Solving the OH + Glyoxal Problem: A Complete Theoretical Description of Post-Transition-State Energy Deposition in Activated Systems

Activated chemistry in coupled reaction systems has broadened our understanding of the chemical kinetics. In the case of intermediates formed in gas phase abstraction reactions (e.g., OH + HC(O)C(O)H (glyoxal) →HC(O)CO + H2O), it is particularly crucial to understand how the reaction energy is partitioned between product species as this determines the propensity for a given product to undergo "prompt" dissociation (e.g., HC(O)CO → HCO + CO) before the excess reaction energy is removed. An example of such an activated system is the OH + glyoxal + O2 coupled reaction system. In this work, we develop a molecular dynamics pipeline, which, combined with a master equation analysis, accurately models previous experimental measurements. This new work resolves previous complexities and discrepancies from earlier master equation modeling for this reaction system. The detailed molecular dynamics approach employed here is a powerful new tool for modeling challenging activated reaction systems.

A Reactive Molecular Dynamics Study of Chlorinated Organic Compounds. Part II: A ChemTraYzer Study of Chlorinated Dibenzofuran Formation and Decomposition Processes

In our two-paper series, we first present the development of ReaxFF CHOCl parameters using the recently published ParAMS parametrization tool. In this second part, we update the reactive Molecular Dynamics - Quantum Mechanics coupling scheme ChemTraYzer and combine it with our new ReaxFF parameters from Part I to study formation and decomposition processes of chlorinated dibenzofurans. We introduce a self-learning method for recovering failed transition-state searches that improves the overall ChemTraYzer transition-state search success rate by 10 percentage points to a total of 48 %. With ChemTraYzer, we automatically find and quantify more than 500 reactions using transition state theory and DFT. Among the discovered chlorinated dibenzofuran reactions are numerous reactions that are new to the literature. In three case studies, we discuss the set of reactions that are most relevant to the dibenzofuran literature: (i) bimolecular reactions of the chlorinated-dibenzofuran precursors phenoxy radical and 1,3,5-trichlorobenzene, (ii) dibenzofuran chlorination and pyrolysis, and (iii) oxidation of chlorinated dibenzofurans.

Efficient Reaction Space Exploration with ChemTraYzer-TAD

The development of a reaction model is often a time-consuming process, especially if unknown reactions have to be found and quantified. To alleviate the reaction modeling process, automated procedures for reaction space exploration are highly desired. We present ChemTraYzer-TAD, a new reactive molecular dynamics acceleration technique aimed at efficient reaction space exploration. The new method is based on the basin confinement strategy known from the temperature-accelerated dynamics (TAD) acceleration method. Our method features integrated ChemTraYzer bond-order processing steps for the automatic and on-the-fly determination of the positions of virtual walls in configuration space that confine the system in a potential energy basin. We use the example of 1,3-dioxolane-4-hydroperoxide-2-yl radical oxidation to show that ChemTraYzer-TAD finds more than 100 different parallel reactions for the given set of reactants in less than 2 ns of simulation time. Among the many observed reactions, ChemTraYzer-TAD finds the expected typical low-temperature reactions despite the use of extremely high simulation temperatures up to 5000 K. Our method also finds a new concerted β-scission plus O₂ addition with a lower reaction barrier than the literature-known and so-far dominant β-scission.

AutoMeKin2021: An open-source program for automated reaction discovery

AutoMeKin2021 is an updated version of tsscds2018, a program for the automated discovery of reaction mechanisms (J. Comput. Chem. 2018, 39, 1922). This release features a number of new capabilities: rare-event molecular dynamics simulations to enhance reaction discovery, extension of the original search algorithm to study van der Waals complexes, use of chemical knowledge, a new search algorithm based on bond-order time series analysis, statistics of the chemical reaction networks, a web application to submit jobs, and other features. The source code, manual, installation instructions and the website link are available at: https://rxnkin.usc.es/index.php/AutoMeKin.

ChemDyME: Kinetically Steered, Automated Mechanism Generation through Combined Molecular Dynamics and Master Equation Calculations

In many scientific fields, there is an interest in understanding the way in which chemical networks evolve. The chemical networks which researchers focus upon have become increasingly complex, and this has motivated the development of automated methods for exploring chemical reactivity or conformational change in a "black-box" manner, harnessing modern computing resources to automate mechanism discovery. In this work, we present a new approach to automated mechanism generation which couples molecular dynamics and statistical rate theory to automatically find kinetically important reactions and then solve the time evolution of the species in the evolving network. The key to this chemical network mapping through combined dynamics and ME simulation approach is the concept of "kinetic convergence", whereby the search for new reactions is constrained to those species which are kinetically favorable at the conditions of interest. We demonstrate the capability of the new approach for two systems, a well-studied combustion system and a multiple oxygen addition system relevant to atmospheric aerosol formation.

Application of Reaction Path Search Calculations to Potential Energy Surface Fits

There has been significant progress in recent years in the use of machine learning techniques to model high-dimensional reactive potential energy surfaces using large-scale data obtained from ab initio electronic structure calculations. In these methods, the strategy used to gather data becomes a key issue as the molecular size increases. In this work, we examine the applicability of the reaction path search algorithm implemented in the Global Reaction Route Mapping (GRRM) code as a data-gathering approach. The electronic energies and gradients sampled by using the GRRM calculation are directly used in potential energy surface fitting to a permutationally invariant polynomial function. This simple approach was applied to the HNS and HCNO reaction systems, and we found that the fitted potential energy surfaces reasonably reproduce the features of the electronic structure calculations used in the GRRM calculations. This suggests that the GRRM sampling scheme can be used to construct an initial potential energy surface.

Insights into the interactions of bisphenol and phthalate compounds with unamended and carnitine-amended montmorillonite clays

Montmorillonite clays could be promising sorbents to mitigate toxic compound exposures. Bisphenols A (BPA) and S (BPS) as well as phthalates, dibutyl phthalate (DBP) and di-2-ethylhexyl phthalate (DEHP), are ubiquitous environmental contaminants linked to adverse health effects. Here, we combined computational and experimental methods to investigate the ability of montmorillonite clays to sorb these compounds. Molecular dynamics simulations predicted that parent, unamended, clay has higher binding propensity for BPA and BPS than for DBP and DEHP; carnitine-amended clay improved BPA and BPS binding, through carnitine simultaneously anchoring to the clay through its quaternary ammonium cation and forming hydrogen bonds with BPA and BPS. Experimental isothermal analysis confirmed that carnitine-amended clay has enhanced BPA binding capacity, affinity and enthalpy. Our studies demonstrate how computational and experimental methods, combined, can characterize clay binding and sorption of toxic compounds, paving the way for future investigation of clays to reduce BPA and BPS exposure.

Interactive molecular dynamics in virtual reality for accurate flexible protein-ligand docking

Simulating drug binding and unbinding is a challenge, as the rugged energy landscapes that separate bound and unbound states require extensive sampling that consumes significant computational resources. Here, we describe the use of interactive molecular dynamics in virtual reality (iMD-VR) as an accurate low-cost strategy for flexible protein-ligand docking. We outline an experimental protocol which enables expert iMD-VR users to guide ligands into and out of the binding pockets of trypsin, neuraminidase, and HIV-1 protease, and recreate their respective crystallographic protein-ligand binding poses within 5-10 minutes. Following a brief training phase, our studies shown that iMD-VR novices were able to generate unbinding and rebinding pathways on similar timescales as iMD-VR experts, with the majority able to recover binding poses within 2.15 Å RMSD of the crystallographic binding pose. These results indicate that iMD-VR affords sufficient control for users to carry out the detailed atomic manipulations required to dock flexible ligands into dynamic enzyme active sites and recover crystallographic poses, offering an interesting new approach for simulating drug docking and generating binding hypotheses.

Low dimensional representations along intrinsic reaction coordinates and molecular dynamics trajectories using interatomic distance matrices

Most chemical transformations (reactions or conformational changes) that are of interest to researchers have many degrees of freedom, usually too many to visualize without reducing the dimensionality of the system to include only the most important atomic motions. In this article, we describe a method of using Principal Component Analysis (PCA) for analyzing a series of molecular geometries (e.g., a reaction pathway or molecular dynamics trajectory) and determining the reduced dimensional space that captures the most structural variance in the fewest dimensions. The software written to carry out this method is called PathReducer, which permits (1) visualizing the geometries in a reduced dimensional space, (2) determining the axes that make up the reduced dimensional space, and (3) projecting the series of geometries into the low-dimensional space for visualization. We investigated two options to represent molecular structures within PathReducer: aligned Cartesian coordinates and matrices of interatomic distances. We found that interatomic distance matrices better captured non-linear motions in a smaller number of dimensions. To demonstrate the utility of PathReducer, we have carried out a number of applications where we have projected molecular dynamics trajectories into a reduced dimensional space defined by an intrinsic reaction coordinate. The visualizations provided by this analysis show that dynamic paths can differ greatly from the minimum energy pathway on a potential energy surface. Viewing intrinsic reaction coordinates and trajectories in this way provides a quick way to gather qualitative information about the pathways trajectories take relative to a minimum energy path. Given that the outputs from PCA are linear combinations of the input molecular structure coordinates (i.e., Cartesian coordinates or interatomic distances), they can be easily transferred to other types of calculations that require the definition of a reduced dimensional space (e.g., biased molecular dynamics simulations).

Interactive molecular dynamics in virtual reality from quantum chemistry to drug binding: An open-source multi-person framework

As molecular scientists have made progress in their ability to engineer nanoscale molecular structure, we face new challenges in our ability to engineer molecular dynamics (MD) and flexibility. Dynamics at the molecular scale differs from the familiar mechanics of everyday objects because it involves a complicated, highly correlated, and three-dimensional many-body dynamical choreography which is often nonintuitive even for highly trained researchers. We recently described how interactive molecular dynamics in virtual reality (iMD-VR) can help to meet this challenge, enabling researchers to manipulate real-time MD simulations of flexible structures in 3D. In this article, we outline various efforts to extend immersive technologies to the molecular sciences, and we introduce "Narupa," a flexible, open-source, multiperson iMD-VR software framework which enables groups of researchers to simultaneously cohabit real-time simulation environments to interactively visualize and manipulate the dynamics of molecular structures with atomic-level precision. We outline several application domains where iMD-VR is facilitating research, communication, and creative approaches within the molecular sciences, including training machines to learn potential energy functions, biomolecular conformational sampling, protein-ligand binding, reaction discovery using "on-the-fly" quantum chemistry, and transport dynamics in materials. We touch on iMD-VR's various cognitive and perceptual affordances and outline how these provide research insight for molecular systems. By synergistically combining human spatial reasoning and design insight with computational automation, technologies such as iMD-VR have the potential to improve our ability to understand, engineer, and communicate microscopic dynamical behavior, offering the potential to usher in a new paradigm for engineering molecules and nano-architectures.

Alkyl hydrogen atom abstraction reactions of the CN radical with ethanol

We present a study of the abstraction of alkyl hydrogen atoms from the β and α positions of ethanol by the CN radical in solution using the Empirical Valence Bond (EVB) method. We have built separate 2 × 2 EVB models for the H_β and H_α reactions, where the atom transfer is parameterized using ab initio calculations. The intra- and intermolecular potentials of the reactant and product molecules were modelled with the General AMBER Force Field, with some modifications. We have carried out the dynamics in water and chloroform, which are solvents of contrasting polarity. We have computed the potential of mean force for both abstractions in each of the solvents. They are found to have a small and early barrier along the reaction coordinate with a large energy release. Analyzing the solvent structure around the reaction system, we have found two solvents to have little effect on either reaction. Simulating the dynamics from the transition state, we also study the fate of the energies in the HCN vibrational modes. The HCN molecule is born vibrationally hot in the CH stretch in both reactions and additionally in the HCN bends for the H_α abstraction reaction. In the early stage of the dynamics, we find that the CN stretch mode gains energy at the expense of the energy in CH stretch mode.

A Blind Test of Computational Technique for Predicting the Likelihood of Peptide Sequences to Cyclize

An in silico computational technique for predicting peptide sequences that can be cyclized by cyanobactin macrocyclases, e.g., PatG_mac, is reported. We demonstrate that the propensity for PatG_mac-mediated cyclization correlates strongly with the free energy of the so-called pre-cyclization conformation (PCC), which is a fold where the cyclizing sequence C and N termini are in close proximity. This conclusion is driven by comparison of the predictions of boxed molecular dynamics (BXD) with experimental data, which have achieved an accuracy of 84%. A true blind test rather than training of the model is reported here as the in silico tool was developed before any experimental data was given, and no parameters of computations were adjusted to fit the data. The success of the blind test provides fundamental understanding of the molecular mechanism of cyclization by cyanobactin macrocyclases, suggesting that formation of PCC is the rate-determining step. PCC formation might also play a part in other processes of cyclic peptides production and on the practical side the suggested tool might become useful for finding cyclizable peptide sequences in general.

Reaction and relaxation at surface hotspots: using molecular dynamics and the energy-grained master equation to describe diamond etching

The extent to which vibrational energy transfer dynamics can impact reaction outcomes beyond the gas phase remains an active research question. Molecular dynamics (MD) simulations are the method of choice for investigating such questions; however, they can be extremely expensive, and therefore it is worth developing cheaper models that are capable of furnishing reasonable results. This paper has two primary aims. First, we investigate the competition between energy relaxation and reaction at 'hotspots' that form on the surface of diamond during the chemical vapour deposition process. To explore this, we developed an efficient reactive potential energy surface by fitting an empirical valence bond model to higher-level ab initio electronic structure theory. We then ran 160 000 NVE trajectories on a large slab of diamond, and the results are in reasonable agreement with experiment: they suggest that energy dissipation from surface hotspots is complete within a few hundred femtoseconds, but that a small fraction of CH₃ does in fact undergo dissociation prior to the onset of thermal equilibrium. Second, we developed and tested a general procedure to formulate and solve the energy-grained master equation (EGME) for surface chemistry problems. The procedure we outline splits the diamond slab into system and bath components, and then evaluates microcanonical transition-state theory rate coefficients in the configuration space of the system atoms. Energy transfer from the system to the bath is estimated using linear response theory from a single long MD trajectory, and used to parametrize an energy transfer function which can be input into the EGME. Despite the number of approximations involved, the surface EGME results are in reasonable agreement with the NVE MD simulations, but considerably cheaper. The results are encouraging, because they offer a computationally tractable strategy for investigating non-equilibrium reaction dynamics at surfaces for a broader range of systems.This article is part of the themed issue 'Theoretical and computational studies of non-equilibrium and non-statistical dynamics in the gas phase, in the condensed phase and at interfaces'.