Ligand Docking Methods to Recognize Allosteric Inhibitors for G-Protein-Coupled Receptors
Ontology highlight
ABSTRACT:
SUBMITTER: Harini K
PROVIDER: S-EPMC8558589 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The rapidly increasing number of high-resolution X-ray structures of G-protein coupled receptors (GPCRs) creates a unique opportunity to employ comparative modeling and docking to provide valuable insight into the function and ligand binding determinants of novel receptors, to assist in virtual screening and to design and optimize drug candidates. However, low sequence identity between receptors, conformational flexibility, and chemical diversity of ligands present an enormous challenge to molecular modeling approaches. It is our hypothesis that rapid Monte-Carlo sampling of protein backbone and side-chain conformational space with Rosetta can be leveraged to meet this challenge. This study performs unbiased comparative modeling and docking methodologies using 14 distinct high-resolution GPCRs and proposes knowledge-based filtering methods for improvement of sampling performance and identification of correct ligand-receptor interactions. On average, top ranked receptor models built on template structures over 50% sequence identity are within 2.9 Å of the experimental structure, with an average root mean square deviation (RMSD) of 2.2 Å for the transmembrane region and 5 Å for the second extracellular loop. Furthermore, these models are consistently correlated with low Rosetta energy score. To predict their binding modes, ligand conformers of the 14 ligands co-crystalized with the GPCRs were docked against the top ranked comparative models. In contrast to the comparative models themselves, however, it remains difficult to unambiguously identify correct binding modes by score alone. On average, sampling performance was improved by 10(3) fold over random using knowledge-based and energy-based filters. In assessing the applicability of experimental constraints, we found that sampling performance is increased by one order of magnitude for every 10 residues known to contact the ligand. Additionally, in the case of DOR, knowledge of a single specific ligand-protein contact improved sampling efficiency 7 fold. These findings offer specific guidelines which may lead to increased success in determining receptor-ligand complexes.
| S-EPMC3699586 | biostudies-literature
Project description:G protein-coupled receptors (GPCRs) are allosteric proteins, because their signal transduction relies on interactions between topographically distinct, yet conformationally linked, domains. Much of the focus on GPCR allostery in the new millennium, however, has been on modes of targeting GPCR allosteric sites with chemical probes due to the potential for novel therapeutics. It is now apparent that some GPCRs possess more than one targetable allosteric site, in addition to a growing list of putative endogenous modulators. Advances in structural biology are also shedding new insights into mechanisms of allostery, although the complexities of candidate allosteric drugs necessitate rigorous biological characterization.
| S-EPMC4528113 | biostudies-literature
Project description:The binding of ligands to G-protein-coupled receptors (GPCRs) in the extracellular region transmits the signal to the intracellular region to initiate coupling to effector proteins. The mechanism of this allosteric communication remains largely unexplored. Knowledge of the residues involved in the pipeline of the allosteric communication from the extracellular to the intracellular region will provide means to (a) design ligands with bias in potency towards one signaling pathway over others, and (b) design allosteric modulators that show subtype selectivity in GPCRs. In this review we describe the current state of the computational methods that provide insights into the allosteric communication in GPCRs and elucidate how this information can be used to design allosteric modulators.
| S-EPMC5127785 | biostudies-literature
Project description:GPCRs (G-protein coupled receptors) are the largest family of drug targets and share a conserved structure. Binding sites are unknown for many important GPCR ligands due to the difficulties of GPCR recombinant expression, biochemistry, and crystallography. We describe our approach, ConDockSite, for predicting ligand binding sites in class A GPCRs using combined information from surface conservation and docking, starting from crystal structures or homology models. We demonstrate the effectiveness of ConDockSite on crystallized class A GPCRs such as the beta2 adrenergic and A2A adenosine receptors. We also demonstrate that ConDockSite successfully predicts ligand binding sites from high-quality homology models. Finally, we apply ConDockSite to predict the ligand binding sites on a structurally uncharacterized GPCR, GPER, the G-protein coupled estrogen receptor. Most of the sites predicted by ConDockSite match those found in other independent modeling studies. ConDockSite predicts that four ligands bind to a common location on GPER at a site deep in the receptor cleft. Incorporating sequence conservation information in ConDockSite overcomes errors introduced from physics-based scoring functions and homology modeling.
| S-EPMC8475542 | biostudies-literature
Project description:The past few years have seen spectacular progress in the structure determination of G protein-coupled receptors (GPCRs). We now have structural representatives from classes A, B, C, and F. Within the rhodopsin-like class A, most structures belong to the ? group, whereas fewer GPCR structures are available from the ?, ?, and ? groups, which include peptide GPCRs such as the receptors for neurotensin (? group), opioids, chemokines (? group), and protease-activated receptors (? group). Structural information on peptide GPCRs is restricted to complexes with non-peptidic drug-like antagonists with the exception of the chemokine receptor CXCR4 that has been crystallized in the presence of a cyclic peptide antagonist. Notably, the neurotensin receptor 1 is to date the only peptide GPCR whose structure has been solved in the presence of a peptide agonist. Although limited in number, the current peptide GPCR structures reveal great diversity in shape and electrostatic properties of the ligand binding pockets, features that play key roles in the discrimination of ligands. Here, we review these aspects of peptide GPCRs in view of possible models for peptide agonist binding.
| S-EPMC4360564 | biostudies-literature
Project description:Allosteric coupling describes a reciprocal process whereby G-protein-coupled receptors (GPCRs) relay ligand-induced conformational changes from the extracellular binding pocket to the intracellular signaling surface. Therefore, GPCR activation is sensitive to both the type of extracellular ligand and intracellular signaling protein. We hypothesized that ligand-specific allosteric coupling may result in preferential (i.e., biased) engagement of downstream effectors. However, the structural basis underlying ligand-dependent control of this essential allosteric mechanism is poorly understood. Here, we show that two sets of extended muscarinic acetylcholine receptor M1 agonists, which only differ in linker length, progressively constrain receptor signaling. We demonstrate that stepwise shortening of their chemical linker gradually hampers binding pocket closure, resulting in divergent coupling to distinct G-protein families. Our data provide an experimental strategy for the design of ligands with selective G-protein recognition and reveal a potentially general mechanism of ligand-specific allosteric coupling.
| S-EPMC7551708 | biostudies-literature
Project description:Allosteric modulation of G protein-coupled receptors represent a promising mechanism of pharmacological intervention. Dramatic developments witnessed in the structural biology of membrane proteins continue to reveal that the binding sites of allosteric modulators are widely distributed, including along protein surfaces. Here we restrict consideration to intrahelical and intracellular sites together with allosteric conformational locks, and show that the protein mapping tools FTMap and FTSite identify 83% and 88% of such experimentally confirmed allosteric sites within the three strongest sites found. The methods were also able to find partially hidden allosteric sites that were not fully formed in X-ray structures crystallized in the absence of allosteric ligands. These results confirm that the intrahelical sites capable of binding druglike allosteric modulators are among the strongest ligand recognition sites in a large fraction of GPCRs and suggest that both FTMap and FTSite are useful tools for identifying allosteric sites and to aid in the design of such compounds in a range of GPCR targets.
| S-EPMC6467999 | biostudies-literature
Project description:G protein-coupled Receptors (GPCRs) play a central role in many physiological processes and, consequently, constitute important drug targets. In particular, the search for allosteric drugs has recently drawn attention, since they could be more selective and lead to fewer side effects. Accordingly, computational tools have been used to estimate the druggability of allosteric sites in these receptors. In spite of many successful results, the problem is still challenging, particularly the prediction of hydrophobic sites in the interface between the protein and the membrane. In this work, we propose a complementary approach, based on dynamical correlations. Our basic hypothesis was that allosteric sites are strongly coupled to regions of the receptor that undergo important conformational changes upon activation. Therefore, using ensembles of experimental structures, normal mode analysis and molecular dynamics simulations we calculated correlations between internal fluctuations of different sites and a collective variable describing the activation state of the receptor. Then, we ranked the sites based on the strength of their coupling to the collective dynamics. In the β2 adrenergic (β2AR), glucagon (GCGR) and M2 muscarinic receptors, this procedure allowed us to correctly identify known allosteric sites, suggesting it has predictive value. Our results indicate that this dynamics-based approach can be a complementary tool to the existing toolbox to characterize allosteric sites in GPCRs.
| S-EPMC7795036 | biostudies-literature
Project description:Topographically distinct, druggable, allosteric sites may be present on all G protein-coupled receptors (GPCRs). As such, targeting these sites with synthetic small molecules offers an attractive approach to develop receptor-subtype selective chemical leads for the development of novel therapies. A crucial part of drug development is to understand the acute and chronic effects of such allosteric modulators at their corresponding GPCR target. Key regulatory processes including cell-surface delivery, endocytosis, recycling, and down-regulation tightly control the number of receptors at the surface of the cell. As many GPCR therapeutics will be administered chronically, understanding how such ligands modulate these regulatory pathways forms an essential part of the characterization of novel GPCR ligands. This is true for both orthosteric and allosteric ligands. In this Review, we summarize our current understanding of GPCR regulatory processes with a particular focus on the effects and implications of allosteric targeting of GPCRs.
| S-EPMC3629737 | biostudies-other
Project description:IntroductionThe affinity constants of a ligand for active and inactive states of a receptor ultimately determine its capacity to activate downstream signaling events. In this report, we describe a reverse-engineering strategy for estimating these microscopic constants.MethodsOur approach involves analyzing responses measured downstream in the signaling pathway of a G protein-coupled receptor under conditions of allosteric modulation and reduced receptor expression or partial receptor inactivation. The analysis also yields estimates of the isomerization constant of the unoccupied receptor, the sensitivity constant of the signaling pathway, and the more empirical parameters of the receptor population including the observed affinities and efficacies of allosteric and orthosteric ligands - including inverse agonists - and the efficacy of the unoccupied receptor (i.e., constitutive activity).Results and discussionWe validate our approach with an analytical proof and by analysis of simulated data. We also use our method to analyze data from the literature. We show that the values of the microscopic constants of orthosteric and allosteric ligands are constant regardless of the allosteric interaction and the nature of the receptor-signaling pathway as long as the same active state mediates the response. Our analysis is useful for quantifying probe-dependent allosteric interactions and the selectivity of agonists for different signaling pathways. Knowing the isomerization constant and sensitivity constant of a signaling pathway in a given cell line or tissue preparation enables future investigators to estimate the affinity constants of agonists for receptor states simply through analysis of their concentration-response curves. Our approach also provides a means of validating in silico estimates of ligand affinity for crystal structures of active and inactive states of the receptor.
| S-EPMC4028174 | biostudies-literature