Title:A Novel Unified Ab Initio and Template-Based Approach to GPCR Modeling: Case of EDG-LPA Receptors.
VOLUME: 8 ISSUE: 5
Author(s):Olaposi I. Omotuyi and Hiroshi Ueda
Affiliation:Department of Molecular Pharmacology & Neuroscience, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki 852-8521, Japan.
Keywords:C-and N-terminal optimization, EDG-LPAs, GPCR modeling, mod refiner, I-TASSER.
Abstract:G-protein-coupled receptors (GPCRs) mediate diverse biological functions through intracellular signal
cascades initiated by intracellular G-protein coupling following extracellular agonist binding. GPCRs are quintessential
targets for drug design due to their involvement in pathophysiological conditions. The difficulty associated with GPCR
crystallization and lack of accurate computational method for GPCR modeling constitutes the major setbacks for GPCRbased
drug development. Here, we reported the combination of previously known ab initio and template-based methods as
a novel approach applicable for modeling geometrically optimized full-length GPCR. First, geometry-optimized
transmembrane helices (7Tms) of full-length GPCR are modeled using the GPCR server (http://gpcr.usc.es) followed by
loop-refinement. A second structure is generated via the Iterative approach as implemented on I-TASSER
(http://zhanglab.ccmb.med.umich.edu/I-TASSER/) server. The best Structures are then selected from the servers based on
DOPE-score (GPCR server) and C-score (I-TASSER server) and piped into ModRefiner algorithm as initial and reference
models respectively. ModRefiner drives the folding of the N- and C-termini regions of the initial model towards the
reference model without altering the local geometries of the 7Tms and the loop regions as evaluated by Local-Global
Alignment (LGA) algorithm. Finally, atomic clashes in the ModelRefiner output are resolved using Fragment-Guided
Molecular Dynamics (FG-MD) simulation. Comparatively, FG-MD output structures of our test proteins (Endothelial
Differentiation Gene-class (EDG) Lysophosphatidic acid receptors) have better model qualities than the initial and
reference structures as evaluated by the QmeanScore6 algorithm.
