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.     

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.     

Ligands act as pharmacological chaperones and increase the efficiency of delta opioid receptor maturation

The endoplasmic reticulum (ER) is recognized as an important site for regulating cell surface expression of membrane proteins. We recently reported that only a fraction of newly synthesized delta opioid receptors could leave the ER and reach the cell surface, the rest being degraded by proteasomes. Here, we demonstrate that membrane-permeable opioid ligands facilitate maturation and ER export of the receptor, thus acting as pharmacological chaperones. We propose that these ligands stabilize the newly synthesized receptor in the native or intermediate state of its folding pathway, possibly by inducing stabilizing conformational constrains within the hydrophobic core of the protein. The receptor precursors that are retained in the ER thus represent fully competent folding intermediates that can be targets for pharmacological intervention aimed at regulating receptor expression and cellular responsiveness. The pharmacological chaperone action is independent of the intrinsic signaling efficacy of the ligand, since both agonists and antagonists were found to promote receptor maturation. This novel property of G protein-coupled receptor ligands may have important implications when considering their effects on cellular responsiveness during therapeutic treatments.     

Export from the endoplasmic reticulum represents the limiting step in the maturation and cell surface expression of the human delta opioid receptor

Synthesis and maturation of G protein-coupled receptors are complex events that require an intricate combination of processes that include protein folding, post-translational modifications, and transport through distinct cellular compartments. Relatively little is known about the nature and kinetics of specific steps involved in these processes. Here, the human delta opioid receptor expressed in human embryonic kidney 293S cells is used as a model to delineate these steps and to establish the kinetics of receptor synthesis, glycosylation, and transport. We found that the receptor is synthesized as a core-glycosylated M(r) 45,000 precursor that is converted to the fully mature M(r) 55,000 receptor with a half-time of about 120 min. In addition to trimming and processing of two N-linked oligosaccharides, maturation involves addition of O-glycans containing N-acetylgalactosamine, galactose, and sialic acid. In contrast to N-glycosylation, which is initiated co-translationally and is completed when the protein reaches the trans-Golgi network, O-glycosylation was found to occur only after the receptor exits from the endoplasmic reticulum (ER) and was terminated as early as the trans-Golgi cisternae. Once the carbohydrates are fully processed and the receptor reaches the trans-Golgi network, it is transported to the cell surface in about 10 min. The exit from the ER was found to be the limiting step in overall processing of the receptor. This indicates that early events in the folding of the receptor are probably rate-limiting and that receptor folding intermediates are retained in the ER until they can adopt the correct conformation. The overall low efficiency of receptor maturation, less than 50% of the precursor being processed to the fully glycosylated protein, further suggests that only a fraction of the synthesized receptors attain properly folded conformation that allows exit from the ER. This indicates that folding and ER export are key events in control of receptor cell surface expression. Whether or not the low efficiency of the ER export is a general feature among G protein-coupled receptors remains to be investigated.     

A fast method to sample real protein conformational space

A fast computer program, FOLDTRAJ, to generate plausible random protein structures is reported. All-atom proteins are made directly in continuous three-dimensional space starting from primary sequence with an N to C directed build-up method. The method uses a novel pipelined residue addition approach in which the leading edge of the protein is constructed three residues at a time for optimal protein geometry, including the placement of cis proline. Build-up methods represent a classic N-body problem, expected to scale as N(2). When proteins become more collapsed, build-up methods are susceptible to backtracking problems which can scale exponentially with the number of residues required to back out of a trapped walk. We have provided solutions to both these problems, using a multiway binary tree that makes the N-body problem of bump-checking scale as NlogN, and speeding up backtracking by varying the number of tries before backtracking based on available conformational space. FOLDTRAJ is independent of energy potentials, other than that implicit in the geometrical properties derived by statistical studies of known structures, and in atomic Van der Waals radii. WHAT-CHECK shows that the program generates chirally and physically valid proteins with all bond lengths, angles and dihedrals within allowable tolerances. Random structures built using sequences from PDB files 1SEM, 2HPR, and 1RTP typically have 5-15% alpha-helical content (according to DSSP) and on the order of 20% beta-strand/extended content. Ensembles of random structures are compared with polymer theory and with experimentally determined fluorescence resonance energy transfer distances. Reasonably sized structure ensembles do sample most of the conformational space available to proteins. The method is also capable of protein reconstruction using Calpha--Calpha direction vectors, and it compares favorably with methods that reconstruct protein backbones based on alpha-carbon coordinates, having an average backbone and Cbeta root mean square deviation of 0.63 A for nine different protein folds. Proteins 2000;39:112-131.     

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.     

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.     

Newly synthesized human delta opioid receptors retained in the endoplasmic reticulum are retrotranslocated to the cytosol, deglycosylated, ubiquitinated, and degraded by the proteasome

We have previously shown that only a fraction of the newly synthesized human delta opioid receptors is able to leave the endoplasmic reticulum (ER) and reach the cell surface (Pet?j?-Repo, U. E, Hogue, M., Laperrière, A., Walker, P., and Bouvier, M. (2000) J. Biol. Chem. 275, 13727-13736). In the present study, we investigated the fate of those receptors that are retained intracellularly. Pulse-chase experiments revealed that the disappearance of the receptor precursor form (M(r) 45,000) and of two smaller species (M(r) 42,000 and 39,000) is inhibited by the proteasome blocker, lactacystin. The treatment also promoted accumulation of the mature receptor form (M(r) 55,000), indicating that the ER quality control actively routes a significant proportion of rescuable receptors for proteasome degradation. In addition, degradation intermediates that included full-length deglycosylated (M(r) 39,000) and ubiquitinated forms of the receptor were found to accumulate in the cytosol upon inhibition of proteasome function. Finally, coimmunoprecipitation experiments with the beta-subunit of the Sec61 translocon complex revealed that the receptor precursor and its deglycosylated degradation intermediates interact with the translocon. Taken together, these results support a model in which misfolded or incompletely folded receptors are transported to the cytoplasmic side of the ER membrane via the Sec61 translocon, deglycosylated and conjugated with ubiquitin prior to degradation by the cytoplasmic 26 S proteasomes.     

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.