Structure Prediction, Evaluation, and Validation of GPR18 Lipid Receptor Using Free Programs

Area of Science:

• Structural biology and computational chemistry
• GPCR research and drug discovery

Background:

• The GPR18 receptor (N-arachidonylglycine receptor) is a class A GPCR orphan with emerging therapeutic potential in immune, neurodegenerative, and cancer processes.
• Understanding GPR18 ligand interactions and the role of structural elements is crucial for drug development, yet its structure remains experimentally unsolved.

Purpose of the Study:

• To generate a reliable homology model of the GPR18 receptor in its inactive state.
• To evaluate the utility of free and academic computational chemistry software for molecular modeling and docking studies.
• To assess the model's ability to recognize known active ligands and predict binding poses.

Main Methods:

• Utilized and compared various contemporary protein structure prediction methods and software to build the GPR18 homology model.
• Employed molecular dynamics simulations to assess the stability of predicted ligand-receptor poses.
• Focused on using only license-free/academic software and online platforms for all computational chemistry experiments.

Main Results:

• Successfully generated a homology model of the GPR18 receptor suitable for further studies.
• Validated the model's ability to recognize known active ligands.
• Demonstrated that meaningful molecular modeling and docking studies can be performed with high scientific confidence using freely available tools.

Conclusions:

• Freely available computational chemistry software and academic licenses are sufficient for conducting high-quality GPR18 molecular modeling and docking.
• The developed GPR18 model serves as a valuable tool for investigating ligand interactions and guiding the discovery of novel therapeutics.
• This study validates the feasibility of cost-effective computational approaches in modern drug discovery research.