scholarly journals Application for Evaluating and Visualizing the Sequence Conservation of Ligand-binding Sites

2015 ◽  
Vol 8 (0) ◽  
pp. 9-13 ◽  
Author(s):  
Nobuaki Yasuo ◽  
Masakazu Sekijima
Keyword(s):  
Ligand Binding ◽  
Binding Sites ◽  
Sequence Conservation ◽  
Ligand Binding Sites

scholarly journals Locating ligand binding sites in G-protein coupled receptors using combined information from docking and sequence conservation

2018 ◽  
Author(s):  
Ashley R. Vidad ◽  
Stephen Macaspac ◽  
Ho-Leung Ng
Keyword(s):  
Ligand Binding ◽  
G Protein ◽  
Binding Sites ◽  
G Protein Coupled Receptors ◽  
Sequence Conservation ◽  
Surface Geometry ◽  
A2a Adenosine Receptors ◽  
Ligand Binding Sites ◽  
G Protein Coupled ◽  
Homology Models

AbstractG-protein coupled receptors (GPCRs) are the largest protein family of drug targets. Detailed mechanisms of binding are unknown for many important GPCR-ligand pairs due to the difficulties of GPCR recombinant expression, biochemistry, and crystallography. We describe our new method, ConDock, for predicting ligand binding sites in GPCRs using combined information from surface conservation and docking starting from crystal structures or homology models. We demonstrate the effectiveness of ConDock on well-characterized GPCRs such as the β2 adrenergic and A2A adenosine receptors. We also demonstrate that ConDock successfully predicts ligand binding sites from high-quality homology models. Finally, we apply ConDock to predict ligand binding sites on a structurally uncharacterized GPCR, GPER. GPER is the G-protein coupled estrogen receptor, with four known ligands: estradiol, G1, G15, and tamoxifen. ConDock predicts that all four ligands bind to the same location on GPER, centered on L119, H307, and N310; this site is deeper in the receptor cleft than predicted by previous studies. We compare the sites predicted by ConDock and traditional methods that utilize information from surface geometry, surface conservation, and ligand chemical interactions. Incorporating sequence conservation information in ConDock overcomes errors introduced from physics-based scoring functions and homology modeling.

scholarly journals Predicting Protein Ligand Binding Sites by Combining Evolutionary Sequence Conservation and 3D Structure

2009 ◽  
Vol 5 (12) ◽  
pp. e1000585 ◽  
Author(s):  
John A. Capra ◽  
Roman A. Laskowski ◽  
Janet M. Thornton ◽  
Mona Singh ◽  
Thomas A. Funkhouser
Keyword(s):  
Ligand Binding ◽  
Binding Sites ◽  
3D Structure ◽  
Sequence Conservation ◽  
Evolutionary Sequence ◽  
Ligand Binding Sites

scholarly journals Locating ligand binding sites in G-protein coupled receptors using combined information from docking and sequence conservation

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12219
Author(s):  
Ashley Ryan Vidad ◽  
Stephen Macaspac ◽  
Ho Leung Ng
Keyword(s):  
Ligand Binding ◽  
G Protein ◽  
Binding Sites ◽  
G Protein Coupled Receptors ◽  
Sequence Conservation ◽  
A2a Adenosine Receptors ◽  
Class A ◽  
Ligand Binding Sites ◽  
G Protein Coupled ◽  
Homology Models

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.

scholarly journals Locating the ligand binding Sites for the G-protein coupled estrogen receptor (GPER) using combined information from docking and sequence conservation

2016 ◽  
Author(s):  
Ashley R. Vidad ◽  
Stephen Macaspac ◽  
Ho Leung Ng
Keyword(s):  
Estrogen Receptor ◽  
Ligand Binding ◽  
G Protein ◽  
Binding Sites ◽  
Sequence Conservation ◽  
Ligand Docking ◽  
Scoring Functions ◽  
Surface Geometry ◽  
Ligand Binding Sites ◽  
G Protein Coupled

AbstractHigh concentrations of estrogenic compounds can overstimulate estrogen receptors and potentially lead to breast, ovarian, and cervical cancers. Recently, a G-protein coupled estrogen receptor (GPER/GPR30) was discovered that has no structural similarity to the well-characterized, classical estrogen receptor ERα. The crystal structure of GPER has not yet been determined, and the ligand binding sites have not yet been experimentally identified. The recent explosion of GPCR crystal structures now allow homology modeling with unprecedented reliability. We create, validate, and describe a homology model for GPER. We describe and apply ConDock, the first hybrid scoring function to use information from protein surface conservation and ligand docking, to predict binding sites on GPER for four ligands, estradiol, G1, G15, and tamoxifen. ConDock is a simple product function of sequence conservation and binding energy scores. ConDock predicts that all four ligands bind to the same location on GPER, centered on L119, H307, and N310; this site is deeper in the receptor cleft than are ligand binding sites predicted by previous studies. We compare the sites predicted by ConDock and traditional methods analyzing surface geometry, surface conservation, and ligand chemical interactions. Incorporating sequence conservation information in ConDock avoids errors resulting from physics-based scoring functions and modeling.

scholarly journals Diversity in the structures and ligand-binding sites of nematode fatty acid and retinol-binding proteins revealed by Na-FAR-1 from Necator americanus

2015 ◽  
Vol 471 (3) ◽  
pp. 403-414 ◽  
Author(s):  
M. Florencia Rey-Burusco ◽  
Marina Ibáñez-Shimabukuro ◽  
Mads Gabrielsen ◽  
Gisela R. Franchini ◽  
Andrew J. Roe ◽  
...  
Keyword(s):  
Fatty Acid ◽  
Ligand Binding ◽  
Tissue Distribution ◽  
Binding Sites ◽  
Binding Proteins ◽  
Retinol Binding Protein ◽  
Internal Cavity ◽  
Binding Characteristics ◽  
Necator Americanus ◽  
Ligand Binding Sites

Necator americanus fatty acid and retinol-binding protein-1 (Na-FAR-1) is an abundantly expressed FAR from a parasitic hookworm. The present work describes its tissue distribution, structure and ligand-binding characteristics and shows that Na-FAR-1 expands to transport multiple FA molecules in its internal cavity.

scholarly journals Adenosine Receptors of Cerebral Microvessels and Choroid Plexus

1986 ◽  
Vol 6 (4) ◽  
pp. 463-470 ◽  
Author(s):  
Rajesh N. Kalaria ◽  
Sami I. Harik
Keyword(s):  
Cerebral Cortex ◽  
Ligand Binding ◽  
Choroid Plexus ◽  
Adenosine Receptors ◽  
Binding Sites ◽  
Specific Binding ◽  
Cerebral Microvessels ◽  
High Affinity ◽  
Receptor Sites ◽  
Ligand Binding Sites

We studied, by ligand binding methods, the two adenosine receptors, A, and A2, in rat and pig cerebral microvessels and pig choroid plexus. Ligand binding to cerebral microvessels was compared with that to membranes of the cerebral cortex. [3H]Cyclohexyladenosine and [3H]l-phenylisopropyladenosine were the ligands used for A1-receptors, and [3H]5'- N-ethylcarboxamide adenosine ([3H]NECA) was used to assess A2-receptors. We report that cerebral microvessels and choroid plexus exhibit specific [3H]NECA binding, but have no appreciable A1-receptor ligand binding sites. Specific binding of [3H]NECA to cerebral microvessels, choroid plexus, and cerebral cortex was saturable and suggested the existence of two classes of A2-receptor sites: high-affinity ( Kd ∼ 250 n M) and low-affinity ( Kd ∼ 1–2 μ M) sites. The Kd and Bmax of NECA binding to cerebral microvessels and cerebral cortex were similar within each species. Our results, indicating the existence of A2-receptors in cerebral microvessels, are consistent with results of increased adenylate cyclase activity by adenosine and some of its analogues in these microvessels.

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