Quantitative predictions from molecular simulations using explicit or implicit interactions

Abstract

Equilibrium simulations of molecular systems allow to extract many physicochemical properties. Given an "accurate enough" model, a "large enough" simulation system and "long enough" simulations, such calculations should yield accurate predictions of properties that can be tested by experimental measurements. Non-equilibrium simulations can be used as a tool to obtain specific properties like viscosity or conductivity, but they have the drawback that in general only one property per simulation is produced. In addition, a range of methods is available for computing free energy differences. We here review the state of the art of using classical simulation models for generating quantitative predictions. Popular force fields have significant predictive power already but there is room for improvement. Bonded force potentials may need to be replaced by more accurate ones to better reproduce vibrational frequencies. Simplification of non-bonded force terms, such as cut-offs for electrostatic or dispersion interactions, should be avoided. Routine usage of force field methods will therefore require some tuning of parameters. Despite the extensive toolbox that is available for producing quantitative results, the computational cost of explicit solvent simulation is significant and therefore, approximate methods like implicit solvent models remain popular and are still being developed. Based on fundamental arguments as well as on examples of solvation free energies, host-guest complexation and non-covalent association of molecules in solution, we conclude that implicit solvents as well as algorithmic simplifications are most useful when validation using experimental data or rigorous theoretical treatments is possible.

Simulations of Amyloid-Forming Peptides in the Crystal State

“…It has been demonstrated in many studies that explicit long range interactions are crucial for accurate simulations [ 28 – 30 ]. In combination with efficient and flexible simulation codes [ 31 ], molecular simulations can be used to extract relevant physicochemical properties [ 32 , 33 ] that can be compared to experimental data [ 34 – 37 ]. In this manner, classical force fields underlying the simulations can be benchmarked against the usually very accurate macroscopic properties that are available in handbooks [ 38 – 40 ].…”

An Ensemble Structure and Physicochemical (SPOC) Descriptor for Machine‐Learning Prediction of Chemical Reaction and Molecular Properties

“…Free energy of hydration describes the energy change of molecular transfer process from gas to water, that are critical factors in many physicochemical or biophysical processes [21,32] . Many efforts have been made to obtain more precise values, either by experiments or calculations [21,33] . The newest version of hydration free energy database (FreeSolv) includes curated experimental and calculated hydration free energies for 642 small neutral molecules in water.…”

Computational Insights into Cyclodextrin Inclusion Complexes with the Organophosphorus Flame Retardant DOPO

“…∆E MM can be further decomposed into bonded (∆E bonded ) and nonbonded (∆E nonbonded ) contributions, and ∆E nonbonded is a sum of van der Waals (∆E vdW ) and electrostatic (∆E elec ) interactions (Equation ( 2)) [75,76,78].…”