Quantifying the Structural and Energetic Consequences of EXOSC3 S1 Domain Variants from a Comparative Assessment of λ-Dynamics with Two Charge-Changing Perturbation Strategies

Abstract

Charge-changing perturbations are notoriously difficult to investigate with alchemical free energy calculations. The routine use of periodic boundary conditions and electrostatic approximations, such as particle-mesh Ewald (PME), may produce finite-size effect errors that become non-negligible as a perturbation changes a simulation cell’s net charge away from zero. Two prevalent strategies exist to correct for these errors: the analytic correction (AC) and co-alchemical ion (CI) methods. Both correction schemes have been found to produce comparable relative free energy results for small molecule perturbations, but these methods have not been compared using λ-dynamics (λD) free energy calculations or for protein side chain mutations. Recently, we investigated relative folding and binding free energies (Δ⁢Δ⁢𝐺⁡s) of a series of EXOSC3 variants involved in a rare neurodegenerative disorder, including D132A, G135R, and G191D charge-change perturbations, with a simplified AC scheme in λD. In this study, these perturbations are reevaluated with the CI scheme for comparison with AC to identify the best correction strategy for λD. The collected AC- and CI-corrected Δ⁢Δ⁢𝐺⁡s show excellent agreement with a mean unsigned error of 0.4 kcal/mol. However, reduced sampling proficiency and increased difficulties of evaluating multisite perturbations with the CI method suggest that a simplified AC approach may be more generalizable for future λD calculations. Previously, the use of the CI approach with λD has been limited due to a lack of infrastructure available to users to simplify its more involved setup procedure. This study introduces an automated workflow for implementation of the CI approach with λD, laying the foundation for future comparisons between charge-change correction schemes. These studies facilitated analysis of the λD trajectories to identify structural changes within EXOSC3 and the RNA exosome complex that clearly rationalize the calculated Δ⁢Δ⁢𝐺⁡s for the D132A, G135R, G191C, and G191D EXOSC3 variants, providing insight into potential disease-causing mechanisms of EXOSC3 modifications.