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.