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

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.