Accurate and Transferable Reactive Molecular Dynamics Models from Constrained Density Functional Theory

24 August 2021, Version 2
This content is a preprint and has not undergone peer review at the time of posting.


Chemical reactions constitute the central feature of many liquid, material, and biomolecular processes. Conventional molecular dynamics (MD) is inadequate for simulating chemical reactions given the fixed bonding topology of most force fields, while modeling chemical reactions using ab initio molecular dynamics is limited to shorter time and length scales given its high computational cost. As such, the multiscale reactive molecular dynamics method provides one promising alternative for simulating complex chemical systems at atomistic detail on a reactive potential energy surface. However, the parameterization of such models is a key barrier to their applicability and success. In this work, we present reactive MD models derived from constrained density functional theory that are both accurate and transferable. We illustrate the features of these models for proton dissociation reactions of amino acids in both aqueous and protein environments. Specifically, we present models for ionizable glutamate and lysine that predict accurate absolute pKa values in water, as well as their significantly shifted pKa in staphylococcal nuclease (SNase) without any modification of the models. As one outcome of the new methodology, the simulations show that the deprotonation of ionizable residues in SNase can be closely coupled with sidechain rotations, which is a concept likely generalizable to many other proteins. Furthermore, the present approach is not limited to only pKa prediction, but can enable the fully atomistic simulation of many other reactive systems along with a determination of the key aspects of the reaction mechanisms.


molecular dynamics
staphylococcal nuclease
Density Functional Theory
Proton Transfer
pKa Calculation
Free Energy Sampling

Supplementary materials

Supplementary Information
Supporting information contains an additional table of the optimized MS-RMD model parameters using BLYP CDFT data, figures illustrating the reactive coordinate definitions in SNase, and showing the statistical errors in PMFs of SNase.


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