Proton Transfer in Aqueous Solution: Exploring the Boundaries of Adaptive QM/MM

Jiang, Tao; Boereboom, Jelle M.; Michel, Carine; Fleurat‐Lessard, Paul; Bulo, Rosa E.

doi:10.1007/978-3-319-21626-3_2

Cited by 19 publications

(26 citation statements)

References 63 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These extra forces artificially drive solvent molecules into or out of the QM (or MM) zone and are deemed nonphysical . If these extra forces are not negligible, they will cause artifacts, e.g., erroneous solvation structures …”

Section: Smoothing the Qm–mm Transitionmentioning

confidence: 99%

“…(Note that a partitioning configuration is also called a partition by some researchers.) 48 The second approach is to interpolate the forces acting on the atoms in a similar manner:…”

Section: Energy Interpolation and Force Interpolationmentioning

confidence: 99%

“…53,56 If these extra forces are not negligible, they will cause artifacts, e.g., erroneous solvation structures. 48,52 The force-based schemes do not conserve energy in NVE simulations, as the forces do not correspond to the gradients of the energy. For example, in the modified-AP schemes by Pezeshki et al, 53 the forces are computed by:…”

Section: Interpolate the Energy Or Forces?mentioning

confidence: 99%

“…An algorithm that offers this flexibility is called adaptive QM/MM . Such flexibility leads to two distinct advantages: First, the on‐the‐fly reclassification of atoms as QM or MM makes adaptive methodology uniquely suited to perform QM/MM simulations of diffusive systems.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Adaptive quantum/molecular mechanics: what have we learned, where are we, and where do we go from here?

Duster

Wang

Garza

et al. 2017

WIREs Comput Mol Sci

108

View full text Add to dashboard Cite

Adaptive quantum‐mechanics/molecular‐mechanics (QM/MM) methods feature on‐the‐fly reclassification of atoms as QM or MM during a molecular dynamics (MD) simulation, allowing the location and contents of the QM subsystem to be dynamically updated as needed. Such flexibility is a distinct advantage over conventional QM/MM, where a ‘static’ boundary is retained between the QM and MM subsystems. The ‘dynamic’ boundary in adaptive QM/MM allows a finite‐size QM to sustain simulations with an arbitrary length of time. To ensure smooth transitions between QM and MM, the energy or forces are interpolated. Special treatments are applied so that artifacts are eliminated or minimized. Recent developments have shed light on the relationship between the adaptive algorithms that describe Hamiltonian and non‐Hamiltonian systems. Originally developed to model an ion solvated in bulk solvent, adaptive QM/MM has been enhanced in many aspects, including the treatment of molecular fragments in macromolecules, monitoring molecules entering/leaving binding sites, and tracking proton transfer via the Grotthuss mechanism. Because the size of the QM region can be set as small as possible in adaptive QM/MM, the computational costs can be kept low. Small QM subsystems also facilitate the utilization of high‐level QM theory and long simulation time, which can potentially lead to new insights. WIREs Comput Mol Sci 2017, 7:e1310. doi: 10.1002/wcms.1310 This article is categorized under: Electronic Structure Theory > Combined QM/MM Methods Molecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods Software > Molecular Modeling

show abstract

Section: Smoothing the Qm–mm Transitionmentioning

confidence: 99%

“…(Note that a partitioning configuration is also called a partition by some researchers.) 48 The second approach is to interpolate the forces acting on the atoms in a similar manner:…”

Section: Energy Interpolation and Force Interpolationmentioning

confidence: 99%

Section: Interpolate the Energy Or Forces?mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive quantum/molecular mechanics: what have we learned, where are we, and where do we go from here?

Duster

Wang

Garza

et al. 2017

WIREs Comput Mol Sci

108

View full text Add to dashboard Cite

show abstract

“…Unsurprisingly, approaches that repartition the system on the fly to address this issue have been developed for the past 20 years and are generally referred to as adaptive QM/MM methods. A number of reviews on adaptive QM/MM methods have already been published . Our review aims to provide a comprehensive description of the entire process of adaptive QM/MM modeling.…”

Section: Introductionmentioning

confidence: 99%

Adaptive quantum mechanics/molecular mechanics methods

Zheng

Waller

2016

WIREs Comput Mol Sci

View full text Add to dashboard Cite

Multiscale methods have enjoyed a well-celebrated place in the computational chemists' toolbox, while the next generation of so-called adaptive quantum mechanics/molecular mechanics (QM/MM) methods were being developed on the fringe for the past 20 years. Adaptive QM/MM methods hold the promise of extending the range of applicability, currently at the expense of complexity and computational scaling. There are a number of challenges in the area; firstly, the ability to partition a system on the fly has led to the distance, number, density, and stress-based approaches. Secondly, methods that smoothen the transition from a QM to an MM region using a single configuration include Hot-Spot, ONIOM-XS, and time-adaptive. Alternatively, more computationally expensive methods that smoothen the transition region based on multiple configurations are the permuted and sorted adaptive permutation, difference-based adaptive, and size-consistent multipartitioning methods. There exist three alternative methods that avoid issues of smoothening altogether; they are the so-called buffered force, ABRUPT, and the flexible inner restraint methods. In this advanced review, an overview on the available methods, a number of applications, and the remaining challenges are discussed.

show abstract

Yoink: An interaction‐based partitioning API

Zheng

Waller

2018

J Comput Chem

View full text Add to dashboard Cite

Herein, we describe the implementation details of our interaction-based partitioning API (application programming interface) called Yoink for QM/MM modeling and fragment-based quantum chemistry studies. Interactions are detected by computing density descriptors such as reduced density gradient, density overlap regions indicator, and single exponential decay detector. Only molecules having an interaction with a user-definable QM core are added to the QM region of a hybrid QM/MM calculation. Moreover, a set of molecule pairs having density-based interactions within a molecular system can be computed in Yoink, and an interaction graph can then be constructed. Standard graph clustering methods can then be applied to construct fragments for further quantum chemical calculations. The Yoink API is licensed under Apache 2.0 and can be accessed via yoink.wallerlab.org. © 2018 Wiley Periodicals, Inc.

show abstract

Proton Transfer in Aqueous Solution: Exploring the Boundaries of Adaptive QM/MM

Cited by 19 publications

References 63 publications

Adaptive quantum/molecular mechanics: what have we learned, where are we, and where do we go from here?

Adaptive quantum/molecular mechanics: what have we learned, where are we, and where do we go from here?

Adaptive quantum mechanics/molecular mechanics methods

Yoink: An interaction‐based partitioning API

Contact Info

Product

Resources

About