1
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Meissner JA, Meisner J. Acceleration of Diffusion in Ab Initio Nanoreactor Molecular Dynamics and Application to Hydrogen Sulfide Oxidation. J Chem Theory Comput 2024. [PMID: 39440718 DOI: 10.1021/acs.jctc.4c00826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2024]
Abstract
The computational description of chemical reactivity can become extremely complex when multiple different reaction products and intermediates come into play, forming a chemical reaction network. Therefore, computational methods for the automated construction of chemical reaction networks have been developed in the last decades. One of these methods, ab initio nanoreactor molecular dynamics (NMD), is based on external forces enhancing reactivity by e.g., periodically compressing the system and allowing it to relax. However, during the relaxation process, a significant simulation time is required to allow energy to dissipate and molecules to diffuse, making this part of the NMD simulation computationally intensive. This work aims to improve NMD by accelerating the diffusion process in the relaxation phase. We systematically investigate the speedup of reaction discovery gained by diffusion acceleration, leading to a factor of up to 28 in discovery frequency. Diffusion-accelerated nanoreactor molecular dynamics (DA-NMD) is then used to construct a reaction network of hydrogen sulfide oxidation under atmospheric conditions, where reactions are automatically detected by a change in the bond order and bond distance. A reaction network of 108 molecular species and 399 elementary reactions was constructed starting from hydrogen sulfide, hydroxy radicals, and molecular oxygen covering a broad variety of sulfur-oxygen chemistry and oxidation states of the sulfur atom ranging from -II to +VI.
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Affiliation(s)
- Jan A Meissner
- Institute of Physical Chemistry, Heinrich Heine University Düsseldorf, Dusseldorf 40225, Germany
| | - Jan Meisner
- Institute of Physical Chemistry, Heinrich Heine University Düsseldorf, Dusseldorf 40225, Germany
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2
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Stuyver T. TS-tools: Rapid and automated localization of transition states based on a textual reaction SMILES input. J Comput Chem 2024; 45:2308-2317. [PMID: 38850166 DOI: 10.1002/jcc.27374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 03/08/2024] [Accepted: 03/20/2024] [Indexed: 06/10/2024]
Abstract
Here, TS-tools is presented, a Python package facilitating the automated localization of transition states (TS) based on a textual reaction SMILES input. TS searches can either be performed at xTB or DFT level of theory, with the former yielding guesses at marginal computational cost, and the latter directly yielding accurate structures at greater expense. On a benchmarking dataset of mono- and bimolecular reactions, TS-tools reaches an excellent success rate of 95% already at xTB level of theory. For tri- and multimolecular reaction pathways - which are typically not benchmarked when developing new automated TS search approaches, yet are relevant for various types of reactivity, cf. solvent- and autocatalysis and enzymatic reactivity - TS-tools retains its ability to identify TS geometries, though a DFT treatment becomes essential in many cases. Throughout the presented applications, a particular emphasis is placed on solvation-induced mechanistic changes, another issue that received limited attention in the automated TS search literature so far.
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Affiliation(s)
- Thijs Stuyver
- Ecole Nationale Supérieure de Chimie de Paris, Université PSL, CNRS, Institute of Chemistry for Life and Health Sciences, Paris, France
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3
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Spiekermann KA, Dong X, Menon A, Green WH, Pfeifle M, Sandfort F, Welz O, Bergeler M. Accurately Predicting Barrier Heights for Radical Reactions in Solution Using Deep Graph Networks. J Phys Chem A 2024; 128:8384-8403. [PMID: 39298746 DOI: 10.1021/acs.jpca.4c04121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/22/2024]
Abstract
Quantitative estimates of reaction barriers and solvent effects are essential for developing kinetic mechanisms and predicting reaction outcomes. Here, we create a new data set of 5,600 unique elementary radical reactions calculated using the M06-2X/def2-QZVP//B3LYP-D3(BJ)/def2-TZVP level of theory. A conformer search is done for each species using TPSS/def2-TZVP. Gibbs free energies of activation and of reaction for these radical reactions in 40 common solvents are obtained using COSMO-RS for solvation effects. These balanced reactions involve the elements H, C, N, O, and S, contain up to 19 heavy atoms, and have atom-mapped SMILES. All transition states are verified by an intrinsic reaction coordinate calculation. We next train a deep graph network to directly estimate the Gibbs free energy of activation and of reaction in both gas and solution phases using only the atom-mapped SMILES of the reactant and product and the SMILES of the solvent. This simple input representation avoids computationally expensive optimizations for the reactant, transition state, and product structures during inference, making our model well-suited for high-throughput predictive chemistry and quickly providing information for (retro-)synthesis planning tools. To properly measure model performance, we report results on both interpolative and extrapolative data splits and also compare to several baseline models. During training and testing, the data set is augmented by including the reverse direction of each reaction and variants with different resonance structures. After data augmentation, we have around 2 million entries to train the model, which achieves a testing set mean absolute error of 1.16 kcal mol-1 for the Gibbs free energy of activation in solution. We anticipate this model will accelerate predictions for high-throughput screening to quickly identify relevant reactions in solution, and our data set will serve as a benchmark for future studies.
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Affiliation(s)
- Kevin A Spiekermann
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Xiaorui Dong
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Angiras Menon
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - William H Green
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Mark Pfeifle
- BASF Digital Solutions GmbH, Ludwigshafen am Rhein 67061, Germany
| | - Frederik Sandfort
- BASF SE, Scientific Modeling, Group Research, Ludwigshafen am Rhein 67056, Germany
| | - Oliver Welz
- BASF SE, Scientific Modeling, Group Research, Ludwigshafen am Rhein 67056, Germany
| | - Maike Bergeler
- BASF SE, Scientific Modeling, Group Research, Ludwigshafen am Rhein 67056, Germany
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4
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Algera RF, Tcyrulnikov S, Reyes GP. Mechanism-Based Regiocontrol in S NAr: A Case Study of Ortho-Selective Etherification with Chloromagnesium Alkoxides. J Am Chem Soc 2024. [PMID: 39358201 DOI: 10.1021/jacs.4c07427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2024]
Abstract
Although nucleophilic aromatic substitution (SNAr) is routinely employed as a practical alternative to transition-metal-catalyzed cross-coupling, the mechanistic basis for reactivity and regioselectivity remains underexplored and is an active area of research. This article reports a SNAr-based etherification of 2,4-difluoroarylcarboxamides as a model system and shows that the ortho/para regioselectivity spans >500:1 to 1:∼20 simply by varying the reaction conditions via high-throughput experimentation (HTE). An in-depth characterization of the ortho-selective lead conditions is presented, and these insights are used to build a reactivity model that self-consistently accounts for the regioselectivity and reaction scope. This article discusses synthetic implications of condition-dependent magnesium coordination and Schlenk equilibria and demonstrates that consideration of molecular-level stoichiometry and isomerism is an essential prerequisite for rationalizing reactivity and regioselectivity in SNAr.
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Affiliation(s)
- Russell F Algera
- Pfizer Chemical Research and Development, Pfizer, Inc., Groton, Connecticut 06340, United States
| | - Sergei Tcyrulnikov
- Pfizer Chemical Research and Development, Pfizer, Inc., Groton, Connecticut 06340, United States
| | - Giselle P Reyes
- Pfizer Chemical Research and Development, Pfizer, Inc., Groton, Connecticut 06340, United States
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5
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Jung J, An H, Lee J, Han S. Modified Activation-Relaxation Technique (ARTn) Method Tuned for Efficient Identification of Transition States in Surface Reactions. J Chem Theory Comput 2024. [PMID: 39240127 DOI: 10.1021/acs.jctc.4c00767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/07/2024]
Abstract
Exploring potential energy surfaces (PES) is essential for unraveling the underlying mechanisms of chemical reactions and material properties. While the activation-relaxation technique (ARTn) is a state-of-the-art method for identifying saddle points on PES, it often faces challenges in complex energy landscapes, especially on surfaces. In this study, we introduce iso-ARTn, an enhanced ARTn method that incorporates constraints on an orthogonal hyperplane and employs an adaptive active volume. By leveraging a neural network potential (NNP) to conduct an exhaustive saddle point search on the Pt(111) surface with 0.3 monolayers of surface oxygen coverage, iso-ARTn achieves a success rate that is 8.2% higher than the original ARTn, with 40% fewer force calls. Moreover, this method effectively finds various saddle points without compromising the success rate. Combined with kinetic Monte Carlo simulations for event table construction, iso-ARTn with NNP demonstrates the capability to reveal structures consistent with experimental observations. This work signifies a substantial advancement in the investigation of PES, enhancing both the efficiency and breadth of saddle point searches.
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Affiliation(s)
- Jisu Jung
- Department of Material Science and Engineering, Seoul National University, Seoul 08826, Korea
| | - Hyungmin An
- Department of Material Science and Engineering, Seoul National University, Seoul 08826, Korea
| | - Jinhee Lee
- Fuel Cell Center, Hyundai Motor Company, Yongin 16891, Korea
| | - Seungwu Han
- Department of Material Science and Engineering, Seoul National University, Seoul 08826, Korea
- Korea Institute for Advanced Study, Seoul 02455, Korea
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6
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Koda SI, Saito S. Flat-Bottom Elastic Network Model for Generating Improved Plausible Reaction Paths. J Chem Theory Comput 2024. [PMID: 39150850 DOI: 10.1021/acs.jctc.4c00792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/18/2024]
Abstract
Rapid generation of a plausible reaction path connecting a given reactant and product in advance is crucial for the efficient computation of precise reaction paths or transition states. We propose a computationally efficient potential energy based on the molecular structure to generate such paths. This potential energy has a flat bottom consisting of structures without atomic collisions while preserving nonreactive chemical bonds, bond angles, and partial planar structures. By combining this potential energy with the direct MaxFlux method, a recently developed reaction-path/transition-state search method, we can find the shortest plausible path passing within the bottom. Numerical results show that this combination yields lower energy paths compared to the paths obtained by the well-known image-dependent pair potential. We also theoretically investigate the differences between these two potential energies. The proposed potential energy and path generation routine are implemented in our Python version of the direct MaxFlux method, available on GitHub.
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Affiliation(s)
- Shin-Ichi Koda
- Department of Theoretical and Computational Molecular Science, Institute for Molecular Science, Myodaiji, Okazaki, Aichi 444-8585, Japan
- School of Physical Sciences, The Graduate University for Advanced Studies, Myodaiji, Okazaki, Aichi 444-8585, Japan
| | - Shinji Saito
- Department of Theoretical and Computational Molecular Science, Institute for Molecular Science, Myodaiji, Okazaki, Aichi 444-8585, Japan
- School of Physical Sciences, The Graduate University for Advanced Studies, Myodaiji, Okazaki, Aichi 444-8585, Japan
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7
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van Gerwen P, Briling KR, Calvino Alonso Y, Franke M, Corminboeuf C. Benchmarking machine-readable vectors of chemical reactions on computed activation barriers. DIGITAL DISCOVERY 2024; 3:932-943. [PMID: 38756222 PMCID: PMC11094696 DOI: 10.1039/d3dd00175j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 02/28/2024] [Indexed: 05/18/2024]
Abstract
In recent years, there has been a surge of interest in predicting computed activation barriers, to enable the acceleration of the automated exploration of reaction networks. Consequently, various predictive approaches have emerged, ranging from graph-based models to methods based on the three-dimensional structure of reactants and products. In tandem, many representations have been developed to predict experimental targets, which may hold promise for barrier prediction as well. Here, we bring together all of these efforts and benchmark various methods (Morgan fingerprints, the DRFP, the CGR representation-based Chemprop, SLATMd, B2Rl2, EquiReact and language model BERT + RXNFP) for the prediction of computed activation barriers on three diverse datasets.
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Affiliation(s)
- Puck van Gerwen
- Laboratory for Computational Molecular Design, Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne 1015 Lausanne Switzerland
- National Center for Competence in Research-Catalysis (NCCR-Catalysis), École Polytechnique Fédérale de Lausanne 1015 Lausanne Switzerland
| | - Ksenia R Briling
- Laboratory for Computational Molecular Design, Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne 1015 Lausanne Switzerland
| | - Yannick Calvino Alonso
- Laboratory for Computational Molecular Design, Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne 1015 Lausanne Switzerland
| | - Malte Franke
- Laboratory for Computational Molecular Design, Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne 1015 Lausanne Switzerland
| | - Clemence Corminboeuf
- Laboratory for Computational Molecular Design, Institute of Chemical Sciences and Engineering, École Polytechnique Fédérale de Lausanne 1015 Lausanne Switzerland
- National Center for Competence in Research-Catalysis (NCCR-Catalysis), École Polytechnique Fédérale de Lausanne 1015 Lausanne Switzerland
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8
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Kammeraad JA, Das S, Argüelles AJ, Sayyed FB, Zimmerman PM. Conformational Sampling over Transition-Metal-Catalyzed Reaction Pathways: Toward Revealing Atroposelectivity. Org Lett 2024; 26:2867-2871. [PMID: 38241482 PMCID: PMC11135461 DOI: 10.1021/acs.orglett.3c04047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2024]
Abstract
The Py-Conformational-Sampling (PyCoSa) technique is introduced as a systematic computational means to sample the configurational space of transition-metal-catalyzed stereoselective reactions. When applied to atroposelective Suzuki-Miyaura coupling to create axially chiral biaryl products, the results show a range of mechanistic possibilities that include multiple low-energy channels through which C-C bonds can be formed.
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Affiliation(s)
- Joshua A Kammeraad
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
| | - Soumik Das
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
| | - Alonso J Argüelles
- Synthetic Molecule Design and Development, Eli Lilly, Eli Lilly, Indianapolis, Indiana 46221, United States
| | - Fareed Bhasha Sayyed
- Synthetic Molecule Design and Development, Eli Lilly Services India Pvt Ltd, Devarabeesanahalli, Bengaluru, Karnataka 560103, India
| | - Paul M Zimmerman
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
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9
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Koda SI, Saito S. Locating Transition States by Variational Reaction Path Optimization with an Energy-Derivative-Free Objective Function. J Chem Theory Comput 2024; 20:2798-2811. [PMID: 38513192 DOI: 10.1021/acs.jctc.3c01246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2024]
Abstract
Locating transition states is essential for understanding molecular reactions. We propose a double-ended transition state search method by revisiting a variational reaction path optimization method known as the MaxFlux method. Although its original purpose is to add temperature effects to reaction paths, we conversely let the temperature approach zero to obtain an asymptotically exact minimum energy path and its corresponding transition state in variational formalism with an energy-derivative-free objective function. Using several numerical techniques to directly optimize the objective function, the present method reliably finds transition states with low computational cost. In particular, only three force evaluations per iteration are sufficient. This is confirmed on a variety of molecular reactions where the nudged elastic band method often fails. The present method is implemented in Python using the Atomic Simulation Environment and is available on GitHub.
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Affiliation(s)
- Shin-Ichi Koda
- Department of Theoretical and Computational Molecular Science, Institute for Molecular Science, Myodaiji, Okazaki, Aichi 444-8585, Japan
- School of Physical Sciences, The Graduate University for Advanced Studies, Myodaiji, Okazaki, Aichi 444-8585, Japan
| | - Shinji Saito
- Department of Theoretical and Computational Molecular Science, Institute for Molecular Science, Myodaiji, Okazaki, Aichi 444-8585, Japan
- School of Physical Sciences, The Graduate University for Advanced Studies, Myodaiji, Okazaki, Aichi 444-8585, Japan
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10
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Vadaddi SM, Zhao Q, Savoie BM. Graph to Activation Energy Models Easily Reach Irreducible Errors but Show Limited Transferability. J Phys Chem A 2024; 128:2543-2555. [PMID: 38517281 DOI: 10.1021/acs.jpca.3c07240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2024]
Abstract
Activation energy characterization of competing reactions is a costly but crucial step for understanding the kinetic relevance of distinct reaction pathways, product yields, and myriad other properties of reacting systems. The standard methodology for activation energy characterization has historically been a transition state search using the highest level of theory that can be afforded. However, recently, several groups have popularized the idea of predicting activation energies directly based on nothing more than the reactant and product graphs, a sufficiently complex neural network, and a broad enough data set. Here, we have revisited this task using the recently developed Reaction Graph Depth 1 (RGD1) transition state data set and several newly developed graph attention architectures. All of these new architectures achieve similar state-of-the-art results of ∼4 kcal/mol mean absolute error on withheld testing sets of reactions but poor performance on external testing sets composed of reactions with differing mechanisms, reaction molecularity, or reactant size distribution. Limited transferability is also shown to be shared by other contemporary graph to activation energy architectures through a series of case studies. We conclude that an array of standard graph architectures can already achieve results comparable to the irreducible error of available reaction data sets but that out-of-distribution performance remains poor.
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Affiliation(s)
- Sai Mahit Vadaddi
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana 47906, United States
| | - Qiyuan Zhao
- Department of Medicinal Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Brett M Savoie
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana 47906, United States
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11
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Xu W, Zhao Y, Chen J, Wan Z, Yan D, Zhang X, Zhang R. A Q-learning method based on coarse-to-fine potential energy surface for locating transition state and reaction pathway. J Comput Chem 2024; 45:487-497. [PMID: 37966714 DOI: 10.1002/jcc.27259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 10/25/2023] [Accepted: 11/02/2023] [Indexed: 11/16/2023]
Abstract
Transition state (TS) on the potential energy surface (PES) plays a key role in determining the kinetics and thermodynamics of chemical reactions. Inspired by the fact that the dynamics of complex systems are always driven by rare but significant transition events, we herein propose a TS search method in accordance with the Q-learning algorithm. Appropriate reward functions are set for a given PES to optimize the reaction pathway through continuous trial and error, and then the TS can be obtained from the optimized reaction pathway. The validity of this Q-learning method with reasonable settings of Q-value table including actions, states, learning rate, greedy rate, discount rate, and so on, is exemplified in 2 two-dimensional potential functions. In the applications of the Q-learning method to two chemical reactions, it is demonstrated that the Q-learning method can predict consistent TS and reaction pathway with those by ab initio calculations. Notably, the PES must be well prepared before using the Q-learning method, and a coarse-to-fine PES scanning scheme is thus introduced to save the computational time while maintaining the accuracy of the Q-learning prediction. This work offers a simple and reliable Q-learning method to search for all possible TS and reaction pathway of a chemical reaction, which may be a new option for effectively exploring the PES in an extensive search manner.
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Affiliation(s)
- Wenjun Xu
- Department of Physics, City University of Hong Kong, Hong Kong SAR, China
| | - Yanling Zhao
- Department of Physics, City University of Hong Kong, Hong Kong SAR, China
| | - Jialu Chen
- Department of Physics, City University of Hong Kong, Hong Kong SAR, China
| | - Zhongyu Wan
- Department of Physics, City University of Hong Kong, Hong Kong SAR, China
| | - Dadong Yan
- Department of Physics, Beijing Normal University, Beijing, China
| | - Xinghua Zhang
- School of Science, Beijing Jiaotong University, Beijing, China
| | - Ruiqin Zhang
- Department of Physics, City University of Hong Kong, Hong Kong SAR, China
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12
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Zhelavskyi O, Parikh S, Jhang YJ, Staples RJ, Zimmerman PM, Nagorny P. Green Light Promoted Iridium(III)/Copper(I)-Catalyzed Addition of Alkynes to Aziridinoquinoxalines Through the Intermediacy of Azomethine Ylides. Angew Chem Int Ed Engl 2024; 63:e202318876. [PMID: 38267370 PMCID: PMC10939844 DOI: 10.1002/anie.202318876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 01/23/2024] [Accepted: 01/24/2024] [Indexed: 01/26/2024]
Abstract
This manuscript describes the development of alkyne addition to the aziridine moiety of aziridinoquinoxalines using dual Ir(III)/Cu(I) catalytic system under green light-emitting diode (LED) photolysis (λmax =525 nm). This mild method features high levels of chemo- and regioselectivity and was used to generate 30 highly functionalized substituted dihydroquinoxalines in 36-98 % yield. This transformation was also carried asymmetrically using phthalazinamine-based chiral ligand to provide 9 chiral addition products in 96 : 4 to 86 : 14 e.r. The experimental and quantum chemical explorations of this reaction suggest a mechanism that involves Ir(III)-catalyzed triplet energy transfer followed by a ring-opening reaction ultimately leading to the formation of azomethine ylide intermediates. These azomethine intermediates undergo sequential protonation/copper(I) acetylide addition to provide the products.
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Affiliation(s)
| | - Seren Parikh
- Chemistry Department, University of Michigan, Ann Arbor, MI 48109, USA
| | - Yin-Jia Jhang
- Chemistry Department, University of Michigan, Ann Arbor, MI 48109, USA
| | - Richard J Staples
- Department of Chemistry and Chemical Biology, Michigan State University, East Lansing, MI 48824, USA
| | - Paul M Zimmerman
- Chemistry Department, University of Michigan, Ann Arbor, MI 48109, USA
| | - Pavel Nagorny
- Chemistry Department, University of Michigan, Ann Arbor, MI 48109, USA
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13
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McFarlane NR, Harvey JN. Exploration of biochemical reactivity with a QM/MM growing string method. Phys Chem Chem Phys 2024; 26:5999-6007. [PMID: 38293892 DOI: 10.1039/d3cp05772k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
In this work, we have implemented the single-ended growing string method using a hybrid internal/Cartesian coordinate scheme within our in-house QM/MM package, QoMMMa, representing the first implementation of the growing string method in the QM/MM framework. The goal of the implementation was to facilitate generation of QM/MM reaction pathways with minimal user input, and also to improve the quality of the pathways generated as compared to the widely used adiabatic mapping approach. We have validated the algorithm against a reaction which has been studied extensively in previous computational investigations - the Claisen rearrangement catalysed by chorismate mutase. The nature of the transition state and the height of the barrier was predicted well using our algorithm, where more than 88% of the pathways generated were deemed to be of production quality. Directly compared to using adiabatic mapping, we found that while our QM/MM single-ended growing string method is slightly less efficient, it readily produces reaction pathways with fewer discontinuites and thus minimises the need for involved remapping of unsatisfactory energy profiles.
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Affiliation(s)
- Neil R McFarlane
- Department of Chemistry, KU Leuven, B-3001 Leuven, Celestijnenlaan 200f, 2404, Belgium.
| | - Jeremy N Harvey
- Department of Chemistry, KU Leuven, B-3001 Leuven, Celestijnenlaan 200f, 2404, Belgium.
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14
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Schmerwitz YLA, Ásgeirsson V, Jónsson H. Improved Initialization of Optimal Path Calculations Using Sequential Traversal over the Image-Dependent Pair Potential Surface. J Chem Theory Comput 2024; 20:155-163. [PMID: 38154117 DOI: 10.1021/acs.jctc.3c01111] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2023]
Abstract
In reaction path optimization, such as the calculation of a minimum energy path (MEP) between given reactant and product configurations of atoms, it is advantageous to start with an initial guess where the close proximity of atoms is avoided and bonds are not unnecessarily broken only to be reformed later. When the configurations of the atoms are described with Cartesian coordinates, a linear interpolation between the end points can be problematic, and a better option is provided by the so-called image dependent pair potential (IDPP) approach where interpolated pairwise distances are generated to form an objective function that can be used to construct an improved initial path. When started with a linear interpolation, this method can, however, still lead to unnecessary bond breaking in, for example, reactions in which a molecular subgroup undergoes significant rotation. In the method presented here, this problem is addressed by constructing the path gradually, introducing images sequentially starting from the vicinity of the end points while the distance between images in the central region is larger. The distribution of images is controlled by systematically scaling the tightness of springs acting between the images until the desired number of images is obtained, and they are evenly spaced. This procedure generates an initial path on the IDPP surface, a task that requires negligible computational effort, as no evaluation of the energy of the system is needed. The calculation of the MEP, typically using electronic structure calculations, is then subsequently carried out in a way that makes efficient use of parallel computing with the nudged elastic band method. Several examples of reactions are given where the linear interpolation IDPP (LI-IDPP) method yields problematic paths with unnecessary bond breaking in some of the intermediate images, while the sequential IDPP (S-IDPP) method yields paths that are significantly closer to realistic MEPs.
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Affiliation(s)
- Yorick L A Schmerwitz
- Science Institute and Faculty of Physical Sciences, University of Iceland VR-III, Reykjavík 107, Iceland
- Institut für Physikalische und Theoretische Chemie, Fakultät für Chemie und Pharmazie, Julius-Maximilians-Universität Würzburg, Emil-Fischer-Straße 42, Würzburg D-97074, Germany
| | - Vilhjálmur Ásgeirsson
- Science Institute and Faculty of Physical Sciences, University of Iceland VR-III, Reykjavík 107, Iceland
| | - Hannes Jónsson
- Science Institute and Faculty of Physical Sciences, University of Iceland VR-III, Reykjavík 107, Iceland
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15
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Kim S, Woo J, Kim WY. Diffusion-based generative AI for exploring transition states from 2D molecular graphs. Nat Commun 2024; 15:341. [PMID: 38184661 PMCID: PMC10771475 DOI: 10.1038/s41467-023-44629-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Accepted: 12/21/2023] [Indexed: 01/08/2024] Open
Abstract
The exploration of transition state (TS) geometries is crucial for elucidating chemical reaction mechanisms and modeling their kinetics. Recently, machine learning (ML) models have shown remarkable performance for prediction of TS geometries. However, they require 3D conformations of reactants and products often with their appropriate orientations as input, which demands substantial efforts and computational cost. Here, we propose a generative approach based on the stochastic diffusion method, namely TSDiff, for prediction of TS geometries just from 2D molecular graphs. TSDiff outperforms the existing ML models with 3D geometries in terms of both accuracy and efficiency. Moreover, it enables to sample various TS conformations, because it learns the distribution of TS geometries for diverse reactions in training. Thus, TSDiff finds more favorable reaction pathways with lower barrier heights than those in the reference database. These results demonstrate that TSDiff shows promising potential for an efficient and reliable TS exploration.
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Affiliation(s)
- Seonghwan Kim
- Department of Chemistry, KAIST, 291 Daehak-ro, Yuseong-gu, 34141, Daejeon, Republic of Korea
| | - Jeheon Woo
- Department of Chemistry, KAIST, 291 Daehak-ro, Yuseong-gu, 34141, Daejeon, Republic of Korea
| | - Woo Youn Kim
- Department of Chemistry, KAIST, 291 Daehak-ro, Yuseong-gu, 34141, Daejeon, Republic of Korea.
- AI Institute, KAIST, 291 Daehak-ro, Yuseong-gu, 34141, Daejeon, Republic of Korea.
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16
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Kopp WA, Huang C, Zhao Y, Yu P, Schmalz F, Krep L, Leonhard K. Automatic Potential Energy Surface Exploration by Accelerated Reactive Molecular Dynamics Simulations: From Pyrolysis to Oxidation Chemistry. J Phys Chem A 2023; 127:10681-10692. [PMID: 38059461 DOI: 10.1021/acs.jpca.3c05253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/08/2023]
Abstract
Automatic potential energy surface (PES) exploration is important to a better understanding of reaction mechanisms. Existing automatic PES mapping tools usually rely on predefined knowledge or computationally expensive on-the-fly quantum-chemical calculations. In this work, we have developed the PESmapping algorithm for discovering novel reaction pathways and automatically mapping out the PES using merely one starting species is present. The algorithm explores the unknown PES by iteratively spawning new reactive molecular dynamics (RMD) simulations for species that it has detected within previous RMD simulations. We have therefore extended the RMD simulation tool ChemTraYzer2.1 (Chemical Trajectory Analyzer, CTY) for this PESmapping algorithm. It can generate new seed species, automatically start replica simulations for new pathways, and stop the simulation when a reaction is found, reducing the computational cost of the algorithm. To explore PESs with low-temperature reactions, we applied the acceleration method collective variable (CV)-driven hyperdynamics. This involved the development of tailored CV templates, which are discussed in this study. We validate our approach for known pathways in various pyrolysis and oxidation systems: hydrocarbon isomerization and dissociation (C4H7 and C8H7 PES), mostly dominant at high temperatures and low-temperature oxidation of n-butane (C4H9O2 PES) and cyclohexane (C6H11O2 PES). As a result, in addition to new pathways showing up in the simulations, common isomerization and dissociation pathways were found very fast: for example, 44 reactions of butenyl radicals including major isomerizations and decompositions within about 30 min wall time and low-temperature chemistry such as the internal H-shift of RO2 → QO2H within 1 day wall time. Last, we applied PESmapping to the oxidation of the recently proposed biohybrid fuel 1,3-dioxane and validated that the tool could be used to discover new reaction pathways of larger molecules that are of practical use.
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Affiliation(s)
- Wassja A Kopp
- Institute of Technical Thermodynamics, RWTH Aachen University, 52062 Aachen, Germany
| | - Can Huang
- Institute of Technical Thermodynamics, RWTH Aachen University, 52062 Aachen, Germany
| | - Yuqing Zhao
- Institute of Technical Thermodynamics, RWTH Aachen University, 52062 Aachen, Germany
| | - Peiyang Yu
- Institute of Technical Thermodynamics, RWTH Aachen University, 52062 Aachen, Germany
| | - Felix Schmalz
- Institute of Technical Thermodynamics, RWTH Aachen University, 52062 Aachen, Germany
| | - Lukas Krep
- Institute of Technical Thermodynamics, RWTH Aachen University, 52062 Aachen, Germany
| | - Kai Leonhard
- Institute of Technical Thermodynamics, RWTH Aachen University, 52062 Aachen, Germany
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17
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Rasmussen MH, Seumer J, Jensen JH. Toward De Novo Catalyst Discovery: Fast Identification of New Catalyst Candidates for Alcohol-Mediated Morita-Baylis-Hillman Reactions. Angew Chem Int Ed Engl 2023; 62:e202310580. [PMID: 37830522 DOI: 10.1002/anie.202310580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 09/15/2023] [Accepted: 10/13/2023] [Indexed: 10/14/2023]
Abstract
Recently we have demonstrated how a genetic algorithm (GA) starting from random tertiary amines can be used to discover a new and efficient catalyst for the alcohol-mediated Morita-Baylis-Hillman (MBH) reaction. In particular, the discovered catalyst was shown experimentally to be eight times more active than DABCO, commonly used to catalyze the MBH reaction. This represents a breakthrough in using generative models for catalyst optimization. However, the GA procedure, and hence discovery, relied on two important pieces of information; 1) the knowledge that tertiary amines catalyze the reaction and 2) the mechanism and reaction profile for the catalyzed reaction, in particular the transition state structure of the rate-determining step. Thus, truly de novo catalyst discovery must include these steps. Here we present such a method for discovering catalyst candidates for a specific reaction while simultaneously proposing a mechanism for the catalyzed reaction. We show that tertiary amines and phosphines are potential catalysts for the MBH reaction by screening 11 molecular templates representing common functional groups. The method relies on an automated reaction discovery workflow using meta-dynamics calculations. Combining this method for catalyst candidate discovery with our GA-based catalyst optimization method results in an algorithm for truly de novo catalyst discovery.
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Affiliation(s)
- Maria H Rasmussen
- Department of Chemistry, University of Copenhagen, Universitetsparken 5, 2100, Copenhagen, Denmark
| | - Julius Seumer
- Department of Chemistry, University of Copenhagen, Universitetsparken 5, 2100, Copenhagen, Denmark
| | - Jan H Jensen
- Department of Chemistry, University of Copenhagen, Universitetsparken 5, 2100, Copenhagen, Denmark
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18
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Skinner KC, Kammeraad JA, Wymore T, Narayan ARH, Zimmerman PM. Simulating Electron Transfer Reactions in Solution: Radical-Polar Crossover. J Phys Chem B 2023; 127:10097-10107. [PMID: 37976536 PMCID: PMC11135460 DOI: 10.1021/acs.jpcb.3c06120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2023]
Abstract
Single-electron transfer (SET) promotes a wide variety of interesting chemical transformations, but modeling of SET requires a careful treatment of electronic and solvent effects to give meaningful insight. Therefore, a combined constrained density functional theory and molecular mechanics (CDFT/MM) tool is introduced specifically for SET-initiated reactions. Mechanisms for two radical-polar crossover reactions involving the organic electron donors tetrakis(dimethylamino)ethylene (TDAE) and tetrathiafulvalene (TTF) were studied with the new tool. An unexpected tertiary radical intermediate within the TDAE system was identified, relationships between kinetics and substitution in the TTF system were explained, and the impact of the solvent environments on the TDAE and TTF reactions were examined. The results highlight the need for including solvent dynamics when quantifying SET kinetics and thermodynamics, as a free energy difference of >20 kcal/mol was observed. Overall, the new method informs mechanistic analysis of SET-initiated reactions and therefore is envisioned to be useful for studying reactions in the condensed phase.
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Affiliation(s)
- Kevin C Skinner
- Life Sciences Institute, University of Michigan, Ann Arbor, Michigan 48109, United States
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Josh A Kammeraad
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Troy Wymore
- Laufer Center, Stony Brook University, Stony Brook, New York 11794, United States
| | - Alison R H Narayan
- Life Sciences Institute, University of Michigan, Ann Arbor, Michigan 48109, United States
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Paul M Zimmerman
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States
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19
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Zhang Y, Xu C, Lan Z. Automated Exploration of Reaction Networks and Mechanisms Based on Metadynamics Nanoreactor Simulations. J Chem Theory Comput 2023. [PMID: 38031422 DOI: 10.1021/acs.jctc.3c00752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2023]
Abstract
We developed an automated approach to construct a complex reaction network and explore the reaction mechanisms for numerous reactant molecules by integrating several theoretical approaches. Nanoreactor-type molecular dynamics was used to generate possible chemical reactions, in which the metadynamics was used to overcome the reaction barriers, and the semiempirical GFN2-xTB method was used to reduce the computational cost. Reaction events were identified from trajectories using the hidden Markov model based on the evolution of the molecular connectivity. This provided the starting points for further transition-state searches at the electronic structure levels of density functional theory to obtain the reaction mechanism. Finally, the entire reaction network containing multiple pathways was built. The feasibility and efficiency of the automated construction of the reaction network were investigated using the HCHO and NH3 biomolecular reaction and the reaction network for a multispecies system comprising dozens of HCN and H2O molecules. The results indicated that the proposed approach provides a valuable and effective tool for the automated exploration of the reaction networks.
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Affiliation(s)
- Yutai Zhang
- Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety and MOE Key Laboratory of Environmental Theoretical Chemistry, SCNU Environmental Research Institute, School of Environment, South China Normal University, Guangzhou 510006, P. R. China
| | - Chao Xu
- Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety and MOE Key Laboratory of Environmental Theoretical Chemistry, SCNU Environmental Research Institute, School of Environment, South China Normal University, Guangzhou 510006, P. R. China
| | - Zhenggang Lan
- Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety and MOE Key Laboratory of Environmental Theoretical Chemistry, SCNU Environmental Research Institute, School of Environment, South China Normal University, Guangzhou 510006, P. R. China
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20
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Chang AM, Meisner J, Xu R, Martínez TJ. Efficient Acceleration of Reaction Discovery in the Ab Initio Nanoreactor: Phenyl Radical Oxidation Chemistry. J Phys Chem A 2023; 127:9580-9589. [PMID: 37934692 DOI: 10.1021/acs.jpca.3c05484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2023]
Abstract
Over the years, many computational strategies have been employed to elucidate reaction networks. One of these methods is accelerated molecular dynamics, which can circumvent the expense required in dynamics to find all reactants and products (local minima) and transition states (first-order saddle points) on a potential energy surface (PES) by using fictitious forces that promote reaction events. The ab initio nanoreactor uses these accelerating forces to study large chemical reaction networks from first-principles quantum mechanics. In the initial nanoreactor studies, this acceleration was done through a piston periodic compression potential, which pushes molecules together to induce entropically unfavorable bimolecular reactions. However, the piston is not effective for discovering intramolecular and dissociative reactions, such as those integral to the decomposition channels of phenyl radical oxidation. In fact, the choice of accelerating forces dictates not only the rate of reaction discovery but also the types of reactions discovered; thus, it is critical to understand the biases and efficacies of these forces. In this study, we examine forces using metadynamics, attractive potentials, and local thermostats for accelerating reaction discovery. For each force, we construct a separate phenyl radical combustion reaction network using solely that force in discovery trajectories. We elucidate the enthalpic and entropic trends of each accelerating force and highlight their efficiency in reaction discovery. Comparing the nanoreactor-constructed reaction networks with literature renditions of the phenyl radical combustion PES shows that a combination of accelerating forces is best suited for reaction discovery.
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Affiliation(s)
- Alexander M Chang
- Department of Chemistry and The PULSE Institute, Stanford University, Stanford, California 94305, United States
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025, United States
| | - Jan Meisner
- Department of Chemistry, Heinrich-Heine-Universität Düsseldorf, Düsseldorf 40225, Germany
| | - Rui Xu
- Department of Chemistry and The PULSE Institute, Stanford University, Stanford, California 94305, United States
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025, United States
| | - Todd J Martínez
- Department of Chemistry and The PULSE Institute, Stanford University, Stanford, California 94305, United States
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025, United States
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21
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Johnson MS, Gierada M, Hermes ED, Bross DH, Sargsyan K, Najm HN, Zádor J. Pynta─An Automated Workflow for Calculation of Surface and Gas-Surface Kinetics. J Chem Inf Model 2023; 63:5153-5168. [PMID: 37559203 DOI: 10.1021/acs.jcim.3c00948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/11/2023]
Abstract
Many important industrial processes rely on heterogeneous catalytic systems. However, given all possible catalysts and conditions of interest, it is impractical to optimize most systems experimentally. Automatically generated microkinetic models can be used to efficiently consider many catalysts and conditions. However, these microkinetic models require accurate estimation of many thermochemical and kinetic parameters. Manually calculating these parameters is tedious and error prone, involving many interconnected computations. We present Pynta, a workflow software for automating the calculation of surface and gas-surface reactions. Pynta takes the reactants, products, and atom maps for the reactions of interest, generates sets of initial guesses for all species and saddle points, runs all optimizations, frequency, and IRC calculations, and computes the associated thermochemistry and rate coefficients. It is able to consider all unique adsorption configurations for both adsorbates and saddle points, allowing it to handle high index surfaces and bidentate species. Pynta implements a new saddle point guess generation method called harmonically forced saddle point searching (HFSP). HFSP defines harmonic potentials based on the optimized adsorbate geometries and which bonds are breaking and forming that allow initial placements to be optimized using the GFN1-xTB semiempirical method to create reliable saddle point guesses. This method is reaction class agnostic and fast, allowing Pynta to consider all possible adsorbate site placements efficiently. We demonstrate Pynta on 11 diverse reactions involving monodenate, bidentate, and gas-phase species, many distinct reaction classes, and both a low and a high index facet of Cu. Our results suggest that it is very important to consider reactions between adsorbates adsorbed in all unique configurations for interadsorbate group transfers and reactions on high index surfaces.
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Affiliation(s)
- Matthew S Johnson
- Combustion Research Facility, Sandia National Laboratories, Livermore, California 94550, United States
| | - Maciej Gierada
- Combustion Research Facility, Sandia National Laboratories, Livermore, California 94550, United States
| | - Eric D Hermes
- Combustion Research Facility, Sandia National Laboratories, Livermore, California 94550, United States
| | - David H Bross
- Chemical Sciences and Engineering Division, Argonne National Laboratory, Lemont, Illinois 60439, United States
| | - Khachik Sargsyan
- Combustion Research Facility, Sandia National Laboratories, Livermore, California 94550, United States
| | - Habib N Najm
- Combustion Research Facility, Sandia National Laboratories, Livermore, California 94550, United States
| | - Judit Zádor
- Combustion Research Facility, Sandia National Laboratories, Livermore, California 94550, United States
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22
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Xu R, Meisner J, Chang AM, Thompson KC, Martínez TJ. First principles reaction discovery: from the Schrodinger equation to experimental prediction for methane pyrolysis. Chem Sci 2023; 14:7447-7464. [PMID: 37449065 PMCID: PMC10337770 DOI: 10.1039/d3sc01202f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 06/02/2023] [Indexed: 07/18/2023] Open
Abstract
Our recent success in exploiting graphical processing units (GPUs) to accelerate quantum chemistry computations led to the development of the ab initio nanoreactor, a computational framework for automatic reaction discovery and kinetic model construction. In this work, we apply the ab initio nanoreactor to methane pyrolysis, from automatic reaction discovery to path refinement and kinetic modeling. Elementary reactions occurring during methane pyrolysis are revealed using GPU-accelerated ab initio molecular dynamics simulations. Subsequently, these reaction paths are refined at a higher level of theory with optimized reactant, product, and transition state geometries. Reaction rate coefficients are calculated by transition state theory based on the optimized reaction paths. The discovered reactions lead to a kinetic model with 53 species and 134 reactions, which is validated against experimental data and simulations using literature kinetic models. We highlight the advantage of leveraging local brute force and Monte Carlo sensitivity analysis approaches for efficient identification of important reactions. Both sensitivity approaches can further improve the accuracy of the methane pyrolysis kinetic model. The results in this work demonstrate the power of the ab initio nanoreactor framework for computationally affordable systematic reaction discovery and accurate kinetic modeling.
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Affiliation(s)
- Rui Xu
- Department of Chemistry, The PULSE Institute, Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory 2575 Sand Hill Road Menlo Park CA 94025 USA
| | - Jan Meisner
- Department of Chemistry, The PULSE Institute, Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory 2575 Sand Hill Road Menlo Park CA 94025 USA
| | - Alexander M Chang
- Department of Chemistry, The PULSE Institute, Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory 2575 Sand Hill Road Menlo Park CA 94025 USA
| | - Keiran C Thompson
- Department of Chemistry, The PULSE Institute, Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory 2575 Sand Hill Road Menlo Park CA 94025 USA
| | - Todd J Martínez
- Department of Chemistry, The PULSE Institute, Stanford University Stanford CA 94305 USA
- SLAC National Accelerator Laboratory 2575 Sand Hill Road Menlo Park CA 94025 USA
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23
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Plett C, Katbashev A, Ehlert S, Grimme S, Bursch M. ONIOM meets xtb: efficient, accurate, and robust multi-layer simulations across the periodic table. Phys Chem Chem Phys 2023. [PMID: 37378957 DOI: 10.1039/d3cp02178e] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/29/2023]
Abstract
The computational treatment of large molecular structures is of increasing interest in fields of modern chemistry. Accordingly, efficient quantum chemical approaches are needed to perform sophisticated investigations on such systems. This engaged the development of the well-established "Our own N-layered integrated molecular orbital and molecular mechanics" (ONIOM) multi-layer scheme [L. W. Chung et al., Chem. Rev., 2015, 115, 5678-5796]. In this work, we present the specific implementation of the ONIOM scheme into the xtb semi-empirical extended tight-binding program package and its application to challenging transition-metal complexes. The efficient and broadly applicable GFNn-xTB and -FF methods are applied in the ONIOM framework to elucidate reaction energies, geometry optimizations, and explicit solvation effects for metal-organic systems with up to several hundreds of atoms. It is shown that an ONIOM-based combination of density functional theory, semi-empirical, and force-field methods can be used to drastically reduce the computational costs and thus enable the investigation of huge systems at almost no significant loss in accuracy.
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Affiliation(s)
- Christoph Plett
- Mulliken Center for Theoretical Chemistry, Universität Bonn, Beringstr. 4, 53115 Bonn, Germany.
| | - Abylay Katbashev
- Mulliken Center for Theoretical Chemistry, Universität Bonn, Beringstr. 4, 53115 Bonn, Germany.
| | - Sebastian Ehlert
- Microsoft Research AI4Science, Evert van de Beekstraat 254, 1118 CZ Schiphol, The Netherlands
| | - Stefan Grimme
- Mulliken Center for Theoretical Chemistry, Universität Bonn, Beringstr. 4, 53115 Bonn, Germany.
| | - Markus Bursch
- Max-Planck-Institut für Kohlenforschung, Kaiser-Wilhelm-Platz 1, 45470 Mülheim an der Ruhr, Germany.
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24
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Zhao Q, Vaddadi SM, Woulfe M, Ogunfowora LA, Garimella SS, Isayev O, Savoie BM. Comprehensive exploration of graphically defined reaction spaces. Sci Data 2023; 10:145. [PMID: 36935430 PMCID: PMC10025260 DOI: 10.1038/s41597-023-02043-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 02/27/2023] [Indexed: 03/21/2023] Open
Abstract
Existing reaction transition state (TS) databases are comparatively small and lack chemical diversity. Here, this data gap has been addressed using the concept of a graphically-defined model reaction to comprehensively characterize a reaction space associated with C, H, O, and N containing molecules with up to 10 heavy (non-hydrogen) atoms. The resulting dataset is composed of 176,992 organic reactions possessing at least one validated TS, activation energy, heat of reaction, reactant and product geometries, frequencies, and atom-mapping. For 33,032 reactions, more than one TS was discovered by conformational sampling, allowing conformational errors in TS prediction to be assessed. Data is supplied at the GFN2-xTB and B3LYP-D3/TZVP levels of theory. A subset of reactions were recalculated at the CCSD(T)-F12/cc-pVDZ-F12 and ωB97X-D2/def2-TZVP levels to establish relative errors. The resulting collection of reactions and properties are called the Reaction Graph Depth 1 (RGD1) dataset. RGD1 represents the largest and most chemically diverse TS dataset published to date and should find immediate use in developing novel machine learning models for predicting reaction properties.
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Affiliation(s)
- Qiyuan Zhao
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN, 47906, USA
| | - Sai Mahit Vaddadi
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN, 47906, USA
| | - Michael Woulfe
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN, 47906, USA
| | - Lawal A Ogunfowora
- Department of Chemistry, Purdue University, West Lafayette, IN, 47906, USA
| | - Sanjay S Garimella
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN, 47906, USA
| | - Olexandr Isayev
- Department of Chemistry, Carnegie Mellon University, Pittsburgh, PA, 15213, USA
| | - Brett M Savoie
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN, 47906, USA.
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25
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Thiele M, Rose T, Lõkov M, Stadtfeld S, Tshepelevitsh S, Parman E, Opara K, Wölper C, Leito I, Grimme S, Niemeyer J. Multifunctional Organocatalysts - Singly-Linked and Macrocyclic Bisphosphoric Acids for Asymmetric Phase-Transfer and Brønsted-Acid Catalysis. Chemistry 2023; 29:e202202953. [PMID: 36161384 PMCID: PMC10099347 DOI: 10.1002/chem.202202953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Indexed: 01/12/2023]
Abstract
The linking of phosphoric acids via covalent or mechanical bonds has proven to be a successful strategy for the design of novel organocatalysts. Here, we present the first systematic investigation of singly-linked and macrocyclic bisphosphoric acids, including their synthesis and their application in phase-transfer and Brønsted acid catalysis. We found that the novel bisphosphoric acids show dramatically increased enantioselectivities in comparison to their monophosphoric acid analogues. However, the nature, length and number of linkers has a profound influence on the enantioselectivities. In the asymmetric dearomative fluorination via phase-transfer catalysis, bisphosphoric acids with a single, rigid bisalkyne-linker give the best results with moderate to good enantiomeric excesses. In contrast, bisphosphoric acids with flexible linkers give excellent enantioselectivities in the transfer-hydrogenation of quinolines via cooperative Brønsted acid catalysis. In the latter case, sufficiently long linkers are needed for high stereoselectivities, as found experimentally and supported by DFT calculations.
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Affiliation(s)
- Maike Thiele
- Faculty of Chemistry (Organic Chemistry) and, Center for Nanointegration Duisburg-Essen (CENIDE), University of Duisburg-Essen, 45141, Essen, Germany
| | - Thomas Rose
- Mulliken Center for Theoretical Chemistry, Rheinische Friedrich-Wilhelms-Universität Bonn, Beringstrasse 4, 53115, Bonn, Germany
| | - Märt Lõkov
- University of Tartu, Institute of Chemistry, 14a Ravila str, 50411, Tartu, Estonia
| | - Sophia Stadtfeld
- Faculty of Chemistry (Organic Chemistry) and, Center for Nanointegration Duisburg-Essen (CENIDE), University of Duisburg-Essen, 45141, Essen, Germany
| | - Sofja Tshepelevitsh
- University of Tartu, Institute of Chemistry, 14a Ravila str, 50411, Tartu, Estonia
| | - Elisabeth Parman
- University of Tartu, Institute of Chemistry, 14a Ravila str, 50411, Tartu, Estonia
| | - Karina Opara
- Faculty of Chemistry (Organic Chemistry) and, Center for Nanointegration Duisburg-Essen (CENIDE), University of Duisburg-Essen, 45141, Essen, Germany
| | - Christoph Wölper
- Faculty of Chemistry, Inorganic Chemistry, University of Duisburg-Essen, 45141, Essen, Germany
| | - Ivo Leito
- University of Tartu, Institute of Chemistry, 14a Ravila str, 50411, Tartu, Estonia
| | - Stefan Grimme
- Mulliken Center for Theoretical Chemistry, Rheinische Friedrich-Wilhelms-Universität Bonn, Beringstrasse 4, 53115, Bonn, Germany
| | - Jochen Niemeyer
- Faculty of Chemistry (Organic Chemistry) and, Center for Nanointegration Duisburg-Essen (CENIDE), University of Duisburg-Essen, 45141, Essen, Germany
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26
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Hannigan MD, Tami JL, Zimmerman PM, McNeil AJ. Rethinking Catalyst Trapping in Ni-Catalyzed Thieno[3,2- b]thiophene Polymerization. Macromolecules 2022; 55:10821-10830. [PMID: 37396500 PMCID: PMC10312364 DOI: 10.1021/acs.macromol.2c01521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Catalyst-transfer polymerization (CTP) is a chain-growth method used to synthesize conjugated polymers. Although CTP works well for most donor-type monomers, the polymerization stalls with thieno[3,2-b]thiophene when using Ni catalysts. Previous reports have rationalized this result by suggesting that the catalyst is trapped in a Ni0 π-complex with the highly electron-rich arene. In this study, evidence is provided that the catalyst trap is more likely a NiII complex that arises from oxidative insertion of Ni0 into the C-S bonds of thieno[3,2-b]thiophene. This result is consistent with the known reactivity of Ni0 complexes toward S-heteroarenes and is supported herein by 31P nuclear magnetic resonance spectra acquired in situ, as well as data collected from small-molecule model reactions and density-functional theory simulations of the polymerization. We propose that this C-S insertion pathway and related off-cycle reactions may be relevant to understanding or enabling the CTP of other monomers with fused thiophenes.
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Affiliation(s)
- Matthew D Hannigan
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
| | - Jessica L Tami
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
| | - Paul M Zimmerman
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
| | - Anne J McNeil
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States; Macromolecular Science and Engineering Program, University of Michigan, Ann Arbor, Michigan 48109-2800, United States
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27
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Zhao Q, Savoie BM. Algorithmic Explorations of Unimolecular and Bimolecular Reaction Spaces. Angew Chem Int Ed Engl 2022; 61:e202210693. [PMID: 36074520 PMCID: PMC9827825 DOI: 10.1002/anie.202210693] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Indexed: 01/12/2023]
Abstract
Algorithmic reaction exploration based on transition state searches has already made inroads into many niche applications, but its potential as a general-purpose tool is still largely unrealized. Computational cost and the absence of benchmark problems involving larger molecules remain obstacles to further progress. Here an ultra-low cost exploration algorithm is implemented and used to explore the reactivity of unimolecular and bimolecular reactants, comprising a total of 581 reactions involving 51 distinct reactants. The algorithm discovers all established reaction pathways, where such comparisons are possible, while also revealing a much richer reactivity landscape, including lower barrier reaction pathways and a strong dependence of reaction conformation in the apparent barriers of the reported reactions. The diversity of these benchmarks illustrate that reaction exploration algorithms are approaching general-purpose capability.
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Affiliation(s)
- Qiyuan Zhao
- Davidson School of Chemical EngineeringPurdue UniversityWest LafayetteIN47906USA
| | - Brett M. Savoie
- Davidson School of Chemical EngineeringPurdue UniversityWest LafayetteIN47906USA
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28
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Bursch M, Mewes J, Hansen A, Grimme S. Best-Practice DFT Protocols for Basic Molecular Computational Chemistry. Angew Chem Int Ed Engl 2022; 61:e202205735. [PMID: 36103607 PMCID: PMC9826355 DOI: 10.1002/anie.202205735] [Citation(s) in RCA: 153] [Impact Index Per Article: 76.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Indexed: 01/11/2023]
Abstract
Nowadays, many chemical investigations are supported by routine calculations of molecular structures, reaction energies, barrier heights, and spectroscopic properties. The lion's share of these quantum-chemical calculations applies density functional theory (DFT) evaluated in atomic-orbital basis sets. This work provides best-practice guidance on the numerous methodological and technical aspects of DFT calculations in three parts: Firstly, we set the stage and introduce a step-by-step decision tree to choose a computational protocol that models the experiment as closely as possible. Secondly, we present a recommendation matrix to guide the choice of functional and basis set depending on the task at hand. A particular focus is on achieving an optimal balance between accuracy, robustness, and efficiency through multi-level approaches. Finally, we discuss selected representative examples to illustrate the recommended protocols and the effect of methodological choices.
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Affiliation(s)
- Markus Bursch
- Max-Planck-Institut für KohlenforschungKaiser-Wilhelm-Platz 145470Mülheim an der RuhrGermany
| | - Jan‐Michael Mewes
- Mulliken Center for Theoretical ChemistryInstitut für Physikalische und Theoretische ChemieUniversität BonnBeringstraße 453115BonnGermany
| | - Andreas Hansen
- Mulliken Center for Theoretical ChemistryInstitut für Physikalische und Theoretische ChemieUniversität BonnBeringstraße 453115BonnGermany
| | - Stefan Grimme
- Mulliken Center for Theoretical ChemistryInstitut für Physikalische und Theoretische ChemieUniversität BonnBeringstraße 453115BonnGermany
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29
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Ramos-Sánchez P, Harvey JN, Gámez JA. An automated method for graph-based chemical space exploration and transition state finding. J Comput Chem 2022; 44:27-42. [PMID: 36239971 DOI: 10.1002/jcc.27011] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 07/28/2022] [Accepted: 09/05/2022] [Indexed: 12/24/2022]
Abstract
Algorithms that automatically explore the chemical space have been limited to chemical systems with a low number of atoms due to expensive involved quantum calculations and the large amount of possible reaction pathways. The method described here presents a novel solution to the problem of chemical exploration by generating reaction networks with heuristics based on chemical theory. First, a second version of the reaction network is determined through molecular graph transformations acting upon functional groups of the reacting. Only transformations that break two chemical bonds and form two new ones are considered, leading to a significant performance enhancement compared to previously presented algorithm. Second, energy barriers for this reaction network are estimated through quantum chemical calculations by a growing string method, which can also identify non-octet species missed during the previous step and further define the reaction network. The proposed algorithm has been successfully applied to five different chemical reactions, in all cases identifying the most important reaction pathways.
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Affiliation(s)
- Pablo Ramos-Sánchez
- Digital R&D, Covestro Deutschland AG, Leverkusen, Germany.,Department of Chemistry, KU Leuven, Leuven, Belgium
| | | | - José A Gámez
- Digital R&D, Covestro Deutschland AG, Leverkusen, Germany
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30
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Ismail I, Chantreau Majerus R, Habershon S. Graph-Driven Reaction Discovery: Progress, Challenges, and Future Opportunities. J Phys Chem A 2022; 126:7051-7069. [PMID: 36190262 PMCID: PMC9574932 DOI: 10.1021/acs.jpca.2c06408] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 09/22/2022] [Indexed: 11/29/2022]
Abstract
Graph-based descriptors, such as bond-order matrices and adjacency matrices, offer a simple and compact way of categorizing molecular structures; furthermore, such descriptors can be readily used to catalog chemical reactions (i.e., bond-making and -breaking). As such, a number of graph-based methodologies have been developed with the goal of automating the process of generating chemical reaction network models describing the possible mechanistic chemistry in a given set of reactant species. Here, we outline the evolution of these graph-based reaction discovery schemes, with particular emphasis on more recent methods incorporating graph-based methods with semiempirical and ab initio electronic structure calculations, minimum-energy path refinements, and transition state searches. Using representative examples from homogeneous catalysis and interstellar chemistry, we highlight how these schemes increasingly act as "virtual reaction vessels" for interrogating mechanistic questions. Finally, we highlight where challenges remain, including issues of chemical accuracy and calculation speeds, as well as the inherent challenge of dealing with the vast size of accessible chemical reaction space.
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Affiliation(s)
- Idil Ismail
- Department of Chemistry, University
of Warwick, CoventryCV4 7AL, United Kingdom
| | | | - Scott Habershon
- Department of Chemistry, University
of Warwick, CoventryCV4 7AL, United Kingdom
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31
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Avis SJ, Panter JR, Kusumaatmaja H. A robust and memory-efficient transition state search method for complex energy landscapes. J Chem Phys 2022; 157:124107. [PMID: 36182442 DOI: 10.1063/5.0102145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Locating transition states is crucial for investigating transition mechanisms in wide-ranging phenomena, from atomistic to macroscale systems. Existing methods, however, can struggle in problems with a large number of degrees of freedom, on-the-fly adaptive remeshing and coarse-graining, and energy landscapes that are locally flat or discontinuous. To resolve these challenges, we introduce a new double-ended method, the Binary-Image Transition State Search (BITSS). It uses just two states that converge to the transition state, resulting in a fast, flexible, and memory-efficient method. We also show that it is more robust compared to existing bracketing methods that use only two states. We demonstrate its versatility by applying BITSS to three very different classes of problems: Lennard-Jones clusters, shell buckling, and multiphase phase-field models.
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Affiliation(s)
- Samuel J Avis
- Department of Physics, Durham University, South Road, Durham DH1 3LE, United Kingdom
| | - Jack R Panter
- Department of Physics, Durham University, South Road, Durham DH1 3LE, United Kingdom
| | - Halim Kusumaatmaja
- Department of Physics, Durham University, South Road, Durham DH1 3LE, United Kingdom
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32
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Bursch M, Mewes J, Hansen A, Grimme S. Best‐Practice DFT Protocols for Basic Molecular Computational Chemistry**. Angew Chem Int Ed Engl 2022. [DOI: 10.1002/ange.202205735] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Markus Bursch
- Max-Planck-Institut für Kohlenforschung Kaiser-Wilhelm-Platz 1 45470 Mülheim an der Ruhr Germany
| | - Jan‐Michael Mewes
- Mulliken Center for Theoretical Chemistry Institut für Physikalische und Theoretische Chemie Universität Bonn Beringstraße 4 53115 Bonn Germany
| | - Andreas Hansen
- Mulliken Center for Theoretical Chemistry Institut für Physikalische und Theoretische Chemie Universität Bonn Beringstraße 4 53115 Bonn Germany
| | - Stefan Grimme
- Mulliken Center for Theoretical Chemistry Institut für Physikalische und Theoretische Chemie Universität Bonn Beringstraße 4 53115 Bonn Germany
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33
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Robo MT, Frank AR, Butler E, Nett AJ, Cañellas S, Zimmerman PM, Montgomery J. Activation Mechanism of Nickel(0) N-Heterocyclic Carbene Catalysts Stabilized by Fumarate Ligands. Organometallics 2022. [DOI: 10.1021/acs.organomet.2c00279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Michael T. Robo
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
| | - Amie R. Frank
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
| | - Ellen Butler
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
| | - Alex J. Nett
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
| | - Santiago Cañellas
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
| | - Paul M. Zimmerman
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
| | - John Montgomery
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
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34
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Unsleber JP, Grimmel SA, Reiher M. Chemoton 2.0: Autonomous Exploration of Chemical Reaction Networks. J Chem Theory Comput 2022; 18:5393-5409. [PMID: 35926118 DOI: 10.1021/acs.jctc.2c00193] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Fueled by advances in hardware and algorithm design, large-scale automated explorations of chemical reaction space have become possible. Here, we present our approach to an open-source, extensible framework for explorations of chemical reaction mechanisms based on the first-principles of quantum mechanics. It is intended to facilitate reaction network explorations for diverse chemical problems with a wide range of goals such as mechanism elucidation, reaction path optimization, retrosynthetic path validation, reagent design, and microkinetic modeling. The stringent first-principles basis of all algorithms in our framework is key for the general applicability that avoids any restrictions to specific chemical systems. Such an agile framework requires multiple specialized software components of which we present three modules in this work. The key module, Chemoton, drives the exploration of reaction networks. For the exploration itself, we introduce two new algorithms for elementary-step searches that are based on Newton trajectories. The performance of these algorithms is assessed for a variety of reactions characterized by a broad chemical diversity in terms of bonding patterns and chemical elements. Chemoton successfully recovers the vast majority of these. We provide the resulting data, including large numbers of reactions that were not included in our reference set, to be used as a starting point for further explorations and for future reference.
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Affiliation(s)
- Jan P Unsleber
- Laboratorium für Physikalische Chemie, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
| | - Stephanie A Grimmel
- Laboratorium für Physikalische Chemie, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
| | - Markus Reiher
- Laboratorium für Physikalische Chemie, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
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35
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Geiger J, Settels V, Deglmann P, Schäfer A, Bergeler M. Automated input structure generation for single-ended reaction path optimizations. J Comput Chem 2022; 43:1662-1674. [PMID: 35866245 DOI: 10.1002/jcc.26969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 06/21/2022] [Accepted: 06/22/2022] [Indexed: 11/05/2022]
Abstract
The exploration of a reaction network requires highly automated workflows to avoid error-prone and time-consuming manual steps. In this respect, a major bottleneck is the search for transition-state (TS) structures, which frequently fails and, therefore, makes (manual) revision necessary. In this work, we present a technique for obtaining suitable input structures for automated TS searches based on single-ended reaction path optimization algorithms, which makes subsequent TS searches via this method significantly more robust. First, possible input structures are generated based on the spatial alignment of the reactants. The appropriate orientation of reacting groups is achieved via stepwise rotations along selected torsional degrees of freedom. Second, a ranking of the obtained structures is performed according to selected geometric criteria. The main goals are to properly align the reactive atoms, to avoid hindrance within the reaction channel and to resolve steric clashes between the reactants. The developed procedure has been carefully tested on a variety of examples and provides suitable input structures for TS searches within seconds. The method is in daily use in an industrial setting.
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Affiliation(s)
- Julian Geiger
- Institute of Chemical Research of Catalonia (ICIQ), The Barcelona Institute of Science and Technology, Tarragona, Spain
| | | | | | | | - Maike Bergeler
- Institute of Chemical Research of Catalonia (ICIQ), The Barcelona Institute of Science and Technology, Tarragona, Spain
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36
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Ismail I, Robertson C, Habershon S. Successes and challenges in using machine-learned activation energies in kinetic simulations. J Chem Phys 2022; 157:014109. [DOI: 10.1063/5.0096027] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The prediction of the thermodynamic and kinetic properties of chemical reactions is increasingly being addressed by machine-learning (ML) methods such as artificial neural networks (ANNs). While a number of recent studies have reported success in predicting chemical reaction activation energies, less attention has focused on how the accuracy of ML predictions filter through to predictions of macroscopic observables. Here, we consider the impact of the uncertainty associated with ML prediction of activation energies on observable properties of chemical reaction networks, as given by microkinetics simulations based on ML-predicted reaction rates. After training an ANN to predict activation energies given standard molecular descriptors for reactants and products alone, we performed microkinetics simulations of three different prototypical reaction networks: formamide decomposition, aldol reactions and decomposition of 3-hydroperoxypropanal. We find that the kinetic modelling predictions can be in excellent agreement with corresponding simulations performed with ab initio calculations, but this is dependent on the inherent energetic landscape of the networks. We use these simulations to suggest some guidelines for when ML-based activation energies can be reliable, and when one should take more care in applications to kinetics modelling.
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Affiliation(s)
| | | | - Scott Habershon
- Department of Chemistry, University of Warwick, United Kingdom
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37
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Martin JL, Sati GC, Malakar T, Hatt J, Zimmerman PM, Montgomery J. Glycosyl Exchange of Unactivated Glycosidic Bonds: Suppressing or Embracing Side Reactivity in Catalytic Glycosylations. J Org Chem 2022; 87:5817-5826. [PMID: 35413188 PMCID: PMC9173671 DOI: 10.1021/acs.joc.2c00132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
While developing boron-catalyzed glycosylations using glycosyl fluoride donors and trialkylsilyl ether acceptors, competing pathways involving productive glycosylation or glycosyl exchange were observed. Experimental and computational mechanistic studies suggest a novel mode of reactivity where a dioxolenium ion is a key intermediate that promotes both pathways through addition to either a silyl ether or to the acetal of an existing glycosidic linkage. Modifications in catalyst structure enable either pathway to be favored, and with this understanding, improved multicomponent iterative couplings and glycosyl exchange processes were demonstrated.
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Affiliation(s)
- Joshua L Martin
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
| | - Girish C Sati
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
| | - Tanmay Malakar
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
| | - Jessica Hatt
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
| | - Paul M Zimmerman
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
| | - John Montgomery
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109-1055, United States
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38
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Two-state reactivity in the acetylene cyclotrimerization reaction catalyzed by a single atomic transition-metal ion: The case for V+ and Fe+. COMPUT THEOR CHEM 2022. [DOI: 10.1016/j.comptc.2022.113682] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
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39
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Zhao Q, Hsu HH, Savoie BM. Conformational Sampling for Transition State Searches on a Computational Budget. J Chem Theory Comput 2022; 18:3006-3016. [PMID: 35403426 DOI: 10.1021/acs.jctc.2c00081] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Affiliation(s)
- Qiyuan Zhao
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana 47906, United States
| | - Hsuan-Hao Hsu
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana 47906, United States
| | - Brett M. Savoie
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana 47906, United States
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40
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Jackman KMK, Liang G, Boyle PD, Zimmerman PM, Blacquiere JM. Changes in ligand coordination mode induce bimetallic C-C coupling pathways. Dalton Trans 2022; 51:3977-3991. [PMID: 35174382 PMCID: PMC8937615 DOI: 10.1039/d2dt00322h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Carbon-carbon coupling is one of the most powerful tools in the organic synthesis arsenal. Known methodologies primarily exploit monometallic Pd0/PdII catalytic mechanisms to give new C-C bonds. Bimetallic C-C coupling mechanisms that involve a PdI/PdII redox cycle, remain underexplored. Thus, a detailed mechnaistic understanding is imperative for the development of new bimetallic catalysts. Previously, a PdII-Me dimer (1) supported by L1, which has phosphine and 1-azaallyl donor groups, underwent reductive elimination to give ethane, a PdI dimer, a PdII monometallic complex, and Pd black. Herein, a comprehensive experimental and computational study of the reactivity of 1 is presented, which reveals that the versatile coordination chemistry of L1 promotes bimetallic C-C bond formation. The phosphine 1-azaallyl ligand adopts various bridging modes to maintain the bimetallic structure throughout the C-C bond forming mechanism, which involves intramolecular methyl transfer and 1,1-reductive elimination from one of the palladium atoms. The minor byproduct, methane, likely forms through a monometallic intermediate that is sensitive to solvent C-H activation. Overall, the capacity of L1 to adopt different coordination modes promotes the bimetallic C-C coupling channel through pathways that are unattainable with statically-coordinated ligands.
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Affiliation(s)
- Kyle M K Jackman
- Department of Chemistry, University of Western Ontario, London, Canada, N6A 5B7.
| | - Guangchao Liang
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, USA.
| | - Paul D Boyle
- Department of Chemistry, University of Western Ontario, London, Canada, N6A 5B7.
| | - Paul M Zimmerman
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, USA.
| | - Johanna M Blacquiere
- Department of Chemistry, University of Western Ontario, London, Canada, N6A 5B7.
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41
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Garay-Ruiz D, Álvarez-Moreno M, Bo C, Martínez-Núñez E. New Tools for Taming Complex Reaction Networks: The Unimolecular Decomposition of Indole Revisited. ACS PHYSICAL CHEMISTRY AU 2022; 2:225-236. [PMID: 36855573 PMCID: PMC9718323 DOI: 10.1021/acsphyschemau.1c00051] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The level of detail attained in the computational description of reaction mechanisms can be vastly improved through tools for automated chemical space exploration, particularly for systems of small to medium size. Under this approach, the unimolecular decomposition landscape for indole was explored through the automated reaction mechanism discovery program AutoMeKin. Nevertheless, the sheer complexity of the obtained mechanisms might be a hindrance regarding their chemical interpretation. In this spirit, the new Python library amk-tools has been designed to read and manipulate complex reaction networks, greatly simplifying their overall analysis. The package provides interactive dashboards featuring visualizations of the network, the three-dimensional (3D) molecular structures and vibrational normal modes of all chemical species, and the corresponding energy profiles for selected pathways. The combination of the joined mechanism generation and postprocessing workflow with the rich chemistry of indole decomposition enabled us to find new details of the reaction (obtained at the CCSD(T)/aug-cc-pVTZ//M06-2X/MG3S level of theory) that were not reported before: (i) 16 pathways leading to the formation of HCN and NH3 (via amino radical); (ii) a barrierless reaction between methylene radical and phenyl isocyanide, which might be an operative mechanism under the conditions of the interstellar medium; and (iii) reaction channels leading to both hydrogen cyanide and hydrogen isocyanide, of potential astrochemical interest as the computed HNC/HCN ratios greatly exceed the calculated equilibrium value at very low temperatures. The reported reaction networks can be very valuable to supplement databases of kinetic data, which is of remarkable interest for pyrolysis and astrochemical studies.
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Affiliation(s)
- Diego Garay-Ruiz
- Institute
of Chemical Research of Catalonia (ICIQ), Barcelona Institute of Science & Technology (BIST), Avinguda Països Catalans,
16, 43007 Tarragona, Spain,Departament
de Química Física i Inorgànica, Universitat Rovira i Virgili (URV), Marcel·lí Domingo s/n, 43007 Tarragona, Spain
| | - Moises Álvarez-Moreno
- Institute
of Chemical Research of Catalonia (ICIQ), Barcelona Institute of Science & Technology (BIST), Avinguda Països Catalans,
16, 43007 Tarragona, Spain
| | - Carles Bo
- Institute
of Chemical Research of Catalonia (ICIQ), Barcelona Institute of Science & Technology (BIST), Avinguda Països Catalans,
16, 43007 Tarragona, Spain,Departament
de Química Física i Inorgànica, Universitat Rovira i Virgili (URV), Marcel·lí Domingo s/n, 43007 Tarragona, Spain,
| | - Emilio Martínez-Núñez
- Departmento
de Química Física, Facultade de Química, Universidade de Santiago de Compostela, 15782 Santiago
de Compostela, Spain,
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42
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Baiardi A, Grimmel SA, Steiner M, Türtscher PL, Unsleber JP, Weymuth T, Reiher M. Expansive Quantum Mechanical Exploration of Chemical Reaction Paths. Acc Chem Res 2022; 55:35-43. [PMID: 34918903 DOI: 10.1021/acs.accounts.1c00472] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Quantum mechanical methods have been well-established for the elucidation of reaction paths of chemical processes and for the explicit dynamics of molecular systems. While they are usually deployed in routine manual calculations on reactions for which some insights are already available (typically from experiment), new algorithms and continuously increasing capabilities of modern computer hardware allow for exploratory open-ended computational campaigns that are unbiased and therefore enable unexpected discoveries. Highly efficient and even automated procedures facilitate systematic approaches toward the exploration of uncharted territory in molecular transformations and dynamics. In this work, we elaborate on such explorative approaches that range from reaction network explorations with (stationary) quantum chemical methods to explorative molecular dynamics and migrant wave packet dynamics. The focus is on recent developments that cover the following strategies. (i) Pruning search options for elementary reaction steps by heuristic rules based on the first-principles of quantum mechanics: Rules are required for reducing the combinatorial explosion of potentially reactive atom pairings, and rooting them in concepts derived from the electronic wave function makes them applicable to any molecular system. (ii) Enforcing reactive events by external biases: Inducing a reaction requires constraints that steer and direct elementary-step searches, which can be formulated in terms of forces, velocities, or supplementary potentials. (iii) Manual steering facilitated by interactive quantum mechanics: As ultrafast quantum chemical methods allow for real-time manual interactions with molecular systems, human-intuition-guided paths can be easily explored with suitable human-machine interfaces. (iv) New approaches for transition-state optimization with continuous curve representations can provide stable schemes to be driven in an automated way by allowing for an efficient tuning of the curve's parameters (instead of a manipulation of a collection of structures along the path), and (v) reactive molecular dynamics and direct wave packet propagation exploit the equations of motion of an underlying mechanical theory (usually, classical Newtonian mechanics or Schrödinger quantum mechanics). Explorative approaches are likely to replace the current state of the art in computational chemistry, because they reduce the human effort to be invested in reaction path elucidations, they are less prone to errors and bias-free, and they cover more extensive regions of the relevant configuration space. As a result, computational investigations that rely on these techniques are more likely to deliver surprising discoveries.
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Affiliation(s)
- Alberto Baiardi
- Laboratory of Physical Chemistry, ETH Zurich, Vladimir-Prelog-Weg 2, 8093 Zurich, Switzerland
| | - Stephanie A. Grimmel
- Laboratory of Physical Chemistry, ETH Zurich, Vladimir-Prelog-Weg 2, 8093 Zurich, Switzerland
| | - Miguel Steiner
- Laboratory of Physical Chemistry, ETH Zurich, Vladimir-Prelog-Weg 2, 8093 Zurich, Switzerland
| | - Paul L. Türtscher
- Laboratory of Physical Chemistry, ETH Zurich, Vladimir-Prelog-Weg 2, 8093 Zurich, Switzerland
| | - Jan P. Unsleber
- Laboratory of Physical Chemistry, ETH Zurich, Vladimir-Prelog-Weg 2, 8093 Zurich, Switzerland
| | - Thomas Weymuth
- Laboratory of Physical Chemistry, ETH Zurich, Vladimir-Prelog-Weg 2, 8093 Zurich, Switzerland
| | - Markus Reiher
- Laboratory of Physical Chemistry, ETH Zurich, Vladimir-Prelog-Weg 2, 8093 Zurich, Switzerland
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43
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Computational Analysis of a Prebiotic Amino Acid Synthesis with Reference to Extant Codon-Amino Acid Relationships. Life (Basel) 2021; 11:life11121343. [PMID: 34947874 PMCID: PMC8707928 DOI: 10.3390/life11121343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 11/26/2021] [Accepted: 11/30/2021] [Indexed: 11/28/2022] Open
Abstract
Novel density functional theory calculations are presented regarding a mechanism for prebiotic amino acid synthesis from alpha-keto acids that was suggested to happen via catalysis by dinucleotide species. Our results were analysed with comparison to the original hypothesis (Copley et al., PNAS, 2005, 102, 4442–4447). It was shown that the keto acid–dinucleotide hypothesis for possible prebiotic amino acid synthesis was plausible based on an initial computational analysis, and details of the structures for the intermediates and transition states showed that there was wide scope for interactions between the keto acid and dinucleotide moieties that could affect the free energy profiles and lead to the required proto-metabolic selectivity.
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44
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Wang S, Zhelavskyi O, Lee J, Argüelles AJ, Khomutnyk YY, Mensah E, Guo H, Hourani R, Zimmerman PM, Nagorny P. Studies of Catalyst-Controlled Regioselective Acetalization and Its Application to Single-Pot Synthesis of Differentially Protected Saccharides. J Am Chem Soc 2021; 143:18592-18604. [PMID: 34705439 PMCID: PMC8585716 DOI: 10.1021/jacs.1c08448] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
This article describes studies on the regioselective acetal protection of monosaccharide-based diols using chiral phosphoric acids (CPAs) and their immobilized polymeric variants, (R)-Ad-TRIP-PS and (S)-SPINOL-PS, as the catalysts. These catalyst-controlled regioselective acetalizations were found to proceed with high regioselectivities (up to >25:1 rr) on various d-glucose-, d-galactose-, d-mannose-, and l-fucose-derived 1,2-diols and could be carried out in a regiodivergent fashion depending on the choice of chiral catalyst. The polymeric catalysts were conveniently recycled and reused multiple times for gram-scale functionalizations with catalytic loadings as low as 0.1 mol %, and their performance was often found to be superior to the performance of their monomeric variants. These regioselective CPA-catalyzed acetalizations were successfully combined with common hydroxyl group functionalizations as single-pot telescoped procedures to produce 32 regioisomerically pure differentially protected mono- and disaccharide derivatives. To further demonstrate the utility of the polymeric catalysts, the same batch of (R)-Ad-TRIP-PS catalyst was recycled and reused to accomplish single-pot gram-scale syntheses of 6 differentially protected d-glucose derivatives. The subsequent exploration of the reaction mechanism using NMR studies of deuterated and nondeuterated substrates revealed that low-temperature acetalizations happen via a syn-addition mechanism and that the reaction regioselectivity exhibits strong dependence on the temperature. The computational studies indicate a complex temperature-dependent interplay of two reaction mechanisms, one involving an anomeric phosphate intermediate and another via concerted asynchronous formation of an acetal, that results in syn-addition products. The computational models also explain the steric factors responsible for the observed C2 selectivities and are consistent with experimentally observed selectivity trends.
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Affiliation(s)
- Sibin Wang
- Chemistry Department, University of Michigan, 930 N. University Avenue, Ann Arbor, MI 48109
| | - Oleksii Zhelavskyi
- Chemistry Department, University of Michigan, 930 N. University Avenue, Ann Arbor, MI 48109
| | - Jeonghyo Lee
- Department of Chemistry, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, South Korea
| | - Alonso J. Argüelles
- Synthetic Molecule Design and Development, Lilly Research Laboratories, Eli Lilly and Company, 307 E. Merrill St. Indianapolis, IN 46225
| | | | - Enoch Mensah
- Chemistry Department, Indiana University Southeast, 4201 Grant Line Rd. New Albany, IN 47150
| | - Hao Guo
- Deparment of Chemical and Biomolecular Engineering, Lehigh University, Bethlehem, PA 18015
| | - Rami Hourani
- Chemistry Department, Stanford University, 333 Campus Drive, Stanford, CA 94305-5080
| | - Paul M. Zimmerman
- Chemistry Department, University of Michigan, 930 N. University Avenue, Ann Arbor, MI 48109
| | - Pavel Nagorny
- Chemistry Department, University of Michigan, 930 N. University Avenue, Ann Arbor, MI 48109
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Automated Construction and Optimization Combined with Machine Learning to Generate Pt(II) Methane C–H Activation Transition States. Top Catal 2021. [DOI: 10.1007/s11244-021-01506-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
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46
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Škoch K, Daniliuc CG, Kehr G, Ehlert S, Müller M, Grimme S, Erker G. Frustrated Lewis-Pair Neighbors at the Xanthene Framework: Epimerization at Phosphorus and Cooperative Formation of Macrocyclic Adduct Structures. Chemistry 2021; 27:12104-12114. [PMID: 34076908 DOI: 10.1002/chem.202100835] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Indexed: 11/07/2022]
Abstract
Attachment of a pair of P-stereogenic mesityl(alkynyl)phosphanyl groups at the 4- and 5-positions of a 9,9-dimethylxanthene framework gave mixtures of the respective rac- and meso-bisphosphanyl diastereoisomers. They slowly epimerized in a thermally induced reaction with Gibbs activation barriers of about 25 kcal mol-1 at room temperature (measured and DFT calculated). The reaction of the meso-mesityl(tert-butylethynyl)phosphanyl derivative with two molar equivalents of Piers' borane [HB(C6 F5 )2 ] led to the formation of the alkylidene-bridged geminal bisphosphane/borane-frustrated Lewis pair system. The compound was obtained enriched (>85 %) in the rac diastereoisomer. With a variety of bifunctional donor substrates, the rac-bis-P/B FLP formed macrocyclic compounds. They were all formally derived from meso-configurated diastereoisomers of the bisphosphanylxanthene backbone.
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Affiliation(s)
- Karel Škoch
- Organisch-Chemisches Institut, Westfälische Wilhelms-Universität Münster, Corrensstraβe 40, 48149, Münster, Germany
| | - Constantin G Daniliuc
- Organisch-Chemisches Institut, Westfälische Wilhelms-Universität Münster, Corrensstraβe 40, 48149, Münster, Germany
| | - Gerald Kehr
- Organisch-Chemisches Institut, Westfälische Wilhelms-Universität Münster, Corrensstraβe 40, 48149, Münster, Germany
| | - Sebastian Ehlert
- Mulliken Center for Theoretical Chemistry Institut für Physikalische und Theoretische Chemie, Universität Bonn, Beringstraβe 4, 53115, Bonn, Germany
| | - Marcel Müller
- Mulliken Center for Theoretical Chemistry Institut für Physikalische und Theoretische Chemie, Universität Bonn, Beringstraβe 4, 53115, Bonn, Germany
| | - Stefan Grimme
- Mulliken Center for Theoretical Chemistry Institut für Physikalische und Theoretische Chemie, Universität Bonn, Beringstraβe 4, 53115, Bonn, Germany
| | - Gerhard Erker
- Organisch-Chemisches Institut, Westfälische Wilhelms-Universität Münster, Corrensstraβe 40, 48149, Münster, Germany
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Martínez-Núñez E, Barnes GL, Glowacki DR, Kopec S, Peláez D, Rodríguez A, Rodríguez-Fernández R, Shannon RJ, Stewart JJP, Tahoces PG, Vazquez SA. AutoMeKin2021: An open-source program for automated reaction discovery. J Comput Chem 2021; 42:2036-2048. [PMID: 34387374 DOI: 10.1002/jcc.26734] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 07/16/2021] [Accepted: 07/27/2021] [Indexed: 01/10/2023]
Abstract
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.
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Affiliation(s)
- Emilio Martínez-Núñez
- Department of Physical Chemistry, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - George L Barnes
- Department of Chemistry and Biochemistry, Siena College, Loudonville, New York, USA
| | - David R Glowacki
- Centre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol, UK
| | - Sabine Kopec
- Institut de Sciences Moléculaires d'Orsay, UMR 8214, Université Paris-Sud - Université Paris-Saclay, Orsay, France
| | - Daniel Peláez
- Institut de Sciences Moléculaires d'Orsay, UMR 8214, Université Paris-Sud - Université Paris-Saclay, Orsay, France
| | - Aurelio Rodríguez
- Galicia Supercomputing Center (CESGA), Santiago de Compostela, Spain
| | | | - Robin J Shannon
- Centre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol, UK
| | | | - Pablo G Tahoces
- Department of Electronics and Computer Science, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Saulo A Vazquez
- Department of Physical Chemistry, University of Santiago de Compostela, Santiago de Compostela, Spain
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48
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Shannon RJ, Martínez-Núñez E, Shalashilin DV, Glowacki DR. ChemDyME: Kinetically Steered, Automated Mechanism Generation through Combined Molecular Dynamics and Master Equation Calculations. J Chem Theory Comput 2021; 17:4901-4912. [PMID: 34283599 DOI: 10.1021/acs.jctc.1c00335] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
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.
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Affiliation(s)
- Robin J Shannon
- School of Chemistry, University of Bristol, Bristol BS8 1TS, U.K
| | - Emilio Martínez-Núñez
- Department of Physical Chemistry, University of Santiago de Compostela, Santiago de Compostela 15705, Spain
| | | | - David R Glowacki
- ArtSci International Foundation, 5th floor Mariner House, Bristol BS1 4QD, U.K
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49
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Ásgeirsson V, Birgisson BO, Bjornsson R, Becker U, Neese F, Riplinger C, Jónsson H. Nudged Elastic Band Method for Molecular Reactions Using Energy-Weighted Springs Combined with Eigenvector Following. J Chem Theory Comput 2021; 17:4929-4945. [PMID: 34275279 DOI: 10.1021/acs.jctc.1c00462] [Citation(s) in RCA: 93] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The climbing image nudged elastic band method (CI-NEB) is used to identify reaction coordinates and to find saddle points representing transition states of reactions. It can make efficient use of parallel computing as the calculations of the discretization points, the so-called images, can be carried out simultaneously. In typical implementations, the images are distributed evenly along the path by connecting adjacent images with equally stiff springs. However, for systems with a high degree of flexibility, this can lead to poor resolution near the saddle point. By making the spring constants increase with energy, the resolution near the saddle point is improved. To assess the performance of this energy-weighted CI-NEB method, calculations are carried out for a benchmark set of 121 molecular reactions. The performance of the method is analyzed with respect to the input parameters. Energy-weighted springs are found to greatly improve performance and result in successful location of the saddle points in less than a thousand energy and force evaluations on average (about a hundred per image) using the same set of parameter values for all of the reactions. Even better performance is obtained by stopping the calculation before full convergence and complete the saddle point search using an eigenvector following method starting from the location of the climbing image. This combination of methods, referred to as NEB-TS, turns out to be robust and highly efficient as it reduces the average number of energy and force evaluations down to a third, to 305. An efficient and flexible implementation of these methods has been made available in the ORCA software.
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Affiliation(s)
- Vilhjálmur Ásgeirsson
- Science Institute and Faculty of Physical Sciences, University of Iceland, VR-III, 107 Reykjavík, Iceland
| | - Benedikt Orri Birgisson
- Science Institute and Faculty of Physical Sciences, University of Iceland, VR-III, 107 Reykjavík, Iceland
| | - Ragnar Bjornsson
- Max-Planck-Institute for Chemical Energy Conversion, Mülheim an der Ruhr 45470, Germany
| | - Ute Becker
- Max-Planck-Institute for Kohlenforschung, Mülheim an der Ruhr 45470, Germany
| | - Frank Neese
- Max-Planck-Institute for Kohlenforschung, Mülheim an der Ruhr 45470, Germany
| | | | - Hannes Jónsson
- Science Institute and Faculty of Physical Sciences, University of Iceland, VR-III, 107 Reykjavík, Iceland
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50
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Zhao Q, Savoie BM. Simultaneously improving reaction coverage and computational cost in automated reaction prediction tasks. NATURE COMPUTATIONAL SCIENCE 2021; 1:479-490. [PMID: 38217124 DOI: 10.1038/s43588-021-00101-3] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Accepted: 06/18/2021] [Indexed: 01/15/2024]
Abstract
Automated reaction prediction has the potential to elucidate complex reaction networks for applications ranging from combustion to materials degradation, but computational cost and inconsistent reaction coverage are still obstacles to exploring deep reaction networks. Here we show that cost can be reduced and reaction coverage can be increased simultaneously by relatively straightforward modifications of the reaction enumeration, geometry initialization and transition state convergence algorithms that are common to many prediction methodologies. These components are implemented in the context of yet another reaction program (YARP), our reaction prediction package with which we report reaction discovery benchmarks for organic single-step reactions, thermal degradation of a γ-ketohydroperoxide, and competing ring-closures in a large organic molecule. Compared with recent benchmarks, YARP (re)discovers both established and unreported reaction pathways and products while simultaneously reducing the cost of reaction characterization by nearly 100-fold and increasing convergence of transition states. This combination of ultra-low cost and high reaction coverage creates opportunities to explore the reactivity of larger systems and more complex reaction networks for applications such as chemical degradation, where computational cost is a bottleneck.
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Affiliation(s)
- Qiyuan Zhao
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN, USA
| | - Brett M Savoie
- Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN, USA.
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