Modeling RNA-ligand interactions: the Rev-binding element RNA-aminoglycoside complex

Area of Science:

• Computational chemistry
• Structural biology
• Drug discovery

Background:

• Modeling ligand-RNA interactions is crucial for understanding biological processes and developing therapeutics.
• Accurate prediction of ligand-bound RNA conformations remains a challenge.

Purpose of the Study:

• To develop and validate a computational approach for modeling ligand-RNA complexes.
• To assess the ability of 3D-SAR to predict bound ligand conformations.
• To identify and optimize the structure of ligand-RNA complexes.

Main Methods:

• Combined three-dimensional structure-activity relationship (3D-SAR) computations with a docking protocol.
• Validated the 3D-SAR approach using phenyloxazoline-HRV14 RNA complexes.
• Applied 3D-SAR and docking to model aminoglycoside-RBE RNA complexes.
• Utilized molecular dynamics for complex optimization.

Main Results:

• The 3D-SAR method successfully predicted known bound conformations of phenyloxazolines.
• The approach identified bioactive conformations of aminoglycosides bound to RBE RNA.
• Docking and molecular dynamics refined the ligand-RNA complex structures.

Conclusions:

• The integrated 3D-SAR and docking methodology is effective for predicting bound ligand conformations.
• This approach provides a valid framework for modeling ligand-RNA complex structures.
• The validated method can aid in the rational design of RNA-targeting drugs.