Recovering Small Molecule Ligand-RNA Binding Pocket Binding Modes and Exploring Potential Binding Pathways Using Metadynamics.

Understanding how an RNA recognizes small molecule ligands is crucial for pharmaceutical research. Molecular dynamics (MD) simulations can potentially reveal this process in atomistic detail. However, simulations frequently fail should energy barriers along the pathway prove to be insurmountably high on the simulation timescale (ns-µs). To address this limitation, we present a novel strategy combining well-tempered metadynamics utilizing X-ray crystallography or NMR-solved hydrogen-bonding interactions between an RNA and its ligand as collective variables (CVs). This approach can sample multiple transitions during the binding process and determine the most favorable binding modes through the reconstructed free energy landscape. Our computational recovery of binding modes for all five cases studied is in good agreement (RMSD below 2.0 Å) with the experimentally determined structures of the bound complexes. Our study demonstrates that metadynamics coupled with strategically chosen collective variables can effectively sample binding pathways and recover binding modes for RNA-small molecule complexes. This method therefore could be valuable for crystal structure interpretation, NMR solution structure refinement, and computer-aided design of RNA-targeted small molecule drugs.