Browsing by Author "Xiong, Yeyue"
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- Developing Fast and Accurate Water Models for Atomistic Molecular Dynamics SimulationsXiong, Yeyue (Virginia Tech, 2021-09-15)Water models are of great importance for different fields of studies such as fluid mechanics, nano materials, and biomolecule simulations. In this dissertation, we focus on the water models applied in atomistic simulations, including those of biomolecules such as proteins and DNA. Despite water's simple structure and countless studies carried out over the decades, the best water models are still far from perfect. Water models are normally divided into two types--explicit model and implicit model. Here my research is mainly focused on explicit models. In explicit water models, fixed charge n-point models are most widely used in atomistic simulations, but have known accuracy drawbacks. Increasing the number of point charges, as well as adding electronic polarizability, are two common strategies for accuracy improvements. Both strategies come at considerable computational cost, which weighs heavily against modest possible accuracy improvements in practical simulations. With a careful comparison between the two strategies, results show that adding polarizability is a more favorable path to take. Optimal point charge approximation (OPCA) method is then applied along with a novel global optimization process, leading to a new polarizable water model OPC3-pol that can reproduce bulk liquid properties of water accurately and run at a speed comparable to 3- and 4-point non-polarizable water models. For practical use, OPC3-pol works with existing non-polarizable AMBER force fields for simulations of globular protein or DNA. In addition, for intrinsically disordered protein simulations, OPC3-pol fixes the over-compactness problem of the previous generation non-polarizable water models.
- Exploring optimization strategies for improving explicit water models: Rigid n-point model and polarizable model based on Drude oscillatorXiong, Yeyue; Onufriev, Alexey V. (PLOS, 2019-11-14)Rigid n-point water models are widely used in atomistic simulations, but have known accuracy drawbacks. Increasing the number of point charges, as well as adding electronic polarizability, are two common strategies for accuracy improvements. Both strategies come at considerable computational cost, which weighs heavily against modest possible accuracy improvements in practical simulations. In an effort to provide guidance for model development, here we have explored the limiting accuracy of “electrostatically globally optimal” npoint water models in terms of their ability to reproduce properties of water dimer—a mimic of the condensed state of water. For a given n, each model is built upon a set of reference multipole moments (e.g. ab initio) and then optimized to reproduce water dimer total dipole moment. The models are then evaluated with respect to the accuracy of reproducing the geometry of the water dimer. We find that global optimization of the charge distribution alone can deliver high accuracy of the water model: for n = 4 or n = 5, the geometry of the resulting water dimer can be almost within 50 of the ab initio reference, which is half that of the experimental error margin. Thus, global optimization of the charge distribution of classical n-point water models can lead to high accuracy models. We also find that while the accuracy improvement in going from n = 3 to n = 4 is substantial, the additional accuracy increase in going from n = 4 to n = 5 is marginal. Next, we have explored accuracy limitations of the standard practice of adding electronic polarizability (via a Drude particle) to a “rigid base”—pre-optimization rigid n-point water model. The resulting model (n = 3) shows a relatively small improvement in accuracy, suggesting that the strategy of merely adding the polarizability to an inferior accuracy water model used as the base cannot fix the defects of the latter. An alternative strategy in which the parameters of the rigid base model are globally optimized along with the polarizability parameter is much more promising: the resulting 3-point polarizable model out-performs even the 5-point optimal rigid model by a large margin. We suggest that future development efforts consider 3- and 4-point polarizable models where global optimization of the “rigid base” is coupled to optimization of the polarizability to deliver globally optimal solutions.