Extending scaled-interaction adaptive-partitioning QM/MM to covalently bonded systems

Reshaping the QM Region On-the-Fly: Adaptive-Shape QM/MM Dynamic Simulations of a Hydrated Proton in Bulk Water

Adaptive quantum mechanics/molecular mechanics (QM/MM) reclassifies on-the-fly a molecule or molecular fragment as QM or MM during dynamics simulations without abrupt changes in the energy or forces. Notably, the permuted adaptive-partitioning (PAP) algorithms have been applied to simulate a hydrated proton, with a mobile QM zone anchored at a pseudoatom called a proton indicator. The position of the proton indicator approximates the location of the delocalized excess proton, yielding a smooth trajectory of the proton diffusing via the Grotthuss mechanism in aqueous solutions. The mobile QM zone, which has been taken to be a sphere with a preset radius, follows the proton wherever it goes. Although the simulations are successful, the use of a spherical QM zone has one disadvantage: A large preset radius must be utilized to minimize the chance of missing water molecules that are important to proton translocation. A large radius leads to a large QM zone, which is computationally expensive. In this work, we report a new way to set up the QM zone, where one includes only the water molecules important to proton transfer. The importance of a given water molecule is quantified by its "weight" that depends on its relation to the reaction path of proton transfer. The weight varies smoothly, ensuring that a water molecule gradually appears in or disappears from the QM zone without abrupt changes, as required by the PAP method. Consequently, the shape of the QM zone evolves on-the-fly, keeping the QM zone as small as possible and as large as necessary. Test simulations demonstrate that the new algorithm significantly improves the computation efficiency while maintaining the proper descriptions of proton transfer in bulk water.

DP/MM: A Hybrid Model for Zinc-Protein Interactions in Molecular Dynamics

Zinc-containing proteins are vital for many biological processes, yet accurately modeling them using classical force fields is hindered by complicated polarization and charge transfer effects. This study introduces DP/MM, a hybrid force field scheme that utilizes a deep potential model to correct the atomic forces of zinc ions and their coordinated atoms, elevating them from MM to QM levels of accuracy. Trained on the difference between MM and QM atomic forces across diverse zinc coordination groups, the DP/MM model faithfully reproduces structural characteristics of zinc coordination during simulations, such as the tetrahedral coordination of Cys4 and Cys3His1 groups. Furthermore, DP/MM allows water exchange in the zinc coordination environment. With its unique blend of accuracy, efficiency, flexibility, and transferability, DP/MM serves as a valuable tool for studying structures and dynamics of zinc-containing proteins and also represents a pioneering approach in the evolving landscape of machine learning potentials for molecular modeling.

Adaptive-Partitioning Multilayer Dynamics Simulations: 2. Implementations of the Permuted and Interpolated Adaptive-Partitioning Gradients

Recently, an adaptive-partitioning multilayer Q1/Q2/MM method was proposed, where Q1 and Q2 denote, respectively, two distinct quantum-mechanical levels of theory and MM, the molecular-mechanical force fields. Such a multilayer model resembles the ONIOM (our own N-layered integrated molecular orbital and molecular mechanics) model by Morokuma and co-workers, but it is distinguished by on-the-fly reclassifying atoms to be Q1, Q2, or MM in dynamics simulations. To smoothly blend the levels of descriptions of the atoms, buffer zones are introduced between adjacent layers, and the energy is smoothly interpolated. In particular, the Q1/Q2 interaction energy was expressed in two different formalisms: permuted and interpolated adaptive-partitioning (PAP and IAP), respectively. While the PAP energy is based on a weighted many-body expansion, the IAP energy is derived via alchemical quantum calculations with interpolated Fock and overlap matrices. In this article, we examine in-depth the irregularities in the IAP energy near the boundary between the buffer and Q2 zones, which were found prominent in some calculations. These irregularities are due to basis-set linear dependencies, which can be effectively suppressed using a cutoff for the weighted atomic orbital coefficients. Furthermore, we derived and implemented the gradients for both PAP and IAP. Test calculations on a series of water cluster models show perfectly smooth gradients in PAP, while a minor discontinuity occurs in IAP gradients at the buffer/Q2 boundary. The energy and gradient discontinuities in IAP become smaller when moving the buffer/Q2 boundary further away from the Q1 center and when increasing the size of the basis sets used. Overall, those discontinuities are controllable, and possible ways to further diminish them are discussed.

The application of QM/MM simulations in heterogeneous catalysis

The QM/MM simulation method is provenly efficient for the simulation of biological systems, where an interplay of extensive environment and delicate local interactions drives a process of interest through a funnel on a complex energy landscape. Recent advances in quantum chemistry and force-field methods present opportunities for the adoption of QM/MM to simulate heterogeneous catalytic processes, and their related systems, where similar intricacies exist on the energy landscape. Herein, the fundamental theoretical considerations for performing QM/MM simulations, and the practical considerations for setting up QM/MM simulations of catalytic systems, are introduced; then, areas of heterogeneous catalysis are explored where QM/MM methods have been most fruitfully applied. The discussion includes simulations performed for adsorption processes in solvent at metallic interfaces, reaction mechanisms within zeolitic systems, nanoparticles, and defect chemistry within ionic solids. We conclude with a perspective on the current state of the field and areas where future opportunities for development and application exist.

Tracking the Delocalized Proton in Concerted Proton Transfer in Bulk Water

A solvated proton in water is often characterized as a charge or structural defect, and it is important to track its evolution on-the-fly in certain dynamics simulations. Previously, we introduced the proton indicator, a pseudo-atom, whose position approximates the location of the excess proton modeled as a structural defect. The proton indicator generally yields a smooth trajectory of a hydrated proton diffusing in aqueous solutions, including in the events of stepwise proton transfer via the Grotthuss mechanism; however, the proton indicator did not perform well in the events of concerted proton transfer, for which it occasionally yielded large position displacements between two successive time steps. To overcome this hurdle, we develop a new algorithm of a proton indicator with greatly enhanced performance for concerted proton transfer in bulk water. A protocol is proposed to exhaustively explore the hydrogen-bonding network of the water wires over which the excess proton is delocalized and to properly account for the contributions of the water molecules in this network as the geometry evolves. The new proton indicator (called Indicator 2.0) is assessed in dynamics simulations of an excess proton in bulk water and in specially constructed model systems of more complex architectures. The results demonstrate that the new indicator yields a smooth trajectory in both stepwise and concerted proton transfers.

Speed-dependent adaptive partitioning in QM/MM MD simulations of displacement damage in solid-state systems

Solids undergo displacement damage (DD) when interacting with energetic particles, which may happen during the fabrication of semiconductor devices, in harsh environments and in certain analysis techniques. Simulations of DD generation are usually carried out using classical molecular dynamics (MD), but classical MD does not account for all the effects in DD, as demonstrated by ab initio calculations of model systems in the literature. A complete ab initio simulation of DD generation is impractical due to the large number of atoms involved. In my previous paper [Yang, Phys. Chem. Chem. Phys., 2020, 22, 19307], I developed an adaptive-center (AC) method for the adaptive-partitioning (AP) of quantum mechanics/molecular mechanics (QM/MM) simulations, allowing the active region centers and the QM/MM partition to be determined on-the-fly for energy-conserving AP-QM/MM methods. I demonstrated that the AC-AP-QM/MM is applicable to the simulation of DD generation, so that the active regions can be treated using an ab initio method. The AC method could not be used to identify the fast-moving recoil ions in DD generation as active region centers, however, and the accuracy is negatively affected by the rapid change in the QM/MM partition of the system. In this paper, I extend the AC method and develop a speed-dependent adaptive-center (SDAC) method for accurate AP-QM/MM simulations of DD. The SDAC method is applicable to general problems with speed-dependent active regions, and is compatible with all existing energy-conserving partitioning-by-distance AP-QM/MM methods. The artifact due to the speed-dependent potential energy surface can be made small by choosing suitable criteria. I demonstrate the SDAC method by simulations of DD generation in bulk silicon.

On-the-fly determination of active region centers in adaptive-partitioning QM/MM

Quantum mechanics/molecular mechanics (QM/MM) methods are widely used in molecular dynamics (MD) simulations of large systems. By partitioning the system into active and environmental regions and treating them with different levels of theory, QM/MM methods achieve accuracy and efficiency at the same time. Adaptive-partitioning (AP) QM/MM allows the partition of the system to change during the MD simulation, making it possible to simulate processes in which the active and environmental regions exchange atoms or molecules, such as processes in solutions or solids. AP-QM/MM methods usually partition the system according to distances to centers of active regions. For energy-conserving AP-QM/MM methods, these centers are chosen beforehand and remain fixed during the MD simulation, making it difficult to simulate processes in which active regions may occur or vanish. In this paper, I develop an adaptive-center (AC) method that allows on-the-fly determination of the centers of active regions according to any geometrical criterion or any criterion dependent on the potential energy. The AC method is compatible with all existing energy-conserving AP-QM/MM methods, and the resulting potential energy surface is smooth. The application of the AC method is demonstrated with two examples in solid systems.