Application of Molecular Dynamics Simulations in Molecular Property Prediction. 1. Density and Heat of Vaporization

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Abstract
Molecular mechanical force field (FF) methods are useful in studying condensed phase properties. They are complementary to experiments and can often go beyond experiments in atomic details. Even if a FF is specific for studying structures, dynamics, and functions of biomolecules, it is still important for the FF to accurately reproduce the experimental liquid properties of small molecules that represent the chemical moieties of biomolecules. Otherwise, the force field may not describe the structures and energies of macromolecules in aqueous solutions properly. In this work, we have carried out a systematic study to evaluate the General AMBER Force Field (GAFF) in studying densities and heats of vaporization for a large set of organic molecules that covers the most common chemical functional groups. The latest techniques, such as the particle mesh Ewald (PME) for calculating electrostatic energies and Langevin dynamics for scaling temperatures, have been applied in the molecular dynamics (MD) simulations. For density, the average percent error (APE) of 71 organic compounds is 4.43% when compared to the experimental values. More encouragingly, the APE drops to 3.43% after the exclusion of two outliers and four other compounds for which the experimental densities have been measured with pressures higher than 1.0 atm. For the heat of vaporization, several protocols have been investigated, and the best one, P4/ntt0, achieves an average unsigned error (AUE) and a root-mean-square error (RMSE) of 0.93 and 1.20 kcal/mol, respectively. How to reduce the prediction errors through proper van der Waals (vdW) parametrization has been discussed. An encouraging finding in vdW parametrization is that both densities and heats of vaporization approach their “ideal” values in a synchronous fashion when vdW parameters are tuned. The following hydration free energy calculation using thermodynamic integration further justifies the vdW refinement. We conclude that simple vdW parametrization can significantly reduce the prediction errors. We believe that GAFF can greatly improve its performance in predicting liquid properties of organic molecules after a systematic vdW parametrization, which will be reported in a separate paper.