Structure-based prediction of g-protein-coupled receptor ligand function: A β-adrenoceptor case study

Research output: Contribution to journalJournal articleResearchpeer-review

Standard

Structure-based prediction of g-protein-coupled receptor ligand function : A β-adrenoceptor case study. / Kooistra, Albert J.; Leurs, Rob; De Esch, Iwan J.P.; De Graaf, Chris.

In: Journal of Chemical Information and Modeling, Vol. 55, No. 5, 26.05.2015, p. 1045-1061.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Kooistra, AJ, Leurs, R, De Esch, IJP & De Graaf, C 2015, 'Structure-based prediction of g-protein-coupled receptor ligand function: A β-adrenoceptor case study', Journal of Chemical Information and Modeling, vol. 55, no. 5, pp. 1045-1061. https://doi.org/10.1021/acs.jcim.5b00066

APA

Kooistra, A. J., Leurs, R., De Esch, I. J. P., & De Graaf, C. (2015). Structure-based prediction of g-protein-coupled receptor ligand function: A β-adrenoceptor case study. Journal of Chemical Information and Modeling, 55(5), 1045-1061. https://doi.org/10.1021/acs.jcim.5b00066

Vancouver

Kooistra AJ, Leurs R, De Esch IJP, De Graaf C. Structure-based prediction of g-protein-coupled receptor ligand function: A β-adrenoceptor case study. Journal of Chemical Information and Modeling. 2015 May 26;55(5):1045-1061. https://doi.org/10.1021/acs.jcim.5b00066

Author

Kooistra, Albert J. ; Leurs, Rob ; De Esch, Iwan J.P. ; De Graaf, Chris. / Structure-based prediction of g-protein-coupled receptor ligand function : A β-adrenoceptor case study. In: Journal of Chemical Information and Modeling. 2015 ; Vol. 55, No. 5. pp. 1045-1061.

Bibtex

@article{5728c12855914b5587c7a3ad9cd4de11,
title = "Structure-based prediction of g-protein-coupled receptor ligand function: A β-adrenoceptor case study",
abstract = "The spectacular advances in G-protein-coupled receptor (GPCR) structure determination have opened up new possibilities for structure-based GPCR ligand discovery. The structure-based prediction of whether a ligand stimulates (full/partial agonist), blocks (antagonist), or reduces (inverse agonist) GPCR signaling activity is, however, still challenging. A total of 31 β1 (β1R) and β2 (β2R) adrenoceptor crystal structures, including antagonist, inverse agonist, and partial/full agonist-bound structures, allowed us to explore the possibilities and limitations of structure-based prediction of GPCR ligand function. We used all unique protein-ligand interaction fingerprints (IFPs) derived from all ligand-bound β-adrenergic crystal structure monomers to post-process the docking poses of known β1R/β2R partial/full agonists, antagonists/inverse agonists, and physicochemically similar decoys in each of the β1R/β2R structures. The systematic analysis of these 1920 unique IFP-structure combinations offered new insights into the relative impact of protein conformation and IFP scoring on selective virtual screening (VS) for ligands with a specific functional effect. Our studies show that ligands with the same function can be efficiently classified on the basis of their protein-ligand interaction profile. Small differences between the receptor conformation (used for docking) and reference IFP (used for scoring of the docking poses) determine, however, the enrichment of specific ligand types in VS hit lists. Interestingly, the selective enrichment of partial/full agonists can be achieved by using agonist IFPs to post-process docking poses in agonist-bound as well as antagonist-bound structures. We have identified optimal structure-IFP combinations for the identification and discrimination of antagonists/inverse agonist and partial/full agonists, and defined a predicted IFP for the small full agonist norepinephrine that gave the highest retrieval rate of agonists over antagonists for all structures (with an enrichment factor of 46 for agonists and 8 for antagonists on average at a 1{\%} false-positive rate). This β-adrenoceptor case study provides new insights into the opportunities for selective structure-based discovery of GPCR ligands with a desired function and emphasizes the importance of IFPs in scoring docking poses.",
author = "Kooistra, {Albert J.} and Rob Leurs and {De Esch}, {Iwan J.P.} and {De Graaf}, Chris",
year = "2015",
month = "5",
day = "26",
doi = "10.1021/acs.jcim.5b00066",
language = "English",
volume = "55",
pages = "1045--1061",
journal = "Journal of Chemical Information and Modeling",
issn = "1549-9596",
publisher = "American Chemical Society",
number = "5",

}

RIS

TY - JOUR

T1 - Structure-based prediction of g-protein-coupled receptor ligand function

T2 - A β-adrenoceptor case study

AU - Kooistra, Albert J.

AU - Leurs, Rob

AU - De Esch, Iwan J.P.

AU - De Graaf, Chris

PY - 2015/5/26

Y1 - 2015/5/26

N2 - The spectacular advances in G-protein-coupled receptor (GPCR) structure determination have opened up new possibilities for structure-based GPCR ligand discovery. The structure-based prediction of whether a ligand stimulates (full/partial agonist), blocks (antagonist), or reduces (inverse agonist) GPCR signaling activity is, however, still challenging. A total of 31 β1 (β1R) and β2 (β2R) adrenoceptor crystal structures, including antagonist, inverse agonist, and partial/full agonist-bound structures, allowed us to explore the possibilities and limitations of structure-based prediction of GPCR ligand function. We used all unique protein-ligand interaction fingerprints (IFPs) derived from all ligand-bound β-adrenergic crystal structure monomers to post-process the docking poses of known β1R/β2R partial/full agonists, antagonists/inverse agonists, and physicochemically similar decoys in each of the β1R/β2R structures. The systematic analysis of these 1920 unique IFP-structure combinations offered new insights into the relative impact of protein conformation and IFP scoring on selective virtual screening (VS) for ligands with a specific functional effect. Our studies show that ligands with the same function can be efficiently classified on the basis of their protein-ligand interaction profile. Small differences between the receptor conformation (used for docking) and reference IFP (used for scoring of the docking poses) determine, however, the enrichment of specific ligand types in VS hit lists. Interestingly, the selective enrichment of partial/full agonists can be achieved by using agonist IFPs to post-process docking poses in agonist-bound as well as antagonist-bound structures. We have identified optimal structure-IFP combinations for the identification and discrimination of antagonists/inverse agonist and partial/full agonists, and defined a predicted IFP for the small full agonist norepinephrine that gave the highest retrieval rate of agonists over antagonists for all structures (with an enrichment factor of 46 for agonists and 8 for antagonists on average at a 1% false-positive rate). This β-adrenoceptor case study provides new insights into the opportunities for selective structure-based discovery of GPCR ligands with a desired function and emphasizes the importance of IFPs in scoring docking poses.

AB - The spectacular advances in G-protein-coupled receptor (GPCR) structure determination have opened up new possibilities for structure-based GPCR ligand discovery. The structure-based prediction of whether a ligand stimulates (full/partial agonist), blocks (antagonist), or reduces (inverse agonist) GPCR signaling activity is, however, still challenging. A total of 31 β1 (β1R) and β2 (β2R) adrenoceptor crystal structures, including antagonist, inverse agonist, and partial/full agonist-bound structures, allowed us to explore the possibilities and limitations of structure-based prediction of GPCR ligand function. We used all unique protein-ligand interaction fingerprints (IFPs) derived from all ligand-bound β-adrenergic crystal structure monomers to post-process the docking poses of known β1R/β2R partial/full agonists, antagonists/inverse agonists, and physicochemically similar decoys in each of the β1R/β2R structures. The systematic analysis of these 1920 unique IFP-structure combinations offered new insights into the relative impact of protein conformation and IFP scoring on selective virtual screening (VS) for ligands with a specific functional effect. Our studies show that ligands with the same function can be efficiently classified on the basis of their protein-ligand interaction profile. Small differences between the receptor conformation (used for docking) and reference IFP (used for scoring of the docking poses) determine, however, the enrichment of specific ligand types in VS hit lists. Interestingly, the selective enrichment of partial/full agonists can be achieved by using agonist IFPs to post-process docking poses in agonist-bound as well as antagonist-bound structures. We have identified optimal structure-IFP combinations for the identification and discrimination of antagonists/inverse agonist and partial/full agonists, and defined a predicted IFP for the small full agonist norepinephrine that gave the highest retrieval rate of agonists over antagonists for all structures (with an enrichment factor of 46 for agonists and 8 for antagonists on average at a 1% false-positive rate). This β-adrenoceptor case study provides new insights into the opportunities for selective structure-based discovery of GPCR ligands with a desired function and emphasizes the importance of IFPs in scoring docking poses.

UR - http://www.scopus.com/inward/record.url?scp=84930227130&partnerID=8YFLogxK

U2 - 10.1021/acs.jcim.5b00066

DO - 10.1021/acs.jcim.5b00066

M3 - Journal article

C2 - 25848966

AN - SCOPUS:84930227130

VL - 55

SP - 1045

EP - 1061

JO - Journal of Chemical Information and Modeling

JF - Journal of Chemical Information and Modeling

SN - 1549-9596

IS - 5

ER -

ID: 199353285