Leveraging a Separation of States Method for Relative Binding Free Energy Calculations in Systems with Trapped Waters.

Methods for calculating the relative binding free energy (RBFE) between ligands to a target protein are gaining importance in the structure-based drug discovery domain, especially as methodological advances and automation improve accuracy and ease of use. In an RBFE calculation, the difference between the binding affinities of two ligands to a protein is calculated by transforming one ligand into another, in the protein-ligand complex, and in solvent. Alchemical binding free energy calculations are often used for such ligand transformations.

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.

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.

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.

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.