Towards improved quality of GPCR models by usage of multiple templates and profile-profile comparison

Autor: Teresa Carlomagno, Slawomir Filipek, Dorota Latek, Pawel Pasznik
Jazyk: angličtina
Rok vydání: 2013
Předmět:
Models
Molecular
Protein Structure
Rhodopsin
Receptor
Adenosine A2A
Protein Conformation
Biophysics
Structure Prediction
lcsh:Medicine
Sequence alignment
Computational biology
Biology
Biochemistry
Computer Applications
Receptors
G-Protein-Coupled
Protein structure
Drug Discovery
Molecular Cell Biology
Macromolecular Structure Analysis
Signaling in Cellular Processes
Humans
Loop modeling
Biomacromolecule-Ligand Interactions
lcsh:Science
Sequence
Multidisciplinary
lcsh:R
Proteins
Computational Biology
MODELLER
Genomics
Protein structure prediction
Adrenergic beta-1 Receptor Antagonists
Transmembrane Proteins
Molecular Docking Simulation
Transmembrane domain
G-Protein Signaling
Template
Computer Science
Receptors
Calcitriol
lcsh:Q
Receptors
Adrenergic
beta-1
Research Article
Signal Transduction
Computer Modeling
Zdroj: PLoS ONE, Vol 8, Iss 2, p e56742 (2013)
PLoS ONE
ISSN: 1932-6203
Popis: 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
Databáze: OpenAIRE
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