Target Flexibility in RNA-Ligand Docking Modeled by Elastic Potential Grids

Area of Science:

• Biochemistry
• Computational Biology
• Drug Discovery

Background:

• The inherent flexibility of RNA poses significant challenges for structure-based drug design.
• Accurate modeling of RNA conformational changes is crucial for effective RNA-targeted therapeutics.

Purpose of the Study:

• To develop and validate a computational approach for modeling RNA conformational changes during RNA-ligand docking.
• To enhance the accuracy and efficiency of RNA-ligand docking simulations.

Main Methods:

• Utilized potential grids represented as elastic bodies governed by Navier's equation to model RNA flexibility.
• Applied the approach to a dataset of 17 RNA-ligand complexes.

Main Results:

• The elastic body approach accurately describes RNA-ligand interactions, accommodating RNA movements up to 6 Å root-mean-square deviation (rmsd).
• Achieved twice the success rate of docking into apo structures and half the success rate of redocking to holo structures.
• Demonstrated applicability across different RNA-ligand complex classes due to robust parametrization.

Conclusions:

• The developed method offers an accurate and efficient way to model RNA flexibility in docking.
• This approach significantly improves RNA-ligand docking performance compared to static models.
• Facilitates structure-based drug design targeting flexible RNA molecules.