G-protein-coupled receptors modeling software tools | Protein structure data analysis
G-protein coupled receptors (GPCRs) are a superfamily of cell signaling membrane proteins that include >750 members in the human genome alone. They are the largest family of drug targets. The vast diversity and relevance of GPCRs contrasts with the paucity of structures available: only 21 unique GPCR structures have been experimentally determined as of the beginning of 2013. User-friendly modeling and small molecule docking tools are thus in great demand.
Allows user to visualize protein sequence features. GPCRHMM offers several advantages: users can zoom in on a region and zoom-dependent sequence rendering displays residues automatically at a sufficiently high zoom level. Moreover, researchers have control to customize the appearance of the data being displayed.
A web app for comparative modeling of G-protein coupled receptors (GPCR) begins with detection of close homologs with solved 3D structures. GPCRM integrates various approaches for template detection, alignment generation, model building, loop refinement and model filtering based on the Z-coordinate. GPCRM was designed to significantly decrease the time of structure generation and analysis needed in large scale biological projects. The platform can be used not only by computational biologists but also experimentalists to visualize their findings on theoretical models.
A web service for computational modeling and simulation of G-protein coupled receptors. GPCR-ModSim provides a modeling protocol for receptors and a molecular dynamics (MD) workflow for atomistic simulations in a lipidic membrane. GPCR-ModSim includes three main features: (i) the target receptor can be modeled in any of the three conformational states structurally characterized (inactive, partially-active, fully active); (ii) a novel modeling protocol gives the user the freedom to choose how to compose chimeric templates; (iii) MD refinement allows the receptor structure to undergo a final relaxation phase where a GPCR-conserved network of interhelical contacts is maintained through a series of pair-distance restraints.
Assists users in predicting amine-binding receptors from its amino acid sequence. GPCRsclass is a web application for recognizing and classifying different types of amine receptors. The method has been developed using a two-step strategy: (i) the method discriminates amine subfamily of G-protein-coupled receptors (GPCRs) from other proteins, such as globular proteins and (ii) the method predicts the type of amine receptor using multiclass support vector machine (SVM).
Samples conformations of the second extracellular loop (ECL2) of G-protein-coupled receptors (GPCRs) based on both template-based and ab initio approaches. GalaxyGPCRloop sampling strategy is independent of any specific energy functions, although steric clashes are evaluated and low-resolution, knowledge-based potential is used for final filtering. The software can be applied to studies of conformational changes relevant to function by providing an ensemble of possible conformations and/or in combination with docking algorithms.
Allows prediction of single point alanine mutations. LITiCon is a computational method for rapid prediction of thermostable mutation positions in a given G protein-coupled receptors (GPCRs) or any helical membrane protein. It is based on the generating of an ensemble of conformations. It permits users to identify properties obtained from molecular dynamics (MD) simulations of GPCR structures and detect the residues that communicate multiple allosteric pipelines.
Predicts G-protein coupling specificity using the support vector machine (SVM) and the hidden Markov model (HMM) methods. GRIFFIN employs the hierarchical SVM classifier using the feature vectors, which is useful for Class A G-protein coupled receptor (GPCR). For the opsins and olfactory subfamilies of Class A and other minor families (Classes B, C, frizzled and smoothened), this method predicted the binding G-protein with high accuracy using the HMM.