The Need for Continuing Blinded Pose- and Activity Prediction Benchmarks.

Area of Science:

• Computational chemistry
• Drug discovery
• cheminformatics

Background:

• Structure-based drug design (SBDD) is vital for efficient drug discovery.
• Current SBDD methodologies, especially for binding pose and activity predictions (P-AP), face significant limitations in reliability.
• A lack of standardized community benchmarking hinders progress.

Purpose of the Study:

• To review the current state of P-AP in SBDD.
• To highlight the need for a community-driven benchmarking process.
• To propose a path forward for improving P-AP method development.

Main Methods:

• Overview of P-AP methodologies.
• Analysis of unblinded benchmarking datasets.
• Review of concluded and ongoing blinded benchmarking initiatives.

Main Results:

• Identified limitations in current P-AP prediction reliability.
• Highlighted the absence of a standardized, independent benchmarking process.
• Provided insights from past and present benchmarking efforts.

Conclusions:

• A community-supported, long-term benchmark challenge is essential for accelerating breakthroughs in P-AP methods.
• Such a challenge requires nonbiased datasets and systematic, independent validation.
• Establishing a forum for scientific discussion is critical for community engagement and progress.