Best Practices in Mixed-Solvent Molecular Dynamics and Solvent-Site-Biased Docking.

Area of Science:

• Computational chemistry
• Structural biology
• Drug discovery

Background:

• Mixed-solvent molecular dynamics (MixMD) and solvent-biased docking (SSBD) are powerful computational techniques.
• These methods have been applied across multiple implementations and studies over the past decade.
• A need exists for standardized best practices to facilitate broader adoption.

Purpose of the Study:

• To provide practical recommendations for setting up, analyzing, and integrating MixMD and SSBD workflows.
• To focus on using MixMD as a foundation for deriving solvent sites that inform docking and pharmacophore strategies.
• To synthesize computational studies into a unified framework for structure-based drug design.

Main Methods:

• Leveraging over a decade of experience in MixMD and SSBD applications.
• Focusing on the derivation of solvent sites from mixed-solvent simulations.
• Integrating solvent occupancy patterns into pharmacophore features and docking constraints.

Main Results:

• Mixed-solvent simulations and solvent-biased docking offer a validated strategy for identifying protein binding hot spots.
• Solvent patterns can be translated into structurally interpretable pharmacophoric features.
• The proposed framework standardizes best practices for these computational methods.

Conclusions:

• Standardizing best practices will facilitate wider adoption of MixMD and SSBD in structure-based drug design.
• These methods enable more reliable identification of functional sites on proteins.
• The unified methodological framework accelerates rational ligand discovery.