Tackling Halogenated Species with PBSA: Effect of Emulating the sigma-Hole

摘要

To model halogen-bond phenomena using classical force fields, an extra point (EP) of charge is frequently introduced at a given distance from the halogen (X) to emulate the sigma-hole. The resulting molecular dynamics (MD) trajectories can be used in subsequent molecular mechanics (MM) combined with Poisson Boltzmann and surface area calculations (PBSA) to estimate protein ligand binding free energies (Delta G(bind)). While EP addition improves the MM/MD description of halogen-containing systems, its effect on the calculation of solvation free energies (Delta G(solv)) using the PBSA approach is yet to be assessed. As the PBSA calculations depend, among other parameters, on the empirical assignment of radii (PB radii), a problematic issue arises, since standard halogen radii are smaller than the typical X center dot center dot center dot EP distances, thus placing the EP within the solvent dielectric. Herein, we took a common literature EP parametrization scheme, which uses X center dot center dot center dot EP = R-min and RESP charges in the context of GAFF, and performed a comprehensive study on the performance of PBSA (using three different setups) in the calculation of Delta G(solv) values for 142 halogenated compounds (bearing Cl, Br, or I) for which the experimental values are known. By conducting an optimization (minimizing the error against experimental values), we provide a new optimized set of halogen PB radii, for each PBSA setup, that should be used in the context of the aforementioned scenario. A simultaneous optimization of PB radii and X center dot center dot center dot EP distances shows that a wide range of distance/radius pairs can be used without significant loss of accuracy, therefore laying the basis for expanding this halogen radii optimization strategy to other force fields and EP implementations. As ligand Delta G(solv) estimation is an important term in the determination of protein-ligand Delta G(bind), this work is particularly relevant in the framework of structure-based virtual screening and related computer-aided drug design routines.