1
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Dommer AC, Rogers MM, Carter-Fenk KA, Wauer NA, Rubio P, Davasam A, Allen HC, Amaro RE. Interfacial Enrichment of Lauric Acid Assisted by Long-Chain Fatty Acids, Acidity and Salinity at Sea Spray Aerosol Surfaces. J Phys Chem A 2024; 128:7195-7207. [PMID: 39106367 PMCID: PMC11372753 DOI: 10.1021/acs.jpca.4c03335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/09/2024]
Abstract
Surfactant monolayers at sea spray aerosol (SSA) surfaces regulate various atmospheric processes including gas transfer, cloud interactions, and radiative properties. Most experimental studies of SSA employ a simplified surfactant mixture of long-chain fatty acids (LCFAs) as a proxy for the sea surface microlayer or SSA surface. However, medium-chain fatty acids (MCFAs) make up nearly 30% of the FA fraction in nascent SSA. Given that LCFA monolayers are easily disrupted upon the introduction of chemical heterogeneity (such as mixed chain lengths), simple FA proxies are unlikely to represent realistic SSA interfaces. Integrating experimental and computational techniques, we characterize the impact that partially soluble MCFAs have on the properties of atmospherically relevant LCFA mixtures. We explore the extent to which the MCFA lauric acid (LA) is surface stabilized by varying acidity, salinity, and monolayer composition. We also discuss the impacts of pH on LCFA-assisted LA retention, where the presence of LCFAs may shift the surface-adsorption equilibria of laurate─the conjugate base─toward higher surface activities. Molecular dynamic simulations suggest a mechanism for the enhanced surface retention of laurate. We conclude that increased FA heterogeneity at SSA surfaces promotes surface activity of soluble FA species, altering monolayer phase behavior and impacting climate-relevant atmospheric processes.
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Affiliation(s)
- Abigail C Dommer
- Department of Molecular Biology, University of California, San Diego, La Jolla, California 92093, United States
| | - Mickey M Rogers
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Kimberly A Carter-Fenk
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
| | - Nicholas A Wauer
- Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California 92093, United States
| | - Patiemma Rubio
- Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California 92093, United States
| | - Aakash Davasam
- Department of Molecular Biology, University of California, San Diego, La Jolla, California 92093, United States
- Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California 92093, United States
| | - Heather C Allen
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
| | - Rommie E Amaro
- Department of Molecular Biology, University of California, San Diego, La Jolla, California 92093, United States
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2
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Aboulfath Y, Bougueroua S, Cimas A, Barth D, Gaigeot MP. Time-Resolved Graphs of Polymorphic Cycles for H-Bonded Network Identification in Flexible Biomolecules. J Chem Theory Comput 2024; 20:1019-1035. [PMID: 38236138 DOI: 10.1021/acs.jctc.3c01031] [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: 01/19/2024]
Abstract
A novel approach based on a coarse-grained representation of topological graphs is proposed for the automatic analysis of molecular dynamics (MD) trajectories of hydrogen-bonded (H-Bonded) flexible biomolecules. Herein, our approach models an H-Bonded biomolecule by its H-Bonded cycles and its graph of cycles in which the vertices and links represent the intersections between these cycles. We propose a methodology in which each identified conformer/isomer from the MD is represented by a well-chosen set of H-Bonded cycles called a minimum cycle basis. The key component is the "polycycles" that distinguish the cycles that play the same polymorphic role in the molecule from the ones that lead to an actual conformational change of the molecule. The relevance of our proposed method is evaluated on MD trajectories of gas-phase biomolecules, for which the covalent bonds are unchanged over time and only the hydrogen bonds change over time. The polygraphs and their time evolution are shown to reveal the dynamicity of the metastructure(s) of the H-Bonded biomolecules while providing polymorphic information on the cycles. Such information on the dynamics and changes in the H-bond network, as some cycles change identity while retaining the same role in the overall structure, is not easily captured at the atomic level of representation. Such information can instead be captured by polymorphic cycles.
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Affiliation(s)
- Ylène Aboulfath
- Université Paris-Saclay, Univ Versailles Saint Quentin, DAVID, 78035 Versailles, France
| | - Sana Bougueroua
- Université Paris-Saclay, Univ Evry, CY Cergy Paris Université, CNRS, LAMBE, 91025 Evry-Courcouronnes, France
| | - Alvaro Cimas
- Université Paris-Saclay, Univ Evry, CY Cergy Paris Université, CNRS, LAMBE, 91025 Evry-Courcouronnes, France
| | - Dominique Barth
- Université Paris-Saclay, Univ Versailles Saint Quentin, DAVID, 78035 Versailles, France
| | - Marie-Pierre Gaigeot
- Université Paris-Saclay, Univ Evry, CY Cergy Paris Université, CNRS, LAMBE, 91025 Evry-Courcouronnes, France
- Institut Universitaire de France (IUF), 75005 Paris, France
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3
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Hashemi A, Bougueroua S, Gaigeot MP, Pidko EA. HiREX: High-Throughput Reactivity Exploration for Extended Databases of Transition-Metal Catalysts. J Chem Inf Model 2023; 63:6081-6094. [PMID: 37738303 PMCID: PMC10565810 DOI: 10.1021/acs.jcim.3c00660] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Indexed: 09/24/2023]
Abstract
A method is introduced for the automated analysis of reactivity exploration for extended in silico databases of transition-metal catalysts. The proposed workflow is designed to tackle two key challenges for bias-free mechanistic explorations on large databases of catalysts: (1) automated exploration of the chemical space around each catalyst with unique structural and chemical features and (2) automated analysis of the resulting large chemical data sets. To address these challenges, we have extended the application of our previously developed ReNeGate method for bias-free reactivity exploration and implemented an automated analysis procedure to identify the classes of reactivity patterns within specific catalyst groups. Our procedure applied to an extended series of representative Mn(I) pincer complexes revealed correlations between structural and reactive features, pointing to new channels for catalyst transformation under the reaction conditions. Such an automated high-throughput virtual screening of systematically generated hypothetical catalyst data sets opens new opportunities for the design of high-performance catalysts as well as an accelerated method for expert bias-free high-throughput in silico reactivity exploration.
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Affiliation(s)
- Ali Hashemi
- Inorganic
Systems Engineering, Department of Chemical Engineering, Faculty of
Applied Sciences, Delft University of Technology, Van der Maasweg 9, Delft 2629 HZ, The Netherlands
| | - Sana Bougueroua
- Laboratoire
Analyse et Modélisation pour la Biologie et l’Environnement
(LAMBE) UMR8587, Paris-Saclay, Univ Evry,
CY Cergy Paris Université, CNRS, LAMBE UMR8587, Evry-Courcouronnes 91025, France
| | - Marie-Pierre Gaigeot
- Laboratoire
Analyse et Modélisation pour la Biologie et l’Environnement
(LAMBE) UMR8587, Paris-Saclay, Univ Evry,
CY Cergy Paris Université, CNRS, LAMBE UMR8587, Evry-Courcouronnes 91025, France
| | - Evgeny A. Pidko
- Inorganic
Systems Engineering, Department of Chemical Engineering, Faculty of
Applied Sciences, Delft University of Technology, Van der Maasweg 9, Delft 2629 HZ, The Netherlands
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4
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Bougueroua S, Bricage M, Aboulfath Y, Barth D, Gaigeot MP. Algorithmic Graph Theory, Reinforcement Learning and Game Theory in MD Simulations: From 3D Structures to Topological 2D-Molecular Graphs (2D-MolGraphs) and Vice Versa. Molecules 2023; 28:molecules28072892. [PMID: 37049654 PMCID: PMC10096312 DOI: 10.3390/molecules28072892] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 03/17/2023] [Accepted: 03/18/2023] [Indexed: 04/14/2023] Open
Abstract
This paper reviews graph-theory-based methods that were recently developed in our group for post-processing molecular dynamics trajectories. We show that the use of algorithmic graph theory not only provides a direct and fast methodology to identify conformers sampled over time but also allows to follow the interconversions between the conformers through graphs of transitions in time. Examples of gas phase molecules and inhomogeneous aqueous solid interfaces are presented to demonstrate the power of topological 2D graphs and their versatility for post-processing molecular dynamics trajectories. An even more complex challenge is to predict 3D structures from topological 2D graphs. Our first attempts to tackle such a challenge are presented with the development of game theory and reinforcement learning methods for predicting the 3D structure of a gas-phase peptide.
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Affiliation(s)
- Sana Bougueroua
- Université Paris-Saclay, University Evry, CY Cergy Paris Université, CNRS, LAMBE UMR8587, 91025 Evry-Courcouronnes, France
| | - Marie Bricage
- Université Paris-Saclay, University Versailles Saint Quentin, DAVID, 78000 Versailles, France
| | - Ylène Aboulfath
- Université Paris-Saclay, University Versailles Saint Quentin, DAVID, 78000 Versailles, France
| | - Dominique Barth
- Université Paris-Saclay, University Versailles Saint Quentin, DAVID, 78000 Versailles, France
| | - Marie-Pierre Gaigeot
- Université Paris-Saclay, University Evry, CY Cergy Paris Université, CNRS, LAMBE UMR8587, 91025 Evry-Courcouronnes, France
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5
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Bougueroua S, Aboulfath Y, Barth D, Gaigeot MP. Algorithmic graph theory for post-processing molecular dynamics trajectories. Mol Phys 2023. [DOI: 10.1080/00268976.2022.2162456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Affiliation(s)
- Sana Bougueroua
- Université Paris-Saclay, Univ Evry, CNRS, LAMBE UMR8587, Evry-Courcouronnes, France
| | - Ylène Aboulfath
- Université Paris-Saclay, Univ Versailles SQ, DAVID, Versailles, France
| | - Dominique Barth
- Université Paris-Saclay, Univ Versailles SQ, DAVID, Versailles, France
| | - Marie-Pierre Gaigeot
- Université Paris-Saclay, Univ Evry, CNRS, LAMBE UMR8587, Evry-Courcouronnes, France
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6
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Hashemi A, Bougueroua S, Gaigeot MP, Pidko EA. ReNeGate: A Reaction Network Graph-Theoretical Tool for Automated Mechanistic Studies in Computational Homogeneous Catalysis. J Chem Theory Comput 2022; 18:7470-7482. [PMID: 36321652 DOI: 10.1021/acs.jctc.2c00404] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Exploration of the chemical reaction space of chemical transformations in multicomponent mixtures is one of the main challenges in contemporary computational chemistry. To remove expert bias from mechanistic studies and to discover new chemistries, an automated graph-theoretical methodology is proposed, which puts forward a network formalism of homogeneous catalysis reactions and utilizes a network analysis tool for mechanistic studies. The method can be used for analyzing trajectories with single and multiple catalytic species and can provide unique conformers of catalysts including multinuclear catalyst clusters along with other catalytic mixture components. The presented three-step approach has the integrated ability to handle multicomponent catalytic systems of arbitrary complexity (mixtures of reactants, catalyst precursors, ligands, additives, and solvents). It is not limited to predefined chemical rules, does not require prealignment of reaction mixture components consistent with a reaction coordinate, and is not agnostic to the chemical nature of transformations. Conformer exploration, reactive event identification, and reaction network analysis are the main steps taken for identifying the pathways in catalytic systems given the starting precatalytic reaction mixture as the input. Such a methodology allows us to efficiently explore catalytic systems in realistic conditions for either previously observed or completely unknown reactive events in the context of a network representing different intermediates. Our workflow for the catalytic reaction space exploration exclusively focuses on the identification of thermodynamically feasible conversion channels, representative of the (secondary) catalyst deactivation or inhibition paths, which are usually most difficult to anticipate based solely on expert chemical knowledge. Thus, the expert bias is sought to be removed at all steps, and the chemical intuition is limited to the choice of the thermodynamic constraint imposed by the applicable experimental conditions in terms of threshold energy values for allowed transformations. The capabilities of the proposed methodology have been tested by exploring the reactivity of Mn complexes relevant for catalytic hydrogenation chemistry to verify previously postulated activation mechanisms and unravel unexpected reaction channels relevant to rare deactivation events.
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Affiliation(s)
- Ali Hashemi
- Inorganic Systems Engineering, Department of Chemical Engineering, Faculty of Applied Sciences, Delft University of Technology, Van der Maasweg 9, Delft 2629 HZ, The Netherlands
| | - Sana Bougueroua
- Laboratoire Analyse et Modélisation pour la Biologie et l'Environnement (LAMBE) UMR8587, Universite Paris-Saclay, Univ Evry, CNRS, LAMBE UMR8587, Evry-Courcouronnes 91025, France
| | - Marie-Pierre Gaigeot
- Laboratoire Analyse et Modélisation pour la Biologie et l'Environnement (LAMBE) UMR8587, Universite Paris-Saclay, Univ Evry, CNRS, LAMBE UMR8587, Evry-Courcouronnes 91025, France
| | - Evgeny A Pidko
- Inorganic Systems Engineering, Department of Chemical Engineering, Faculty of Applied Sciences, Delft University of Technology, Van der Maasweg 9, Delft 2629 HZ, The Netherlands
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7
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Seo J, Choi S, Singh R, Choi JH. Spatial Inhomogeneity and Molecular Aggregation behavior in Aqueous Binary Liquid Mixtures. J Mol Liq 2022. [DOI: 10.1016/j.molliq.2022.120949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022]
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8
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Gaigeot MP. Some opinions on MD-based vibrational spectroscopy of gas phase molecules and their assembly: An overview of what has been achieved and where to go. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2021; 260:119864. [PMID: 34052762 DOI: 10.1016/j.saa.2021.119864] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Revised: 04/13/2021] [Accepted: 04/18/2021] [Indexed: 06/12/2023]
Abstract
We hereby review molecular dynamics simulations for anharmonic gas phase spectroscopy and provide some of our opinions of where the field is heading. With these new directions, the theoretical IR/Raman spectroscopy of large (bio)-molecular systems will be more easily achievable over longer time-scale MD trajectories for an increase in accuracy of the MD-IR and MD-Raman calculated spectra. With the new directions presented here, the high throughput 'decoding' of experimental IR/Raman spectra into 3D-structures should thus be possible, hence advancing e.g. the field of MS-IR for structural characterization by spectroscopy. We also review the assignment of vibrational spectra in terms of anharmonic molecular modes from the MD trajectories, and especially introduce our recent developments based on Graph Theory algorithms. Graph Theory algorithmic is also introduced in this review for the identification of the molecular 3D-structures sampled over MD trajectories.
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Affiliation(s)
- Marie-Pierre Gaigeot
- Université Paris-Saclay, Univ Evry, CNRS, LAMBE UMR8587, 91025 Evry-Courcouronnes, France.
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9
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Perez-Mellor AF, Spezia R. Determination of kinetic properties in unimolecular dissociation of complex systems from graph theory based analysis of an ensemble of reactive trajectories. J Chem Phys 2021; 155:124103. [PMID: 34598552 DOI: 10.1063/5.0058382] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
In this paper, we report how graph theory can be used to analyze an ensemble of independent molecular trajectories, which can react during the simulation time-length, and obtain structural and kinetic information. This method is totally general and here is applied to the prototypical case of gas phase fragmentation of protonated cyclo-di-glycine. This methodology allows us to analyze the whole set of trajectories in an automatic computer-based way without the need of visual inspection but by getting all the needed information. In particular, we not only determine the appearance of different products and intermediates but also characterize the corresponding kinetics. The use of colored graph and canonical labeling allows for the correct characterization of the chemical species involved. In the present case, the simulations consist of an ensemble of unimolecular fragmentation trajectories at constant energy such that from the rate constants at different energies, the threshold energy can also be obtained for both global and specific pathways. This approach allows for the characterization of ion-molecule complexes, likely through a roaming mechanism, by properly taking into account the elusive nature of such species. Finally, it is possible to directly obtain the theoretical mass spectrum of the fragmenting species if the reacting system is an ion as in the specific example.
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Affiliation(s)
- Ariel F Perez-Mellor
- LAMBE UMR8587, Université d'Evry Val d'Essonne, CNRS, CEA, Université Paris-Saclay, Laboratoire Analyse et Modélisation pour la Biologie et l'Environnement, 91025 Evry, France
| | - Riccardo Spezia
- Laboratoire de Chimie Théorique, Sorbonne Université and CNRS, F-75005 Paris, France
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10
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Enders AA, North NM, Fensore CM, Velez-Alvarez J, Allen HC. Functional Group Identification for FTIR Spectra Using Image-Based Machine Learning Models. Anal Chem 2021; 93:9711-9718. [PMID: 34190551 DOI: 10.1021/acs.analchem.1c00867] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Fourier transform infrared spectroscopy (FTIR) is a ubiquitous spectroscopic technique. Spectral interpretation is a time-consuming process, but it yields important information about functional groups present in compounds and in complex substances. We develop a generalizable model via a machine learning (ML) algorithm using convolutional neural networks (CNNs) to identify the presence of functional groups in gas-phase FTIR spectra. The ML models reduce the amount of time required to analyze functional groups and facilitate interpretation of FTIR spectra. Through web scraping, we acquire intensity-frequency data from 8728 gas-phase organic molecules within the NIST spectral database and transform the data into spectral images. We successfully train models for 15 of the most common organic functional groups, which we then determine via identification from previously untrained spectra. These models serve to expand the application of FTIR measurements for facile analysis of organic samples. Our approach was done such that we have broad functional group models that infer in tandem to provide full interpretation of a spectrum. We present the first implementation of ML using image-based CNNs for predicting functional groups from a spectroscopic method.
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Affiliation(s)
- Abigail A Enders
- Department of Chemistry & Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
| | - Nicole M North
- Department of Chemistry & Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
| | - Chase M Fensore
- Department of Chemistry & Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
| | - Juan Velez-Alvarez
- Department of Chemistry & Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
| | - Heather C Allen
- Department of Chemistry & Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
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11
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Carrà A, Spezia R. In Silico
Tandem Mass Spectrometer: an Analytical and Fundamental Tool. ACTA ACUST UNITED AC 2021. [DOI: 10.1002/cmtd.202000071] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Affiliation(s)
- Andrea Carrà
- Agilent Technologies Italia Via Piero Gobetti 2/C 20063 Cernusco SN, Milano Italy
| | - Riccardo Spezia
- Laboratoire de Chimie Théorique Sorbonne Université, UMR 7616 CNRS 4, Place Jussieu 75005 Paris France
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12
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Yin S, Zhang B, Yang Y, Huang Y, Shen HB. Clustering Enhancement of Noisy Cryo-Electron Microscopy Single-Particle Images with a Network Structural Similarity Metric. J Chem Inf Model 2019; 59:1658-1667. [DOI: 10.1021/acs.jcim.8b00853] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Affiliation(s)
- Shuo Yin
- Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, and Key
Laboratory of System Control and Information Processing, Ministry
of Education of China, Shanghai 200240, China
| | - Biao Zhang
- Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, and Key
Laboratory of System Control and Information Processing, Ministry
of Education of China, Shanghai 200240, China
| | - Yang Yang
- Department of Computer Science, Shanghai Jiao Tong University, and Key Laboratory
of Shanghai Education Commission for Intelligent Interaction and Cognitive
Engineering, Shanghai 200240, China
| | - Yan Huang
- State Key Laboratory of Infrared Physics Shanghai Institute of Technical Physics, Chinese Academy of Sciences, 500 Yutian Road, Shanghai 200083, China
| | - Hong-Bin Shen
- Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, and Key
Laboratory of System Control and Information Processing, Ministry
of Education of China, Shanghai 200240, China
- Department of Computer Science, Shanghai Jiao Tong University, and Key Laboratory
of Shanghai Education Commission for Intelligent Interaction and Cognitive
Engineering, Shanghai 200240, China
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13
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Galimberti DR, Bougueroua S, Mahé J, Tommasini M, Rijs AM, Gaigeot MP. Conformational assignment of gas phase peptides and their H-bonded complexes using far-IR/THz: IR-UV ion dip experiment, DFT-MD spectroscopy, and graph theory for mode assignment. Faraday Discuss 2019; 217:67-97. [DOI: 10.1039/c8fd00211h] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Graph theory based vibrational modes as new entities for vibrational THz spectroscopy.
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Affiliation(s)
| | | | - Jérôme Mahé
- LAMBE UMR8587
- Univ Evry
- Université Paris-Saclay
- CNRS
- 91025 Evry
| | - Matteo Tommasini
- Department of Chemistry, Materials, Chemical Engineering “G. Natta” Politecnico di Milano
- 20133 Milano
- Italy
| | - Anouk M. Rijs
- Radboud University
- Institute for Molecules and Materials
- FELIX Laboratory
- 6525 ED Nijmegen
- The Netherlands
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14
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A Trajectory-Based Method to Explore Reaction Mechanisms. Molecules 2018; 23:molecules23123156. [PMID: 30513663 PMCID: PMC6321347 DOI: 10.3390/molecules23123156] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2018] [Revised: 11/23/2018] [Accepted: 11/29/2018] [Indexed: 12/02/2022] Open
Abstract
The tsscds method, recently developed in our group, discovers chemical reaction mechanisms with minimal human intervention. It employs accelerated molecular dynamics, spectral graph theory, statistical rate theory and stochastic simulations to uncover chemical reaction paths and to solve the kinetics at the experimental conditions. In the present review, its application to solve mechanistic/kinetics problems in different research areas will be presented. Examples will be given of reactions involved in photodissociation dynamics, mass spectrometry, combustion chemistry and organometallic catalysis. Some planned improvements will also be described.
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