Virtual Screening of Human Class-A GPCRs Using Ligand Profiles Built on Multiple Ligand–Receptor Interactions

G protein-coupled receptors (GPCRs) are a large family of integral membrane proteins responsible for cellular signal transductions. Identification of therapeutic compounds to regulate physiological processes is an important first step of drug discovery. We proposed MAGELLAN, a novel hierarchical vir...

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Bibliographic Details
Published in:Journal of molecular biology 2020-08, Vol.432 (17), p.4872-4890
Main Authors: Chan, Wallace K.B., Zhang, Yang
Format: Article
Language:English
Subjects:
Binding Sites
deorphanization
Drug Evaluation, Preclinical - methods
G protein-coupled receptors
Humans
ligand docking
Ligands
Molecular Docking Simulation
Protein Binding
Protein Conformation
protein structure prediction
Receptors, G-Protein-Coupled - chemistry
Receptors, G-Protein-Coupled - metabolism
Structure-Activity Relationship
virtual screening
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Summary:G protein-coupled receptors (GPCRs) are a large family of integral membrane proteins responsible for cellular signal transductions. Identification of therapeutic compounds to regulate physiological processes is an important first step of drug discovery. We proposed MAGELLAN, a novel hierarchical virtual-screening (VS) pipeline, which starts with low-resolution protein structure prediction and structure-based binding-site identification, followed by homologous GPCR detections through structure and orthosteric binding-site comparisons. Ligand profiles constructed from the homologous ligand–GPCR complexes are then used to thread through compound databases for VS. The pipeline was first tested in a large-scale retrospective screening experiment against 224 human Class A GPCRs, where MAGELLAN achieved a median enrichment factor (EF) of 14.38, significantly higher than that using individual ligand profiles. Next, MAGELLAN was examined on 5 and 20 GPCRs from two public VS databases (DUD-E and GPCR-Bench) and resulted in an average EF of 9.75 and 13.70, respectively, which compare favorably with other state-of-the-art docking- and ligand-based methods, including AutoDock Vina (with EF = 1.48/3.16 in DUD-E and GPCR-Bench), DOCK 6 (2.12/3.47 in DUD-E and GPCR-Bench), PoLi (2.2 in DUD-E), and FINDSITECcomb2.0 (2.90 in DUD-E). Detailed data analyses show that the major advantage of MAGELLAN is attributed to the power of ligand profiling, which integrates complementary methods for ligand–GPCR interaction recognition and thus significantly improves the coverage and sensitivity of VS models. Finally, cases studies on opioid and motilin receptors show that new connections between functionally related GPCRs can be visualized in the minimum spanning tree built on the similarities of predicted ligand-binding ensembles, suggesting a novel use of MAGELLAN for GPCR deorphanization. [Display omitted] •Developed a new pipeline for Class-A GPCR virtual screening•Proposed a novel concept to improve virtual screening based on ligand profiling•A novel approach to GPCR deorphanization through ligand-binding ensembles•Integrating composite pipelines improves ligand–GPCR interaction recognition•Stringent tests of pipelines on three large-scale virtual screening experiments
ISSN:0022-2836
1089-8638
DOI:10.1016/j.jmb.2020.07.003