Macquarie University
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A semi-automated workflow for structural modelling of insect odorant receptors

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posted on 2024-03-26, 23:20 authored by Vaanathi Chidambara Thanu

Background: Insects utilize seven transmembrane (7TM) odorant receptors (iORs), to identify chemical cues within the environment. For the biocontrol of insect pests, novel odorants are urgently needed, which require 3D iOR structures. As experimental structural determination of these membrane receptors is challenging, a complementary approach, template-based modelling (TBM) can generate model structures. TBM selects templates based on sequence identity, but the iOR family is highly divergent. As the four recent experimental iOR structures are from two evolutionarily distant organisms, a different template selection approach is needed, such as Bio-GATS ( Bio-GATS uses hydrophobicity correspondence to select templates for 7TM G-protein coupled receptors (GPCRs), although iORs have an inverted topology compared to GPCRs.

Aim: To create a workflow for building high-quality structural models of insect ORs, based on the Bio-GATS approach, followed by validation and application. Methodology: I have modified Python-based Bio-GATS to use iOR structures, with inverted topology (iBio-GATS) and then developed a workflow by integrating iBio-GATS and Modeller 10.4, for TBM; through shell scripting, to rapidly generate high-quality insect OR models. Users can run the workflow completely automated or select a single desired template.

Results: An easy-to-use workflow that generates high-quality models for iORs has been successfully validated on experimental iOR structures (AbOrco and MhOR5) and applied to the fruitfly DmOR59b with mutagenesis data. Unlike AlphaFold models for DmOR59b and its mutant, the models built using this workflow were able to recover the mutagenesis site in the ligand binding pocket for DmOR59b.

Significance and future directions: This current generic workflow will facilitate more rapid analysis in obtaining high-quality structural models for insect odorant receptors. The workflow can be converted to a fully automated workflow by integrating AlignME into it and can also be updated by adding more templates upon their availability in the future.


Table of Contents

1 Introduction -- 2 Methods -- 3 Workflow development and validation -- 4 Capturing DmOR59b mutagenesis data using iBio-GATS -- 5 Summary and future directions -- 6 References -- 7 Appendices

Awarding Institution

Macquarie University

Degree Type

Thesis MRes


Master of Research

Department, Centre or School

Department of Applied BioSciences

Year of Award


Principal Supervisor

Shoba Ranganathan

Additional Supervisor 1

Phillip Taylor


Copyright: The Author Copyright disclaimer:




80 pages

Former Identifiers

AMIS ID: 282997