GPCR-Bench: A Benchmarking Set and Practitioners' Guide for G Protein-Coupled Receptor Docking

Area of Science:

• Computational chemistry
• Drug discovery
• Structural biology

Background:

• Virtual screening is crucial for identifying novel ligands and chemotypes for G protein-coupled receptors (GPCRs).
• Tailoring docking protocols is essential for effective virtual screening.
• Existing benchmarking sets are often evaluated retrospectively, not by their prospective hit potential.

Purpose of the Study:

• To introduce GPCR-Bench, a public docking benchmarking dataset for GPCRs.
• To provide a resource for validating and comparing molecular docking protocols.
• To guide the evaluation of docking methods based on their ability to yield prospective hits.

Main Methods:

• Creation of GPCR-Bench, a dataset comprising 25 nonredundant high-resolution GPCR co-structures.
• Inclusion of diverse ligands and computational decoys for each GPCR target.
• Development of a case study to highlight considerations for evaluating docking methods.

Main Results:

• GPCR-Bench provides a standardized resource for docking protocol validation.
• The dataset facilitates the assessment of docking methods' ability to identify novel prospective hits.
• The study emphasizes the need for objective, machine-scriptable functions for evaluating docking performance.

Conclusions:

• GPCR-Bench aids in the development of more effective virtual screening strategies for GPCR targets.
• Objective evaluation of docking protocols is critical for advancing drug discovery.
• The presented case study offers practical guidance for researchers in the field.