthases are well characterized, archaeal ATP synthases are relatively poorly understood. The hyperthermophilic archaeal parasite, Nanoarcheaum equitans, lacks several subunits of the ATP synthase and is suspected to be energetically dependent on its host, Ignicoccus hospitalis. This suggests that this ATP synthase might be a rudimentary machine. Here, we report the crystal structures and biophysical studies of the regulatory subunit, NeqB, the apo-NeqAB, and NeqAB in complex with nucleotides, ADP, and adenylyl-imidodiphosphate (non-hydrolysable analog of ATP). NeqB is ∼20 amino acids shorter at its C terminus than its homologs, but this does not impede its binding with NeqA to form the complex. The heterodimeric NeqAB complex assumes a closed, rigid conformation irrespective of nucleotide binding; this differs from its homologs, which require conformational changes for catalytic activity. Thus, although N. equitans possesses an ATP synthase core A3B3 hexameric complex, it might not function as a bona fide ATP synthase.

A cooperative jack model of random coil-to-elongation transition of the FH1 domain by profilin binding explains formin motor behavior in actin polymerization.

Filopodia are essential for the development of neuronal growth cones, cell polarity and cell migration. Their protrusions are powered by the polymerization of actin filaments linked to the plasma membrane, catalyzed by formin proteins. The acceleration of polymerization depends on the number of profilin-actins binding with the formin-FH1 domain. Biophysical characterization of the disordered formin-FH1 domain remains a challenge. We analyzed the conformational distribution of the diaphanous-related formin mDia1-FH1 bound with one to six profilins. We found a coil-to-elongation transition in the FH1 domain. We propose a cooperative "jack" model for the Formin-Homology-1 (FH1) domain of formins stacked by profilin-actins.

Biophysical properties of intrinsically disordered p130Cas substrate domain--implication in mechanosensing.

Mechanical stretch-induced tyrosine phosphorylation in the proline-rich 306-residue substrate domain (CasSD) of p130Cas (or BCAR1) has eluded an experimentally validated structural understanding. Cellular p130Cas tyrosine phosphorylation is shown to function in areas without internal actomyosin contractility, sensing force at the leading edge of cell migration. Circular dichroism shows CasSD is intrinsically disordered with dominant polyproline type II conformations. Strongly conserved in placental mammals, the proline-rich sequence exhibits a pseudo-repeat unit with variation hotspots 2-9 residues before substrate tyrosine residues. Atomic-force microscopy pulling experiments show CasSD requires minimal extension force and exhibits infrequent, random regions of weak stability. Proteolysis, light scattering and ultracentrifugation results show that a monomeric intrinsically disordered form persists for CasSD in solution with an expanded hydrodynamic radius. All-atom 3D conformer sampling with the TraDES package yields ensembles in agreement with experiment when coil-biased sampling is used, matching the experimental radius of gyration. Increasing ß-sampling propensities increases the number of prolate conformers. Combining the results, we conclude that CasSD has no stable compact structure and is unlikely to efficiently autoinhibit phosphorylation. Taking into consideration the structural propensity of CasSD and the fact that it is known to bind to LIM domains, we propose a model of how CasSD and LIM domain family of transcription factor proteins may function together to regulate phosphorylation of CasSD and effect machanosensing.

Protein kinases display minimal interpositional dependence on substrate sequence: potential implications for the evolution of signalling networks.

Characterization of in vitro substrates of protein kinases by peptide library screening provides a wealth of information on the substrate specificity of kinases for amino acids at particular positions relative to the site of phosphorylation, but provides no information concerning interdependence among positions. High-throughput techniques have recently made it feasible to identify large numbers of in vivo kinase substrates. We used data from experiments on the kinases ATM/ATR and CDK1, and curated CK2 substrates to evaluate the prevalence of interactions between substrate positions within a motif and the utility of these interactions in predicting kinase substrates. Among these data, evidence of interpositional sequence dependencies is strikingly rare, and what dependency exists does little to aid in the prediction of novel kinase substrates. Significant increases in the ability of models to predict kinase-substrate specificity beyond position-independent models must come largely from inclusion of elements of biological and cellular context, rather than further analysis of substrate sequences alone. Our results suggest that, evolutionarily, kinase substrate fitness exists in a smooth energetic landscape. Taken with results from others indicating that phosphopeptide-binding domains do exhibit interpositional dependence, our data suggest that incorporation of new substrate molecules into phospho-signalling networks may be rate-limited by the evolution of suitability for binding by phosphopeptide-binding domains.

Near-membrane ensemble elongation in the proline-rich LRP6 intracellular domain may explain the mysterious initiation of the Wnt signaling pathway.

BACKGROUND: LRP6 is a membrane protein crucial in the initiation of canonical Wnt/ß-catenin signalling. Its function is dependent on its proline-serine rich intracellular domain. LRP6 has five PPP(S/T)P motifs that are phosphorylated during activation, starting with the site closest to the membrane. Like all long proline rich regions, there is no stable 3D structure for this isolated, contiguous region. RESULTS: In our study, we use a computational simulation tool to sample the conformational space of the LRP6 intracellular domain, under the spatial constraints imposed by (a) the membrane and (b) the close approach of the neighboring intracellular molecular complex, which is assembled on Frizzled when Wnt binds to both LRP6 and Frizzled on the opposite side of the membrane. We observe that an elongated form dominates in the LRP6 intracellular domain structure ensemble. This elongation could relieve conformational auto-inhibition of the PPP(S/T)PX(S/T) motif binding sites and allow GSK3 and CK1 to approach their phosphorylation sites, thereby activating LRP6 and the downstream pathway. CONCLUSIONS: We propose a model in which the conformation of the LRP6 intracellular domain is elongated before activation. This is based on the intrusion of the Frizzled complex into the ensemble space of the proline rich region of LRP6, which alters the shape of its available ensemble space. To test whether this observed ensemble conformational change is sequence dependent, we did a control simulation with a hypothetical sequence with 50% proline and 50% serine in alternating residues. We confirm that this ensemble neighbourhood-based conformational change is independent of sequence and conclude that it is likely found in all proline rich sequences. These observations help us understand the nature of proline rich regions which are both unstructured and which seem to evolve at a higher rate of mutation, while maintaining sequence composition.

Structure-templated predictions of novel protein interactions from sequence information.

The multitude of functions performed in the cell are largely controlled by a set of carefully orchestrated protein interactions often facilitated by specific binding of conserved domains in the interacting proteins. Interacting domains commonly exhibit distinct binding specificity to short and conserved recognition peptides called binding profiles. Although many conserved domains are known in nature, only a few have well-characterized binding profiles. Here, we describe a novel predictive method known as domain-motif interactions from structural topology (D-MIST) for elucidating the binding profiles of interacting domains. A set of domains and their corresponding binding profiles were derived from extant protein structures and protein interaction data and then used to predict novel protein interactions in yeast. A number of the predicted interactions were verified experimentally, including new interactions of the mitotic exit network, RNA polymerases, nucleotide metabolism enzymes, and the chaperone complex. These results demonstrate that new protein interactions can be predicted exclusively from sequence information.

Domain-based small molecule binding site annotation.

BACKGROUND: Accurate small molecule binding site information for a protein can facilitate studies in drug docking, drug discovery and function prediction, but small molecule binding site protein sequence annotation is sparse. The Small Molecule Interaction Database (SMID), a database of protein domain-small molecule interactions, was created using structural data from the Protein Data Bank (PDB). More importantly it provides a means to predict small molecule binding sites on proteins with a known or unknown structure and unlike prior approaches, removes large numbers of false positive hits arising from transitive alignment errors, non-biologically significant small molecules and crystallographic conditions that overpredict ion binding sites. DESCRIPTION: Using a set of co-crystallized protein-small molecule structures as a starting point, SMID interactions were generated by identifying protein domains that bind to small molecules, using NCBI's Reverse Position Specific BLAST (RPS-BLAST) algorithm. SMID records are available for viewing at http://smid.blueprint.org. The SMID-BLAST tool provides accurate transitive annotation of small-molecule binding sites for proteins not found in the PDB. Given a protein sequence, SMID-BLAST identifies domains using RPS-BLAST and then lists potential small molecule ligands based on SMID records, as well as their aligned binding sites. A heuristic ligand score is calculated based on E-value, ligand residue identity and domain entropy to assign a level of confidence to hits found. SMID-BLAST predictions were validated against a set of 793 experimental small molecule interactions from the PDB, of which 472 (60%) of predicted interactions identically matched the experimental small molecule and of these, 344 had greater than 80% of the binding site residues correctly identified. Further, we estimate that 45% of predictions which were not observed in the PDB validation set may be true positives. CONCLUSION: By focusing on protein domain-small molecule interactions, SMID is able to cluster similar interactions and detect subtle binding patterns that would not otherwise be obvious. Using SMID-BLAST, small molecule targets can be predicted for any protein sequence, with the only limitation being that the small molecule must exist in the PDB. Validation results and specific examples within illustrate that SMID-BLAST has a high degree of accuracy in terms of predicting both the small molecule ligand and binding site residue positions for a query protein.

A complete small molecule dataset from the protein data bank.

A complete set of 6300 small molecule ligands was extracted from the protein data bank, and deposited online in PubChem as data source 'SMID'. This set's major improvement over prior methods is the inclusion of cyclic polypeptides and branched polysaccharides, including an unambiguous nomenclature, in addition to normal monomeric ligands. Only the best available example of each ligand structure is retained, and an additional dataset is maintained containing co-ordinates for all examples of each structure. Attempts are made to correct ambiguous atomic elements and other common errors, and a perception algorithm was used to determine bond order and aromaticity when no other information was available.

Searching, viewing, and visualizing data in the Biomolecular Interaction Network Database (BIND).

The Biomolecular Interaction Network Database (BIND) comprises data from peer-reviewed literature and direct submissions. BIND's data model was the first of its kind to be peer-reviewed prior to database development, and is now a mature standard data format spanning molecular interactions, small molecule chemical reactions, and interfaces from three-dimensional structures, pathways, and genetic interaction networks. BIND supports additional file formats to achieve compatibility with other database efforts, including the HUPO PSI Level 2. BIND's latest software spans over 2000 metadata fields and is constructed using the Java Enterprise Systems software platform. Protocols are provided for searching BIND via the Internet, as well as for viewing and exporting search results or individual records. Furthermore, a protocol is provided for visualizing biomolecular interactions within BIND or for transferring this information to the visualization tools Cytoscape and Cn3D.

CO: A chemical ontology for identification of functional groups and semantic comparison of small molecules.

A novel chemical ontology based on chemical functional groups automatically, objectively assigned by a computer program, was developed to categorize small molecules. It has been applied to PubChem and the small molecule interaction database to demonstrate its utility as a basic pharmacophore search system. Molecules can be compared using a semantic similarity score based on functional group assignments rather than 3D shape, which succeeds in identifying small molecules known to bind a common binding site. This ontology will serve as a powerful tool for searching chemical databases and identifying key functional groups responsible for biological activities.

Armadillo: domain boundary prediction by amino acid composition.

The identification and annotation of protein domains provides a critical step in the accurate determination of molecular function. Both computational and experimental methods of protein structure determination may be deterred by large multi-domain proteins or flexible linker regions. Knowledge of domains and their boundaries may reduce the experimental cost of protein structure determination by allowing researchers to work on a set of smaller and possibly more successful alternatives. Current domain prediction methods often rely on sequence similarity to conserved domains and as such are poorly suited to detect domain structure in poorly conserved or orphan proteins. We present here a simple computational method to identify protein domain linkers and their boundaries from sequence information alone. Our domain predictor, Armadillo (http://armadillo.blueprint.org), uses any amino acid index to convert a protein sequence to a smoothed numeric profile from which domains and domain boundaries may be predicted. We derived an amino acid index called the domain linker propensity index (DLI) from the amino acid composition of domain linkers using a non-redundant structure dataset. The index indicates that Pro and Gly show a propensity for linker residues while small hydrophobic residues do not. Armadillo predicts domain linker boundaries from Z-score distributions and obtains 35% sensitivity with DLI in a two-domain, single-linker dataset (within +/-20 residues from linker). The combination of DLI and an entropy-based amino acid index increases the overall Armadillo sensitivity to 56% for two domain proteins. Moreover, Armadillo achieves 37% sensitivity for multi-domain proteins, surpassing most other prediction methods. Armadillo provides a simple, but effective method by which prediction of domain boundaries can be obtained with reasonable sensitivity. Armadillo should prove to be a valuable tool for rapidly delineating protein domains in poorly conserved proteins or those with no sequence neighbors. As a first-line predictor, domain meta-predictors could yield improved results with Armadillo predictions.

Hardware-accelerated protein identification for mass spectrometry.

An ongoing issue in mass spectrometry is the time it takes to search DNA sequences with MS/MS peptide fragments (see, e.g., Choudary et al., Proteomics 2001; 1: 651-667.) Search times are far longer than spectra acquisition time, and parallelization of search software on clusters requires doubling the size of a conventional computing cluster to cut the search time in half. Field programmable gate arrays (FPGAs) are used to create hardware-accelerated algorithms that reduce operating costs and improve search speed compared to large clusters. We present a novel hardware design that takes full spectra and computes 6-frame translation word searches on DNA databases at a rate of approximately 3 billion base pairs per second, with queries of up to 10 amino acids in length and arbitrary wildcard positions. Hardware post-processing identifies in silico tryptic peptides and scores them using a variety of techniques including mass frequency expected values. With faster FPGAs protein identifications from the human genome can be achieved in less than a second, and this makes it an ideal solution for a number of proteome-scale applications.

Analysis of domain correlations in yeast protein complexes.

MOTIVATION: A growing body of research has concentrated on the identification and definition of conserved sequence motifs. It is widely recognized that these conserved sequence and structural units often mediate protein functions and interactions. The continuing advancements in high-throughput experiments necessitate the development of computational methods to critically assess the results. In this work, we analyzed high-throughput protein complexes using the domain composition of their protein constituents. Domains that mediate similar or related functions may consistently co-occur in protein complexes. RESULTS: We analyzed Saccharomyces cerevisiae protein complexes from curated and high-throughput experimental datasets to identify statistically significant functional associations between domains. The resulting correlations are represented as domain networks that form the basis of comparison between the datasets, as well as to binary protein interactions. The results show that the curated datasets produce domain networks that map to known biological assemblies, such as ribosome, RNA polymerase, proteasome regulators, transcription initiation and histones. Furthermore, many of these domain correlations were also found in binary protein interactions. In contrast, the high-throughput datasets contain one large network of domain associations. High connectivity of RNA processing and binding domains in the high-throughput datasets reflects the abundance of RNA binding proteins in yeast, in agreement with a previous report that identified a nucleolar protein cluster, possibly mediated by rRNA, from these complexes. AVAILABILITY: The software is available upon request from the authors and is dependent on the NCBI C++ toolkit.

Intermediate filament networks: in vitro and in vivo assembly models.

We propose two systems of ordinary differential equations modeling the assembly of intermediate filament networks. The first one describes the in vitro intermediate filament assembly dynamics. The second one deals with the in vivo evolution of cytokeratin, which is the intermediate filament protein expressed by epithelial cells. The in vitro model is then briefly analyzed in a simplified case.

Fluorescence based structural analysis of tryptophan analogue-AMP formation in single tryptophan mutants of Bacillus stearothermophilus tryptophanyl-tRNA synthetase.

The symmetrical dimer structure of tryptophanyl-tRNA synthetase is similar to that of tyrosyl-tRNA synthetase whose binding behavior and structural details have been elucidated in detail. The structure of both subunits after forming the intermediate tryptophanyl-AMP has important implications for the binding of the cognate tRNA(Trp). Single tryptophan mutants of Bacillus stearothermophilus tryptophanyl-tRNA synthetase have been constructed and expressed and used to probe structural changes in different domains of the enzyme in both subunits. Substrate titrations using the Trp analogues 4-fluorotryptophan and 7-azatryptophan in the presence of ATP to form the corresponding aminoacyl-adenylate reveal significant structural changes occurring throughout the active subunit in regions not confined to the active site. Changes in environment around the specific Trp residues were monitored using UV absorbance and steady-state fluorescence measurements. When titrated with 4-fluorotryptophan, both Trp 91 and Trp 290 fluorescence is quenched (49 and 22%, respectively) when one subunit has formed Trp-AMP. The fluorescence of Trp 48 is enhanced 19%. No further change in signal was observed after a 1:1 dimer/L-4FW-AMP complex ratio had been established. Using an anion-exchange filter binding assay with radiolabeled l-Trp as a substrate, binding to only one subunit was observed under nonsaturating conditions. This agrees with the results of the assay using 7-azatryptophan as a substrate. The observed changes extend to the unfilled subunit where a similar structure is believed to form after one subunit has formed tryptophan-AMP. Movement in the regions of the enzyme containing Trp 290 and Trp 91 suggests a mechanism for cross-subunit communication involving the helical backbone and dimer interface containing these two residues.

PreBIND and Textomy--mining the biomedical literature for protein-protein interactions using a support vector machine.

BACKGROUND: The majority of experimentally verified molecular interaction and biological pathway data are present in the unstructured text of biomedical journal articles where they are inaccessible to computational methods. The Biomolecular interaction network database (BIND) seeks to capture these data in a machine-readable format. We hypothesized that the formidable task-size of backfilling the database could be reduced by using Support Vector Machine technology to first locate interaction information in the literature. We present an information extraction system that was designed to locate protein-protein interaction data in the literature and present these data to curators and the public for review and entry into BIND. RESULTS: Cross-validation estimated the support vector machine's test-set precision, accuracy and recall for classifying abstracts describing interaction information was 92%, 90% and 92% respectively. We estimated that the system would be able to recall up to 60% of all non-high throughput interactions present in another yeast-protein interaction database. Finally, this system was applied to a real-world curation problem and its use was found to reduce the task duration by 70% thus saving 176 days. CONCLUSIONS: Machine learning methods are useful as tools to direct interaction and pathway database back-filling; however, this potential can only be realized if these techniques are coupled with human review and entry into a factual database such as BIND. The PreBIND system described here is available to the public at http://bind.ca. Current capabilities allow searching for human, mouse and yeast protein-interaction information.

BIND: the Biomolecular Interaction Network Database.

The Biomolecular Interaction Network Database (BIND: http://bind.ca) archives biomolecular interaction, complex and pathway information. A web-based system is available to query, view and submit records. BIND continues to grow with the addition of individual submissions as well as interaction data from the PDB and a number of large-scale interaction and complex mapping experiments using yeast two hybrid, mass spectrometry, genetic interactions and phage display. We have developed a new graphical analysis tool that provides users with a view of the domain composition of proteins in interaction and complex records to help relate functional domains to protein interactions. An interaction network clustering tool has also been developed to help focus on regions of interest. Continued input from users has helped further mature the BIND data specification, which now includes the ability to store detailed information about genetic interactions. The BIND data specification is available as ASN.1 and XML DTD.