Exploring the structure of opioid receptors with homology modeling based on single and multiple templates and subsequent docking: A comparative study

Opioid receptors are the principal targets for opioids, which have been used as analgesics for centuries. Opioid receptors belong to the rhodopsin family of G-protein coupled receptors (GPCRs). In the absence of crystal structures of opioid receptors, 3D homology models have been reported with bovine rhodopsin as a template, though the sequence homology is low. Recently, it has been reported that use of multiple templates results in a better model for a target having low sequence identity with a single template. With the objective of carrying out a comparative study on the structural quality of the 3D models based on single and multiple templates, the homology models for opioid receptors (mu, delta and kappa) were generated using bovine rhodopsin as single template and the recently deposited crystal structures of squid rhodopsin, turkey β-1 and human β-2 adrenoreceptors along with bovine rhodopsin as multiple templates. In this paper we report the results of comparison between the refined 3D models based on multiple sequence alignment (MSA) and models built with bovine rhodopsin as template, using validation programs PROCHECK, PROSA, Verify 3D, Molprobity and docking studies. The results indicate that homology models of mu and kappa with multiple templates are better than those built with only bovine rhodopsin as template, whereas, in many aspects, the homology model of delta opioid receptor with single template is better with respect to the model based on multiple templates. Three nonselective ligands were docked to both the models of mu, delta and kappa opioid receptors using GOLD 3.1. The results of docking complied well with the pharamacophore, reported for nonspecific opioid ligands. The comparison of docking results for models with multiple templates and those with single template have been discussed in detail. Three selective ligands for each receptor were also docked. As the crystallographic structures are not yet known, this comparison will help in choosing better homology models of opioid receptors for studying ligand receptor interactions to design new potent opioid antagonists.     

Towards Improved Quality of GPCR Models by Usage of Multiple Templates and Profile-Profile Comparison

G-protein coupled receptors (GPCRs) are targets of nearly one third of the drugs at the current pharmaceutical market. Despite their importance in many cellular processes the crystal structures are available for less than 20 unique GPCRs of the Rhodopsin-like class. Fortunately, even though involved in different signaling cascades, this large group of membrane proteins has preserved a uniform structure comprising seven transmembrane helices that allows quite reliable comparative modeling. Nevertheless, low sequence similarity between the GPCR family members is still a serious obstacle not only in template selection but also in providing theoretical models of acceptable quality. An additional level of difficulty is the prediction of kinks and bulges in transmembrane helices. Usage of multiple templates and generation of alignments based on sequence profiles may increase the rate of success in difficult cases of comparative modeling in which the sequence similarity between GPCRs is exceptionally low. Here, we present GPCRM, a novel method for fast and accurate generation of GPCR models using averaging of multiple template structures and profile-profile comparison. In particular, GPCRM is the first GPCR structure predictor incorporating two distinct loop modeling techniques: Modeller and Rosetta together with the filtering of models based on the Z-coordinate. We tested our approach on all unique GPCR structures determined to date and report its performance in comparison with other computational methods targeting the Rhodopsin-like class. We also provide a database of precomputed GPCR models of the human receptors from that class.

Availability

GPCRM server and database: http://gpcrm.biomodellab.eu     

Structure modeling of all identified G protein-coupled receptors in the human genome

G protein-coupled receptors (GPCRs), encoded by about 5% of human genes, comprise the largest family of integral membrane proteins and act as cell surface receptors responsible for the transduction of endogenous signal into a cellular response. Although tertiary structural information is crucial for function annotation and drug design, there are few experimentally determined GPCR structures. To address this issue, we employ the recently developed threading assembly refinement (TASSER) method to generate structure predictions for all 907 putative GPCRs in the human genome. Unlike traditional homology modeling approaches, TASSER modeling does not require solved homologous template structures; moreover, it often refines the structures closer to native. These features are essential for the comprehensive modeling of all human GPCRs when close homologous templates are absent. Based on a benchmarked confidence score, approximately 820 predicted models should have the correct folds. The majority of GPCR models share the characteristic seven-transmembrane helix topology, but 45 ORFs are predicted to have different structures. This is due to GPCR fragments that are predominantly from extracellular or intracellular domains as well as database annotation errors. Our preliminary validation includes the automated modeling of bovine rhodopsin, the only solved GPCR in the Protein Data Bank. With homologous templates excluded, the final model built by TASSER has a global C(alpha) root-mean-squared deviation from native of 4.6 angstroms, with a root-mean-squared deviation in the transmembrane helix region of 2.1 angstroms. Models of several representative GPCRs are compared with mutagenesis and affinity labeling data, and consistent agreement is demonstrated. Structure clustering of the predicted models shows that GPCRs with similar structures tend to belong to a similar functional class even when their sequences are diverse. These results demonstrate the usefulness and robustness of the in silico models for GPCR functional analysis. All predicted GPCR models are freely available for noncommercial users on our Web site (http://www.bioinformatics.buffalo.edu/GPCR).     

Using molecular dynamics for the refinement of atomistic models of GPCRs by homology modeling

Despite GPCRs sharing a common seven helix bundle, analysis of the diverse crystallographic structures available reveal specific features that might be relevant for ligand design. Despite the number of crystallographic structures of GPCRs steadily increasing, there are still challenges that hamper the availability of new structures. In the absence of a crystallographic structure, homology modeling remains one of the important techniques for constructing 3D models of proteins. In the present study we investigated the use of molecular dynamics simulations for the refinement of GPCRs models constructed by homology modeling. Specifically, we investigated the relevance of template selection, ligand inclusion as well as the length of the simulation on the quality of the GPCRs models constructed. For this purpose we chose the crystallographic structure of the rat muscarinic M3 receptor as reference and constructed diverse atomistic models by homology modeling, using different templates. Specifically, templates used in the present work include the human muscarinic M2; the more distant human histamine H1 and the even more distant bovine rhodopsin as shown in the GPCRs phylogenetic tree. We also investigated the use or not of a ligand in the refinement process. Hence, we conducted the refinement process of the M3 model using the M2 muscarinic as template with tiotropium or NMS docked in the orthosteric site and compared with the results obtained with a model refined without any ligand bound.     

An Evolutionarily Conserved Arginine Is Essential for Tre1 G Protein-Coupled Receptor Function During Germ Cell Migration in Drosophila melanogaster

Background

G protein-coupled receptors (GPCRs) play central roles in mediating cellular responses to environmental signals leading to changes in cell physiology and behaviors, including cell migration. Numerous clinical pathologies including metastasis, an invasive form of cell migration, have been linked to abnormal GPCR signaling. While the structures of some GPCRs have been defined, the in vivo roles of conserved amino acid residues and their relationships to receptor function are not fully understood. Trapped in endoderm 1 (Tre1) is an orphan receptor of the rhodopsin class that is necessary for primordial germ cell migration in Drosophila melanogaster embryos. In this study, we employ molecular genetic approaches to identify residues in Tre1 that are critical to its functions in germ cell migration.

Methodology/Principal Findings

First, we show that the previously reported scattershot mutation is an allele of tre1. The scattershot allele results in an in-frame deletion of 8 amino acids at the junction of the third transmembrane domain and the second intracellular loop of Tre1 that dramatically impairs the function of this GPCR in germ cell migration. To further refine the molecular basis for this phenotype, we assayed the effects of single amino acid substitutions in transgenic animals and determined that the arginine within the evolutionarily conserved E/N/DRY motif is critical for receptor function in mediating germ cell migration within an intact developing embryo.

Conclusions/Significance

These structure-function studies of GPCR signaling in native contexts will inform future studies into the basic biology of this large and clinically important family of receptors.     

Revisiting the homology modeling of G-protein coupled receptors: β1-adrenoceptor as an example

G-protein coupled receptors (GPCRs) are recognized to constitute the largest family of membrane proteins. Due to the disproportion in the quantity of crystal structures and their amino acid sequences, homology modeling contributes a reasonable and feasible approach to GPCR theoretical coordinates. With the brand new crystal structures resolved recently, herein we deliberated how to designate them as templates to carry out homology modeling in four aspects: (1) various sequence alignment methods; (2) protein weight matrix; (3) different sets of multiple templates; (4) active and inactive state of templates. The accuracy of models was evaluated by comparing the similarity of stereo conformation and molecular docking results between models and the experimental structure of Meleagris gallopavo β(1)-adrenergic receptor (Mg_Adrb1) that we desired to develop as an example. Our results proposed that: (1) Cobalt and MAFFT, two algorithms of sequence alignment, were suitable for single- and multiple-template modeling, respectively; (2) Blosum30 is applicable to align sequences in the case of low sequence identity; (3) multiple-template modeling is not always better than single-template one; (4) the state of template is an influential factor in simulating the GPCR structures as well.     

Novel approach to computer modeling of seven-helical transmembrane proteins: current progress in the test case of bacteriorhodopsin.

G-protein coupled receptors (GPCRs) are thought to be proteins with 7-membered transmembrane helical bundles (7TM proteins). Recently, the X-ray structures have been solved for two such proteins, namely for bacteriorhodopsin (BR) and rhodopsin (Rh), the latter being a GPCR. Despite similarities, the structures are different enough to suggest that 3D models for different GPCRs cannot be obtained directly employing 3D structures of BR or Rh as a unique template. The approach to computer modeling of 7TM proteins developed in this work was capable of reproducing the experimental X-ray structure of BR with great accuracy. A combination of helical packing and low-energy conformers for loops most close to the X-ray structure possesses the r.m.s.d. value of 3.13 A. Such a level of accuracy for the 3D-structure prediction for a 216-residue protein has not been achieved, so far, by any available ab initio procedure of protein folding. The approach may produce also other energetically consistent combinations of helical bundles and loop conformers, creating a variety of possible templates for 3D structures of 7TM proteins, including GPCRs. These templates may provide experimentalists with various plausible options for 3D structure of a given GPCR; in our view, only experiments will determine the final choice of the most reasonable 3D template.     

Relevance of rhodopsin studies for GPCR activation

Rhodopsin, the dim-light photoreceptor present in the rod cells of the retina, is both a retinal-binding protein and a G protein-coupled receptor (GPCR). Due to this conjunction, it benefits from an arsenal of spectroscopy techniques that can be used for its characterization, while being a model system for the important family of Class A (also referred to as “rhodopsin-like”) GPCRs. For instance, rhodopsin has been a crucial player in the field of GPCR structural biology. Until 2007, it was the only GPCR for which a high-resolution crystal structure was available, so all structure–activity analyses on GPCRs, from structure-based drug discovery to studies of structural changes upon activation, were based on rhodopsin. At present, about a third of currently available GPCR structures are still from rhodopsin. In this review, I show some examples of how these structures can still be used to gain insight into general aspects of GPCR activation. First, the analysis of the third intracellular loop in rhodopsin structures allows us to gain an understanding of the structural and dynamic properties of this region, which is absent (due to protein engineering or poor electron density) in most of the currently available GPCR structures. Second, a detailed analysis of the structure of the transmembrane domains in inactive, intermediate and active rhodopsin structures allows us to detect early conformational changes in the process of ligand-induced GPCR activation. Finally, the analysis of a conserved ligand-activated transmission switch in the transmembrane bundle of GPCRs in the context of the rhodopsin activation cycle, allows us to suggest that the structures of many of the currently available agonist-bound GPCRs may correspond to intermediate active states. While the focus in GPCR structural biology is inevitably moving away from rhodopsin, in other aspects rhodopsin is still at the forefront. For instance, the first studies of the structural basis of disease mutants in GPCRs, or the most detailed analysis of cellular GPCR signal transduction networks using a systems biology approach, have been carried out in rhodopsin. Finally, due again to its unique properties among GPCRs, rhodopsin will likely play an important role in the application of X-ray free electron laser crystallography to time-resolved structural biology in membrane proteins. Rhodopsin, thus, still remains relevant as a model system to study the molecular mechanisms of GPCR activation. This article is part of a Special Issue entitled: Retinal Proteins—You can teach an old dog new tricks.     

Prediction of heterodimerization interfaces of G-protein coupled receptors with a new subtractive correlated mutation method

Recent studies employing differential epitope tagging, selective immunoprecipitation of receptor complexes and fluorescence or bioluminescence resonance energy transfer techniques provide direct evidence for heterodimerization between both closely and distantly related members of the G-protein coupled receptor (GPCR) family. Since heterodimerization appears to play a role in modulating agonist affinity, efficacy and/or trafficking properties, the molecular models of GPCRs required to understand receptor function must consider these oligomerization hypotheses. To advance knowledge in this field, we present here a computational approach based on correlated mutation analysis and the structural information contained in three-dimensional molecular models of the transmembrane regions of GPCRs built using the rhodopsin crystal structure as a template. The new subtractive correlated mutation method reveals likely heterodimerization interfaces amongst the different alternatives for the positioning of two tightly packed bundles of seven transmembrane domains next to each other in contact heterodimers of GPCRs. Predictions are applied to GPCRs in the class of opioid receptors. However, in the absence of a known structure of any GPCR dimer, the features of the method and predictions are also illustrated and analyzed for a dimeric complex of known structure.     

Gi-Coupled GPCR Signaling Controls the Formation and Organization of Human Pluripotent Colonies

Background

Reprogramming adult human somatic cells to create human induced pluripotent stem (hiPS) cell colonies involves a dramatic morphological and organizational transition. These colonies are morphologically indistinguishable from those of pluripotent human embryonic stem (hES) cells. G protein-coupled receptors (GPCRs) are required in diverse developmental processes, but their role in pluripotent colony morphology and organization is unknown. We tested the hypothesis that G_i-coupled GPCR signaling contributes to the characteristic morphology and organization of human pluripotent colonies.

Methodology/Principal Findings

Specific and irreversible inhibition of G_i-coupled GPCR signaling by pertussis toxin markedly altered pluripotent colony morphology. Wild-type hES and hiPS cells formed monolayer colonies, but colonies treated with pertussis toxin retracted inward, adopting a dense, multi-layered conformation. The treated colonies were unable to reform after a scratch wound insult, whereas control colonies healed completely within 48 h. In contrast, activation of an alternative GPCR pathway, G_s-coupled signaling, with cholera toxin did not affect colony morphology or the healing response. Pertussis toxin did not alter the proliferation, apoptosis or pluripotency of pluripotent stem cells.

Conclusions/Significance

Experiments with pertussis toxin suggest that G_i signaling plays a critical role in the morphology and organization of pluripotent colonies. These results may be explained by a G_i-mediated density-sensing mechanism that propels the cells radially outward. GPCRs are a promising target for modulating the formation and organization of hiPS and hES cell colonies and may be important for understanding somatic cell reprogramming and for engineering pluripotent stem cells for therapeutic applications.     

Critical analysis of the successes and failures of homology models of G protein‐coupled receptors

We present a critical assessment of the performance of our homology model refinement method for G protein‐coupled receptors (GPCRs), called LITICon that led to top ranking structures in a recent structure prediction assessment GPCRDOCK2010. GPCRs form the largest class of drug targets for which only a few crystal structures are currently available. Therefore, accurate homology models are essential for drug design in these receptors. We submitted five models each for human chemokine CXCR4 (bound to small molecule IT1t and peptide CVX15) and dopamine D3DR (bound to small molecule eticlopride) before the crystal structures were published. Our models in both CXCR4/IT1t and D3/eticlopride assessments were ranked first and second, respectively, by ligand RMSD to the crystal structures. For both receptors, we developed two types of protein models: homology models based on known GPCR crystal structures, and ab initio models based on the prediction method MembStruk. The homology‐based models compared better to the crystal structures than the ab initio models. However, a robust refinement procedure for obtaining high accuracy structures is needed. We demonstrate that optimization of the helical tilt, rotation, and translation is vital for GPCR homology model refinement. As a proof of concept, our in‐house refinement program LITiCon captured the distinct orientation of TM2 in CXCR4, which differs from that of adrenoreceptors. These findings would be critical for refining GPCR homology models in future. Proteins 2013. © 2012 Wiley Periodicals, Inc.     

Structural biology of G protein‐coupled receptor signaling complexes

G protein‐coupled receptors (GPCRs) constitute the largest family of cell surface receptors that mediate numerous cell signaling pathways, and are targets of more than one‐third of clinical drugs. Thanks to the advancement of novel structural biology technologies, high‐resolution structures of GPCRs in complex with their signaling transducers, including G‐protein and arrestin, have been determined. These 3D complex structures have significantly improved our understanding of the molecular mechanism of GPCR signaling and provided a structural basis for signaling‐biased drug discovery targeting GPCRs. Here we summarize structural studies of GPCR signaling complexes with G protein and arrestin using rhodopsin as a model system, and highlight the key features of GPCR conformational states in biased signaling including the sequence motifs of receptor TM6 that determine selective coupling of G proteins, and the phosphorylation codes of GPCRs for arrestin recruitment. We envision the future of GPCR structural biology not only to solve more high‐resolution complex structures but also to show stepwise GPCR signaling complex assembly and disassembly and dynamic process of GPCR signal transduction.     

GPCRs: an update on structural approaches to drug discovery

G-protein-coupled receptors (GPCRs) are a major opportunity for drug discovery in the post-genomic era. There are thought to be more than 500 therapeutically relevant GPCRs out of a total of over 700 identified to date, although only one, rhodopsin, has been the subject of a full 3D X-ray crystallography study. Two structurally related proteins, bacteriorhodopsin and sensory rhodopsin, which are not GPCRs but are part of the seven-helix membrane receptor family, have also been the subject of X-ray crystallographic studies and have been used in GPCR modeling studies. The significant differences between these rhodopsin structures, the relatively low sequence homology between individual GPCRs, and some difficulties in rationalizing point-mutation data suggests that homology-based molecular modeling alone will not provide the accurate structural information on individual receptors required for ligand design and in silico screening. In the absence of such structural information, several approaches can be used to assist in the discovery of ligands.     

Crystal Structure and Computational Modeling of the Fab Fragment from a Protective Anti-Ricin Monoclonal Antibody

Background

Many antibody crystal structures have been solved. Structural modeling programs have been developed that utilize this information to predict 3-D structures of an antibody based upon its sequence. Because of the problem of self-reference, the accuracy and utility of these predictions can only be tested when a new structure has not yet been deposited in the Protein Data Bank.

Methods

We have solved the crystal structure of the Fab fragment of RAC18, a protective anti-ricin mAb, to 1.9 Å resolution. We have also modeled the Fv structure of RAC18 using publicly available Ab modeling tools Prediction of Immunoglobulin Structures (PIGS), RosettaAntibody, and Web Antibody Modeling (WAM). The model structures underwent energy minimization. We compared results to the crystal structure on the basis of root-mean-square deviation (RMSD), template modeling score (TM-score), Z-score, and MolProbity analysis.

Findings

The crystal structure showed a pocket formed mainly by AA residues in each of the heavy chain complementarity determining regions (CDRs). There were differences between the crystal structure and structures predicted by the modeling tools, particularly in the CDRs. There were also differences among the predicted models, although the differences were small and within experimental error. No one modeling program was clearly superior to the others. In some cases, choosing structures based only on sequence homology to the crystallized Ab yielded RMSDs comparable to the models.

Conclusions

Molecular modeling programs accurately predict the structure of most regions of antibody variable domains of RAC18. The hypervariable CDRs proved most difficult to model, particularly H chain CDR3. Because CDR3 is most often involved in contact with antigen, this defect must be considered when using models to identify potential contacts between antibody and antigen. Because this study represents only a single case, the results cannot be generalized. Rather they highlight the utility and limitations of modeling programs.     

Activation of rhodopsin: new insights from structural and biochemical studies

G-protein-coupled receptors (GPCRs) are involved in a vast variety of cellular signal transduction processes from visual, taste and odor perceptions to sensing the levels of many hormones and neurotransmitters. As a result of agonist-induced conformation changes, GPCRs become activated and catalyze nucleotide exchange within the G proteins, thus detecting and amplifying the signal. GPCRs share a common heptahelical transmembrane structure as well as many conserved key residues and regions. Rhodopsins are prototypical GPCRs that detect photons in retinal photoreceptor cells and trigger a phototransduction cascade that culminates in neuronal signaling. Biophysical and biochemical studies of rhodopsin activation, and the recent crystal structure determination of bovine rhodopsin, have provided new information that enables a more complete mechanism of vertebrate rhodopsin activation to be proposed. In many aspects, rhodopsin might provide a structural and functional template for other members of the GPCR family.     

MT-Toolbox: improved amplicon sequencing using molecule tags

Background

Short oligonucleotides can be used as markers to tag and track DNA sequences. For example, barcoding techniques (i.e. Multiplex Identifiers or Indexing) use short oligonucleotides to distinguish between reads from different DNA samples pooled for high-throughput sequencing. A similar technique called molecule tagging uses the same principles but is applied to individual DNA template molecules. Each template molecule is tagged with a unique oligonucleotide prior to polymerase chain reaction. The resulting amplicon sequences can be traced back to their original templates by their oligonucleotide tag. Consensus building from sequences sharing the same tag enables inference of original template molecules thereby reducing effects of sequencing error and polymerase chain reaction bias. Several independent groups have developed similar protocols for molecule tagging; however, user-friendly software for build consensus sequences from molecule tagged reads is not readily available or is highly specific for a particular protocol.

Results

MT-Toolbox recognizes oligonucleotide tags in amplicons and infers the correct template sequence. On a set of molecule tagged test reads, MT-Toolbox generates sequences having on average 0.00047 errors per base. MT-Toolbox includes a graphical user interface, command line interface, and options for speed and accuracy maximization. It can be run in serial on a standard personal computer or in parallel on a Load Sharing Facility based cluster system. An optional plugin provides features for common 16S metagenome profiling analysis such as chimera filtering, building operational taxonomic units, contaminant removal, and taxonomy assignments.

Conclusions

MT-Toolbox provides an accessible, user-friendly environment for analysis of molecule tagged reads thereby reducing technical errors and polymerase chain reaction bias. These improvements reduce noise and allow for greater precision in single amplicon sequencing experiments.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-284) contains supplementary material, which is available to authorized users.     

Quantifying conformational changes in GPCRs: glimpse of a common functional mechanism

Background

G-protein-coupled receptors (GPCRs) are important drug targets and a better understanding of their molecular mechanisms would be desirable. The crystallization rate of GPCRs has accelerated in recent years as techniques have become more sophisticated, particularly with respect to Class A GPCRs interacting with G-proteins. These developments have made it possible for a quantitative analysis of GPCR geometrical features and binding-site conformations, including a statistical comparison between Class A GPCRs in active (agonist-bound) and inactive (antagonist-bound) states.

Results

Here we implement algorithms for the analysis of interhelical angles, distances, interactions and binding-site volumes in the transmembrane domains of 25 Class A GPCRs (7 active and 18 inactive). Two interhelical angles change in a statistically significant way between average inactive and active states: TM3-TM6 (by -9°) and TM6-TM7 (by +12°). A third interhelical angle: TM5-TM6 shows a trend, changing by -9°. In the transition from inactive to active states, average van der Waals interactions between TM3 and TM7 significantly increase as the average distance between them decreases by >2 Å. Average H-bonding between TM3 and TM6 decreases but is seemingly compensated by an increase in H-bonding between TM5 and TM6. In five Class A GPCRs, crystallized in both active and inactive states, increased H-bonding of agonists to TM6 and TM7, relative to antagonists, is observed. These protein-agonist interactions likely favour a change in the TM6-TM7 angle, which creates a narrowing in the binding pocket of activated receptors and an average ~200 ų reduction in volume.

Conclusions

In terms of similar conformational changes and agonist binding pattern, Class A GPCRs appear to share a common mechanism of activation, which can be exploited in future drug development.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0567-3) contains supplementary material, which is available to authorized users.     

Molecular dynamics simulations of bovine rhodopsin: influence of protonation states and different membrane-mimicking environments

G-protein coupled receptors (GPCRs) are a protein family of outstanding pharmaceutical interest. GPCR homology models, based on the crystal structure of bovine rhodopsin, have been shown to be valuable tools in the drug-design process. The initial model is often refined by molecular dynamics (MD) simulations, a procedure that has been recently discussed controversially. We therefore analyzed MD simulations of bovine rhodopsin in order to identify contacts that could serve as constraints in the simulation of homology models. Additionally, the effect of an N-terminal truncation, the nature of the membrane mimic, the influence of varying protonation states of buried residues and the importance of internal water molecules was analyzed. All simulations were carried out using the program-package GROMACS. While N-terminal truncation negatively influenced the overall protein stability, a stable simulation was possible in both solvent environments. As regards the protonation state of titratable sites, the experimental data could be reproduced by the program UHBD (University of Houston Brownian Dynamics), suggesting its application for studying homology models of GPCRs. A high flexibility was observed for internal water molecules at some sites. Finally, interhelical hydrogen-bonding interactions could be derived, which can now serve as constraints in the simulations of GPCR homology models.     

MOSBIE: a tool for comparison and analysis of rule-based biochemical models

Background

Mechanistic models that describe the dynamical behaviors of biochemical systems are common in computational systems biology, especially in the realm of cellular signaling. The development of families of such models, either by a single research group or by different groups working within the same area, presents significant challenges that range from identifying structural similarities and differences between models to understanding how these differences affect system dynamics.

Results

We present the development and features of an interactive model exploration system, MOSBIE, which provides utilities for identifying similarities and differences between models within a family. Models are clustered using a custom similarity metric, and a visual interface is provided that allows a researcher to interactively compare the structures of pairs of models as well as view simulation results.

Conclusions

We illustrate the usefulness of MOSBIE via two case studies in the cell signaling domain. We also present feedback provided by domain experts and discuss the benefits, as well as the limitations, of the approach.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-316) contains supplementary material, which is available to authorized users.