Cited by 28Receptor Mechanisms and SignalingComputational Drug Discovery MethodsProtein Structure and Dynamics

Modeling the Orthosteric Binding Site of the G Protein-Coupled Odorant Receptor OR5K1

Open access
Nicoli, Alessandro, Haag, Franziska, Marcinek, Patrick, He, Ruiming, Kreißl, Johanna, Stein, Jörg, Marchetto, Alessandro, Dunkel, Andreas +3 more·2023·Journal of Chemical Information and Modeling

Published version of a preprint

Abstract

With approximately 400 encoding genes in humans, odorant receptors (ORs) are the largest subfamily of class A G protein-coupled receptors (GPCRs). Despite its high relevance and representation, the odorant-GPCRome is structurally poorly characterized: no experimental structures are available, and the low sequence identity of ORs to experimentally solved GPCRs is a significant challenge for their modeling. Moreover, the receptive range of most ORs is unknown. The odorant receptor OR5K1 was recently and comprehensively characterized in terms of cognate agonists. Here, we report two additional agonists and functional data of the most potent compound on two mutants, L1043.32 and L2556.51. Experimental data was used to guide the investigation of the binding modes of OR5K1 ligands into the orthosteric binding site using structural information from AI-driven modeling, as recently released in the AlphaFold Protein Structure Database, and from homology modeling. Induced-fit docking simulations were used to sample the binding site conformational space for ensemble docking. Mutagenesis data guided side chain residue sampling and model selection. We obtained models that could better rationalize the different activity of active (agonist) versus inactive molecules with respect to starting models and also capture differences in activity related to minor structural differences. Therefore, we provide a model refinement protocol that can be applied to model the orthosteric binding site of ORs as well as that of GPCRs with low sequence identity to available templates.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/acs.jcim.2c00752

Cites

135 of 135 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Nicoli, A., Haag, F., Marcinek, P., He, R., Kreißl, J., Stein, J., Marchetto, A., Dunkel, A., Hofmann, T., Krautwurst, D., & Di Pizio, A.
Affiliations
  • Leibniz-Institute for Food Systems Biology at the Technical University of Munich (DE)
  • Leibniz Institute for Food Systems Biology at the Technical University of Munich , ,
  • Forschungszentrum Jülich (DE)
  • Technical University of Munich (DE)
Corresponding author
Krautwurst, Dietmar
Venue
Journal of Chemical Information and Modeling
Published
2023-01-25
Volume
63
Issue
7
Pages
2014-2029
ISSN
  • 1549-9596 (ISSN-L)
  • 1549-960X
OpenAlex
W4318023216
Cited by
28
References
135
Citations by year
2026: 7 · 2025: 9 · 2024: 7 · 2023: 5
FWCI
2.50
Type
journal article
Language
en
Open access
Locations
  • Journal of Chemical Information and Modeling (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion)
  • RWTH Publications (RWTH Aachen)
Funders
Deutsche Forschungsgemeinschaft (PI 1672/3-1)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Receptor Mechanisms and Signaling
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
Keywords
olfactory receptors, G protein-coupled receptors, orthosteric binding site, receptor modeling, induced fit docking, ensemble docking, AlphaFold structures, homology modeling, receptor mutants, model refinement
MeSH terms
Binding Sites, Humans, Ligands, Odorants, Receptors, Odorant, GTP-Binding Proteins, Receptors, G-Protein-Coupled

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review