A Comparison of QM/MM Simulations with and without the Drude Oscillator Model Based on Hydration Free Energies of Simple Solutes

Abstract

Maintaining a proper balance between specific intermolecular interactions and non-specific solvent interactions is of critical importance in molecular simulations, especially when predicting binding affinities or reaction rates in the condensed phase. The most rigorous metric for characterizing solvent affinity are solvation free energies, which correspond to a transfer from the gas phase into solution. Due to the drastic change of the electrostatic environment during this process, it is also a stringent test of polarization response in the model. Here, we employ both the CHARMM fixed charge and polarizable force fields to predict hydration free energies of twelve simple solutes. The resulting classical ensembles are then reweighted to obtain QM/MM hydration free energies using a variety of QM methods, including MP2, Hartree–Fock, density functional methods (BLYP, B3LYP, M06-2X) and semi-empirical methods (OM2 and AM1 ). Our simulations test the compatibility of quantum-mechanical methods with molecular-mechanical water models and solute Lennard–Jones parameters. In all cases, the resulting QM/MM hydration free energies were inferior to purely classical results, with the QM/MM Drude force field predictions being only marginally better than the QM/MM fixed charge results. In addition, the QM/MM results for different quantum methods are highly divergent, with almost inverted trends for polarizable and fixed charge water models. While this does not necessarily imply deficiencies in the QM models themselves, it underscores the need to develop consistent and balanced QM/MM interactions. Both the QM and the MM component of a QM/MM simulation have to match, in order to avoid artifacts due to biased solute–solvent interactions. Finally, we discuss strategies to improve the convergence and efficiency of multi-scale free energy simulations by automatically adapting the molecular-mechanics force field to the target quantum method.

How accurate are approximate quantum chemical methods at modelling solute–solvent interactions in solvated clusters?

“…32 Similarly, York and co-workers have also reported hydration free energies determined using DFT/MM methods were generally inferior to classical force field simulations. 33 This raises the question of whether the use of more robust DFT/MM potentials can indeed better describe solute-solvent interactions than classical force fields, and whether explicit solvent models can be systematically improved.…”

“…These end-state corrections may be obtained from FEP calculations using MM and QM solute-solvent interaction energies determined on clusters containing a sufficient number of solvent molecules to mimic bulk solvent effects. Such a "reference potential" type approach [33][34][35][36][37][38][39][40][41] represents a cost-effective alternative to "one-pot" ab initio MD simulations, which treat both the intra-and intermolecular degrees of freedom at the same level of theory (usually DFT) and are exceedingly expensive. While our recent work demonstrated the effectiveness of this approach in the treatment of an SN2 reaction in water, there are several issues concerning the broader applicability of this procedure.…”

Alchemical Hydration Free Energy Calculations Using Molecular Dynamics with Explicit Polarization and Induced Polarity Decoupling: An On-the-Fly Approach

“…[37][38][39][40] It is also often the case that this use of QM/MM makes the estimated free energy of hydration worse than using the MM approach alone. 41 The method has recently been applied to hydration free energy simulations of organic molecules and, in conjunction with the IPolQ-Mod partial charge method, yielded results similar to standard RESP and AM1-BCC free energies with GAFF on small test sets. 35,42 IPolQ is a recently developed method that calculates the electron density distribution of the solute based on measurements taken during explicit water simulation, 43 and then employs it to calculate polarized restrained electrostatic potential (RESP).…”

On the faithfulness of molecular mechanics representations of proteins towards quantum-mechanical energy surfaces

“…In a second step, we ask the question which MM force field among AMBER [47,48], CHARMM [42,49], GROMOS [50,51] and OPLS [52] more closely reproduces all QM energy minima occurring in 14 neutral amino acids according to the refined YMPJ conformer database [53,54]. Blocked serine is used as an example to discuss possible improvements by the CHARMM polarizable force field [55–57], or using tailored force fields based on QM optimizations [58]. In the following, we first discuss the methodological details, followed by presenting the results and our conclusions.…”