Alchemical Metadynamics: Adding Alchemical Variables to Metadynamics to Enhance Sampling in Free Energy Calculations.

Performing alchemical transformations, in which one molecular system is nonphysically changed to another system, is a popular approach adopted in performing free energy calculations associated with various biophysical processes, such as protein-ligand binding or the transfer of a molecule between environments. While the sampling of alchemical intermediate states in either parallel (e.g., Hamiltonian replica exchange) or serial manner (e.g., expanded ensemble) can bridge the high-probability regions in the configurational space between two end states of interest, alchemical methods can fail in scenarios where the most important slow degrees of freedom in the configurational space are, in large part, orthogonal to the alchemical variable, or if the system gets trapped in a deep basin extending in both the configurational and alchemical space. To alleviate these issues, we propose to use alchemical variables as an additional dimension in metadynamics, making it possible to both sample collective variables and to enhance sampling in free energy calculations simultaneously. In this study, we validate our implementation of "alchemical metadynamics" in PLUMED with test systems and alchemical processes with varying complexities and dimensionalities of collective variable space, including the interconversion between the torsional metastable states of a toy system and the methylation of a nucleoside both in the isolated form and in a duplex. We show that multidimensional alchemical metadynamics can address the challenges mentioned above and further accelerate sampling by introducing configurational collective variables. The method can trivially be combined with other metadynamics-based algorithms implemented in PLUMED. The necessary PLUMED code changes have already been released for general use in PLUMED 2.8.

physical_validation: A Python package to assess the physical validity of molecular simulation results.

Molecular simulations such as molecular dynamics (MD) and Monte Carlo (MC) simulations are powerful tools allowing the prediction of experimental observables in the study of systems such as proteins, membranes, and polymeric materials. The quality of predictions based on molecular simulations depend on the validity of the underlying physical assumptions. physical_validation allows users of molecular simulation programs to perform simple yet powerful tests of physical validity on their systems and setups. It can also be used by molecular simulation package developers to run representative test systems during development, increasing code correctness. The theoretical foundation of the physical validation tests were established by Merz & Shirts (2018), in which the physical_validation package was first mentioned.

Testing for physical validity in molecular simulations.

Advances in recent years have made molecular dynamics (MD) and Monte Carlo (MC) simulations powerful tools in molecular-level research, allowing the prediction of experimental observables in the study of systems such as proteins, membranes, and polymeric materials. However, the quality of any prediction based on molecular dynamics results will strongly depend on the validity of underlying physical assumptions. Unphysical behavior of simulations can have significant influence on the results and reproducibility of these simulations, such as folding of proteins and DNA or properties of lipid bilayers determined by cutoff treatment, dynamics of peptides and polymers affected by the choice of thermostat, or liquid properties depending on the simulation time step. Motivated by such examples, we propose a two-fold approach to increase the robustness of molecular simulations. The first part of this approach involves tests which can be performed by the users of MD programs on their respective systems and setups. We present a number of tests of different complexity, ranging from simple post-processing analysis to more involved tests requiring additional simulations. These tests are shown to significantly increase the reliability of MD simulations by catching a number of common simulation errors violating physical assumptions, such as non-conservative integrators, deviations from the Boltzmann ensemble, and lack of ergodicity between degrees of freedom. To make the usage as easy as possible, we have developed an open-source and platform-independent Python library (https://physical-validation.readthedocs.io) implementing these tests. The second part of the approach involves testing for code correctness. While unphysical behavior can be due to poor or incompatible choices of parameters by the user, it can just as well originate in coding errors within the program. We therefore propose to include physical validation tests in the code-checking mechanism of MD software packages. We have implemented such a validation for the GROMACS software package, ensuring that every major release passes a number of physical sanity checks performed on selected representative systems before shipping. It is, to our knowledge, the first major molecular mechanics software package to run such validation routinely. The tests are, as the rest of the package, open source software, and can be adapted for other software packages.

A GROMOS-Compatible Force Field for Small Organic Molecules in the Condensed Phase: The 2016H66 Parameter Set.

This article reports on the calibration and validation of a new GROMOS-compatible parameter set 2016H66 for small organic molecules in the condensed phase. The calibration is based on 62 organic molecules spanning the chemical functions alcohol, ether, aldehyde, ketone, carboxylic acid, ester, amine, amide, thiol, sulfide, and disulfide, as well as aromatic compounds and nucleic-acid bases. For 57 organic compounds, the calibration targets are the experimental pure-liquid density ρliq and the vaporization enthalpy ΔHvap, as well as the hydration free energy ΔGwat and the solvation free energy ΔGche in cyclohexane, at atmospheric pressure and at (or close to) room temperature. The final root-mean-square deviations (RMSD) for these four quantities over the set of compounds are 32.4 kg m(-3), 3.5 kJ mol(-1), 4.1 kJ mol(-1), and 2.1 kJ mol(-1), respectively, and the corresponding average deviations (AVED) are 1.0 kg m(-3), 0.2 kJ mol(-1), 2.6 kJ mol(-1), and 1.0 kJ mol(-1), respectively. For the five nucleic-acid bases, the parametrization is performed by transferring the final 2016H66 parameters from analogous organic compounds followed by a slight readjustment of the charges to reproduce the experimental water-to-chloroform transfer free energies ΔGtrn. The final RMSD for this quantity over the five bases is 1.7 kJ mol(-1), and the corresponding AVED is 0.8 kJ mol(-1). As an initial validation of the 2016H66 set, seven additional thermodynamic, transport, and dielectric properties are calculated for the 57 organic compounds in the liquid phase. The agreement with experiment in terms of these additional properties is found to be reasonable, with significant deviations typically affecting either a specific chemical function or a specific molecule. This suggests that in most cases, a classical force-field description along with a careful parametrization against ρliq, ΔHvap, ΔGwat, and ΔGche results in a model that appropriately describes the liquid in terms of a wide spectrum of its physical properties.