Drug Repurposing on G Protein-Coupled Receptors Using a Computational Profiling Approach

Area of Science:

• Pharmacology
• Computational Biology
• Drug Discovery

Background:

• G protein-coupled receptors (GPCRs) are crucial drug targets, involved in diverse cell signaling pathways.
• Approximately 40% of marketed drugs target GPCRs, highlighting their therapeutic importance.
• Understanding drug cross-activity across GPCRs is key for rationalizing side effects and improving drug design.

Purpose of the Study:

• To introduce an in silico approach, Computational Profiling for GPCRs (CPG), for predicting ligand-GPCR interactions.
• To demonstrate CPG's capability in repurposing existing drugs for different GPCR targets.
• To provide a user-friendly tool for assisting in the rational design of GPCR-targeting drugs.

Main Methods:

• Development of CPG, an in silico method representing ligand-GPCR binding properties in a 1D string.
• Utilizing a tailored alignment algorithm within CPG to predict drug repurposing.
• Validation through docking calculations and pharmacological data for specific GPCRs.

Main Results:

• CPG successfully predicted drug repurposing for three case studies involving specific GPCRs.
• Docking and pharmacological data confirmed the computational predictions.
• The CPG approach effectively represents physico-chemical properties of ligand-GPCR interactions.

Conclusions:

• CPG is a powerful tool for identifying potential off-label uses of existing drugs.
• The method aids in designing more selective and less toxic drug candidates for GPCRs.
• CPG's graphical user interface facilitates its application in drug discovery and development.