Path-Based Nonequilibrium Binding Free Energy Estimation, from Protein-Ligand to RNA-Ligand Binding.

In this study, we addressed the challenge of estimating binding free energies in complex biological systems of pharmaceutical relevance, including both protein-ligand and RNA-ligand complexes. As case studies, we examined the intricate binding of the drug Gleevec to Abl-tyrosine kinase and two ligands binding to the preQ1 RNA riboswitch. By refining our approach based on nonequilibrium steered molecular dynamics simulations and path-based collective variables, we tackled the specific difficulties posed by these systems. In particular, the Abl-Gleevec complex is characterized by significant system size and extensive conformational rearrangements of the protein, whereas the systems involving RNA are characterized by marked conformational flexibility. For the Abl-Gleevec system, our method produced binding free energy estimates closely aligned with experimental values, demonstrating its reliability. For the RNA-ligand complexes investigated, we found that the simpler water model TIP3P yields more accurate free energy estimates than the TIP4P-D model, offering practical insight for future research. In this case, the agreement with the experimental results is reasonable. Overall, this work underscores the effectiveness of the proposed path-based workflow in handling complex biomolecular systems with unique characteristics, enabling systematic binding free energy predictions across a variety of targets.