Assessment and Challenges of Ligand Docking into Comparative Models of G-Protein Coupled Receptors

G-protein coupled receptors (GPCRs) are large protein families known to be important in many cellular processes. They are well known for their allosteric activation mechanisms. They are drug targets for several FDA-approved drugs. We have investigated the diversity of the ligand binding site for these class of proteins against their cognate ligands using computational docking, even if their structures are known in the ligand-complexed form. The cognate ligand of some of these receptors dock at allosteric binding site, with better score than the binding at the conservative site. Further, ligands obtained from GLASS database, which consists of experimentally verified GPCR ligands, also show allosteric binding to GPCRs. The allosteric binders show strong affinity to the binding site, though the residues at the binding site are not conserved across GPCR subfamilies.

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Ligand Docking Methods to Recognize Allosteric Inhibitors for G-Protein-Coupled Receptors

Bioinformatics and Biology Insights ◽

10.1177/11779322211037769 ◽

2021 ◽

Vol 15 ◽

pp. 117793222110377

Author(s):

K Harini ◽

S Jayashree ◽

Vikas Tiwari ◽

Sneha Vishwanath ◽

Ramanathan Sowdhamini

Keyword(s):

Binding Site ◽

G Protein ◽

Drug Targets ◽

Drug Binding ◽

G Protein Coupled Receptors ◽

Ligand Docking ◽

Amino Acid Residues ◽

Computational Docking ◽

Cellular Processes ◽

G Protein Coupled

G-protein-coupled receptors (GPCRs) are membrane proteins which play an important role in many cellular processes and are excellent drug targets. Despite the existence of several US Food and Drug Administration (FDA)-approved GPCR-targeting drugs, there is a continuing challenge of side effects owing to the nonspecific nature of drug binding. We have investigated the diversity of the ligand binding site for this class of proteins against their cognate ligands using computational docking, even if their structures are known already in the ligand-complexed form. The cognate ligand of some of these receptors dock at allosteric binding site with better score than the binding at the conservative site. Interestingly, amino acid residues at such allosteric binding site are not conserved across GPCR subfamilies. Such a computational approach can assist in the prediction of specific allosteric binders for GPCRs.

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patGPCR: A Multitemplate Approach for Improving 3D Structure Prediction of Transmembrane Helices of G-Protein-Coupled Receptors

Computational and Mathematical Methods in Medicine ◽

10.1155/2013/486125 ◽

2013 ◽

Vol 2013 ◽

pp. 1-12 ◽

Cited By ~ 2

Author(s):

Hongjie Wu ◽

Qiang Lü ◽

Lijun Quan ◽

Peide Qian ◽

Xiaoyan Xia

Keyword(s):

G Protein ◽

Structure Prediction ◽

Transmembrane Helix ◽

3D Structure ◽

G Protein Coupled Receptors ◽

Ligand Docking ◽

Molecular Function ◽

Transmembrane Helices ◽

G Protein Coupled ◽

Multiple Template

The structures of the seven transmembrane helices of G-protein-coupled receptors are critically involved in many aspects of these receptors, such as receptor stability, ligand docking, and molecular function. Most of the previous multitemplate approaches have built a “super” template with very little merging of aligned fragments from different templates. Here, we present a parallelized multitemplate approach, patGPCR, to predict the 3D structures of transmembrane helices of G-protein-coupled receptors. patGPCR, which employs a bundle-packing related energy function that extends on the RosettaMem energy, parallelizes eight pipelines for transmembrane helix refinement and exchanges the optimized helix structures from multiple templates. We have investigated the performance of patGPCR on a test set containing eight determined G-protein-coupled receptors. The results indicate that patGPCR improves the TM RMSD of the predicted models by 33.64% on average against a single-template method. Compared with other homology approaches, the best models for five of the eight targets built by patGPCR had a lower TM RMSD than that obtained from SWISS-MODEL; patGPCR also showed lower average TM RMSD than single-template and multiple-template MODELLER.

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Novel Computational Methodologies for Structural Modeling of Spacious Ligand Binding Sites of G-Protein-Coupled Receptors: Development and Application to Human Leukotriene B4 Receptor

The Scientific World JOURNAL ◽

10.1100/2012/691579 ◽

2012 ◽

Vol 2012 ◽

pp. 1-11 ◽

Cited By ~ 1

Author(s):

Yoko Ishino ◽

Takanori Harada

Keyword(s):

G Protein ◽

Time Scale ◽

Thermal Fluctuations ◽

Leukotriene B4 ◽

G Protein Coupled Receptors ◽

Dynamics Simulation ◽

Ligand Docking ◽

Leukotriene B4 Receptor ◽

G Protein Coupled ◽

Gpcr Protein

This paper describes a novel method to predict the activated structures of G-protein-coupled receptors (GPCRs) with high accuracy, while aiming for the use of the predicted 3D structures inin silicovirtual screening in the future. We propose a new method for modeling GPCR thermal fluctuations, where conformation changes of the proteins are modeled by combining fluctuations on multiple time scales. The core idea of the method is that a molecular dynamics simulation is used to calculate average 3D coordinates of all atoms of a GPCR protein against heat fluctuation on the picosecond or nanosecond time scale, and then evolutionary computation including receptor-ligand docking simulations functions to determine the rotation angle of each helix of a GPCR protein as a movement on a longer time scale. The method was validated using human leukotriene B4 receptor BLT1 as a sample GPCR. Our study demonstrated that the proposed method was able to derive the appropriate 3D structure of the active-state GPCR which docks with its agonists.

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An evaluation of automated in silico ligand docking of amino acid ligands to Family C G-protein coupled receptors

Bioorganic & Medicinal Chemistry ◽

10.1016/j.bmc.2005.10.052 ◽

2006 ◽

Vol 14 (6) ◽

pp. 2032-2039 ◽

Cited By ~ 13

Author(s):

Minghua Wang ◽

David R. Hampson

Keyword(s):

Amino Acid ◽

G Protein ◽

In Silico ◽

G Protein Coupled Receptors ◽

Ligand Docking ◽

G Protein Coupled

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Ligand Docking Methods to Recognize Allosteric Inhibitors for G-protein Coupled Receptors

10.21203/rs.3.rs-218684/v1 ◽

2021 ◽

Author(s):

Harini K ◽

Jayashree S ◽

Vikas Tiwari ◽

Sneha Vishwanath ◽

Ramanathan Sowdhamini

Keyword(s):

Binding Site ◽

G Protein ◽

Drug Targets ◽

Computational Approach ◽

G Protein Coupled Receptors ◽

Ligand Docking ◽

Allosteric Site ◽

Computational Docking ◽

Approved Drugs ◽

G Protein Coupled

Abstract BackgroundG-protein coupled receptors (GPCRs) are large protein families known to be important in many cellular processes. They are well known for their allosteric activation mechanisms. They are drug targets for several FDA-approved drugs. We have investigated the diversity of the ligand binding site for these class of proteins against their cognate ligands using computational docking, even if their structures are known in the ligand-complexed form. ResultsThe cognate ligand of some of these receptors dock at allosteric binding site, with better score than the binding at the conservative site. Further, ligands obtained from GLASS database, which consists of experimentally verified GPCR ligands, also show allosteric binding to GPCRs. The allosteric binders show strong affinity to the binding site, though the residues at the binding site are not conserved across GPCR subfamilies.ConclusionsBased on our computational approach it was found that the residues at the allosteric site are not as conserved as in the cognate binding site, which might explain the specificity of a particular GPCR. Further, for certain GPCRs, some of their known cognate ligands were predicted to have better binding preference towards the allosteric site than orthosteric site and therefore this computational approach can assist in the prediction of allosteric binders for GPCRs.

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Multi-state Modeling of G-protein Coupled Receptors at Experimental Accuracy

10.1101/2021.11.26.470086 ◽

2021 ◽

Author(s):

Lim Heo ◽

Michael Feig

Keyword(s):

Ligand Binding ◽

G Protein ◽

Structural Changes ◽

High Accuracy ◽

G Protein Coupled Receptors ◽

Ligand Docking ◽

Gpcr Activation ◽

The Family ◽

Activation Mechanisms ◽

G Protein Coupled

The family of G-protein coupled receptors (GPCRs) is one of the largest protein families in the human genome. GPCRs transduct chemical signals from extracellular to intracellular regions via a conformational switch between active and inactive states upon ligand binding. While experimental structures of GPCRs remain limited, high-accuracy computational predictions are now possible with AlphaFold2. However, AlphaFold2 only predicts one state and is biased towards the inactive conformation. Here, a multi-state prediction protocol is introduced that extends AlphaFold2 to predict either active or inactive states at very high accuracy using state-annotated templated GPCR databases. The predicted models accurately capture the main structural changes upon activation of the GPCR at the atomic level. The models were also highly successful in predicting ligand binding poses via protein-ligand docking. We expect that high accuracy GPCR models in both activation states will promote understanding in GPCR activation mechanisms and drug discovery for GPCRs. At the time, the new protocol paves the way towards capturing the dynamics of proteins at high-accuracy via machine-learning methods.

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