Enabling In-Silico Hit Discovery Workflows Targeting RNA with Small Molecules.

Area of Science:

• Computational chemistry and structural biology.
• Drug discovery and medicinal chemistry.
• Molecular modeling and simulation.

Background:

• Ribonucleic acid (RNA) receptors are crucial targets in drug discovery.
• Accurate prediction of binding sites and ligand poses is essential for structure-based drug design.
• Existing computational methods require further refinement for RNA targets.

Purpose of the Study:

• To improve the performance of SiteMap and Glide for predicting RNA binding sites and ligand poses.
• To extend absolute binding free energy perturbation methods to RNA receptors.
• To validate computational predictions against experimental binding affinities.

Main Methods:

• Utilized and enhanced SiteMap and Glide algorithms for RNA receptor analysis.
• Applied absolute binding free energy perturbation calculations for RNA systems.
• Compared computational predictions with experimental binding affinity data.

Main Results:

• Achieved state-of-the-art or superior accuracy in predicting RNA binding sites and ligand poses.
• Demonstrated strong correlation between calculated and experimental binding affinities for RNA targets.
• Successfully adapted free energy perturbation methods for RNA receptor studies.

Conclusions:

• The enhanced computational methods provide reliable predictions for RNA-ligand interactions.
• These advancements facilitate structure-based drug discovery targeting RNA.
• The study offers a validated computational framework for RNA-focused drug development.