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Template-based modeling of insect odorant receptors outperforms AlphaFold3 for ligand binding predictions

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Jabeen, Amara, Oakeshott, John Graham, Lee, Siu Fai, Ranganathan, Shoba, Taylor, Phillip W.·2024·Scientific Reports
DOI 10.1038/s41598-024-80094-xPMC PMC11585542

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Abstract

Insects rely on odorant receptors (ORs) to detect and respond to volatile environmental cues, so the ORs are attracting increasing interest as potential targets for pest control. However, experimental analysis of their structures and functions faces significant challenges. Computational methods such as template-based modeling (TBM) and AlphaFold3 (AF3) could facilitate the structural characterisation of ORs. This study first showed that both models accurately predicted the structural fold of MhOR5, a jumping bristletail OR with known experimental 3D structures, although accuracy was higher in the extracellular region of the protein and binding mode of their cognate ligands with TBM. The two approaches were then compared for their ability to predict the empirical binding evidence available for OR-odorant complexes in two economically important fruit fly species, Bactrocera dorsalis and B. minax. Post-simulation analyses including binding affinities, complex and ligand stability and receptor-ligand interactions (RLIs) revealed that TBM performed better than AF3 in discriminating between binder and non-binder complexes. TBM's superior performance is attributed to hydrophobicity-based helix-wise multiple sequence alignment (MSA) between available insect OR templates and the ORs for which the binding data were generated. This MSA identified conserved residues and motifs which could be used as anchor points for refining the alignments.

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Metadata

Authors
Jabeen, A., Oakeshott, J. G., Lee, S. F., Ranganathan, S., & Taylor, P. W.
Affiliations
  • Macquarie University (AU)
  • Commonwealth Scientific and Industrial Research Organisation (AU)
Corresponding author
Jabeen, Amara
ORCID
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2024-11-23
Volume
14
Issue
1
Pages
29084-29084
ISSN
2045-2322 (ISSN-L)
DOI
10.1038/s41598-024-80094-x
PMC
PMC11585542
OpenAlex
W4404655236
Cited by
11
References
4
Citations by year
2026: 8 · 2025: 2 · 2024: 1
FWCI
1.50
Type
journal article
Language
en
Open access
Licence
Locations
  • Scientific Reports (publishedVersion, cc-by-nc-nd)
  • Research Square (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Receptor Mechanisms and Signaling
  • Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
Keywords
insect odorant receptors, template-based modeling, AlphaFold3, ligand binding prediction, jumping bristletails, Bactrocera dorsalis, Bactrocera minax, fruit flies, ligand-receptor interactions, binding affinity, multiple sequence alignment, hydrophobicity, protein structure prediction, pest control targets
MeSH terms
Amino Acid Sequence, Animals, Binding Sites, Ligands, Models, Molecular, Protein Binding, Receptors, Odorant, Insect Proteins

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