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Nakata H, Fedorov DG. Analytic Gradient for Time-Dependent Density Functional Theory Combined with the Fragment Molecular Orbital Method. J Chem Theory Comput 2023; 19:1276-1285. [PMID: 36753486 DOI: 10.1021/acs.jctc.2c01177] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2023]
Abstract
The analytic energy gradient of energy with respect to nuclear coordinates is derived for the fragment molecular orbital (FMO) method combined with time-dependent density functional theory (TDDFT). The response terms arising from the use of a polarizable embedding are derived. The obtained analytic FMO-TDDFT gradient is shown to be accurate in comparison to both numerical FMO-TDDFT and unfragmented TDDFT gradients, at the level of two- and three-body expansions. The gradients are used for geometry optimizations, molecular dynamics, vibrational calculations, and simulations of IR and Raman spectra of excited states. The developed method is used to optimize the geometry of the ground and excited electronic states of the photoactive yellow protein (PDB: 2PHY).
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Affiliation(s)
- Hiroya Nakata
- Department of Chemistry, Kyungpook National University, Daegu 41566, South Korea
| | - Dmitri G Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST), Central 2, Umezono 1-1-1, Tsukuba 305-8568, Japan
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2
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Fedorov DG. Parametrized quantum-mechanical approaches combined with the fragment molecular orbital method. J Chem Phys 2022; 157:231001. [PMID: 36550057 DOI: 10.1063/5.0131256] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022] Open
Abstract
Fast parameterized methods such as density-functional tight-binding (DFTB) facilitate realistic calculations of large molecular systems, which can be accelerated by the fragment molecular orbital (FMO) method. Fragmentation facilitates interaction analyses between functional parts of molecular systems. In addition to DFTB, other parameterized methods combined with FMO are also described. Applications of FMO methods to biochemical and inorganic systems are reviewed.
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Affiliation(s)
- Dmitri G Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST), Central 2, Umezono 1-1-1, Tsukuba 305-8568, Japan
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3
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Liu W, Wang Z, Chen Z, Luo J, Li S, Wang L. Algorithm advances and applications of time‐dependent first‐principles simulations for ultrafast dynamics. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2022. [DOI: 10.1002/wcms.1577] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- Wen‐Hao Liu
- State Key Laboratory of Superlattices and Microstructures, Institute of Semiconductors Chinese Academy of Sciences Beijing China
- Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing China
| | - Zhi Wang
- State Key Laboratory of Superlattices and Microstructures, Institute of Semiconductors Chinese Academy of Sciences Beijing China
| | - Zhang‐Hui Chen
- Materials Science Division Lawrence Berkeley National Laboratory Berkeley California USA
| | - Jun‐Wei Luo
- State Key Laboratory of Superlattices and Microstructures, Institute of Semiconductors Chinese Academy of Sciences Beijing China
- Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing China
- Beijing Academy of Quantum Information Sciences Beijing China
| | - Shu‐Shen Li
- State Key Laboratory of Superlattices and Microstructures, Institute of Semiconductors Chinese Academy of Sciences Beijing China
- Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing China
- Beijing Academy of Quantum Information Sciences Beijing China
| | - Lin‐Wang Wang
- Materials Science Division Lawrence Berkeley National Laboratory Berkeley California USA
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4
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Harville T, Gordon MS. Electronic Structure Theory Calculations Using Modern Architectures: KNL vs Haswell. J Chem Theory Comput 2021; 17:6910-6917. [PMID: 34699218 DOI: 10.1021/acs.jctc.1c00705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The time to solution and parallel efficiency of several commonly used electronic structure methods (Hartree-Fock, density functional theory, second order perturbation theory, resolution of the identity second order perturbation theory, coupled cluster) are evaluated on both the Intel Xeon Haswell and the Intel Xeon Phi Knights Landing (KNL) architectures. The Haswell completes the benchmark calculations with a faster time to solution than the KNL for all molecules and methods tested. While the Haswell exhibits an average speedup of at least 3.5 relative to the KNL for all nonthreaded computations, the KNL has a better parallel efficiency than the Haswell with increasing core counts. The architectures are further tested using a more computationally costly coupled cluster method on a transition state reaction. The Haswell appears to be the best choice to minimize the time to solution, though for very large systems and high levels of theory that require memory intensive processes the superior memory hierarchy and larger on node memory of the KNL can make it a better choice. These results are used to showcase aspects of novel architectures that will increase efficiency for quantum chemistry applications.
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Affiliation(s)
- Taylor Harville
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, United States
| | - Mark S Gordon
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, United States
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5
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Liang Q, Yang J. Third-Order Many-Body Expansion of OSV-MP2 Wave Function for Low-Order Scaling Analytical Gradient Computation. J Chem Theory Comput 2021; 17:6841-6860. [PMID: 34704757 DOI: 10.1021/acs.jctc.1c00581] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
We present a many-body expansion (MBE) formulation and implementation for efficient computation of analytical energy gradients from the orbital-specific-virtual second-order Møllet-Plesset perturbation theory (OSV-MP2) based on our earlier work (Zhou et al. J. Chem. Theory Comput. 2020, 16, 196-210). The third-order MBE(3) expansion of OSV-MP2 amplitudes and density matrices was developed to adopt the orbital-specific clustering and long-range termination schemes, which avoids term-by-term differentiations of the MBE energy bodies. We achieve better efficiency by exploiting the algorithmic sparsity that allows us to prune out insignificant fitting integrals and OSV relaxations. With these approximations, the present implementation is benchmarked on a range of molecules that show an economic scaling in the linear and quadratic regimes for computing MBE(3)-OSV-MP2 amplitude and gradient equations, respectively, and yields normal accuracy comparable to the original OSV-MP2 results. The MPI-3-based parallelism through shared memory one-sided communication is further developed for improving parallel scalability and memory accessibility by sorting the MBE(3) orbital clusters into independent tasks that are distributed on multiple processes across many nodes, supporting both global and local data locations in which selected MBE(3)-OSV-MP2 intermediates of different sizes are distinguished and accordingly placed. The accuracy and efficiency level of our MBE(3)-OSV-MP2 analytical gradient implementation is finally illustrated in two applications: we show that the subtle coordination structure differences of mechanically interlocked Cu-catenane complexes can be distinguished when tuning ligand lengths; and the porphycene molecular dynamics reveals the emergence of the vibrational signature arising from softened N-H stretching associated with hydrogen transfer, using an MP2 level of electron correlation and classical nuclei for the first time.
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Affiliation(s)
- Qiujiang Liang
- Department of Chemistry, The University of Hong Kong, Hong Kong SAR, P. R. China
| | - Jun Yang
- Department of Chemistry, The University of Hong Kong, Hong Kong SAR, P. R. China
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6
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Hisama K, Orimoto Y, Pomogaeva A, Nakatani K, Aoki Y. Ab initio multi-level layered elongation method and its application to local interaction analysis between DNA bulge and ligand molecules. J Chem Phys 2021; 155:044110. [PMID: 34340364 DOI: 10.1063/5.0050096] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
A multi-level layered elongation method was developed for efficiently analyzing the electronic states of local structures in large bio/nano-systems at the full ab initio level of theory. The original elongation method developed during the last three decades in our group has focused on the system in one direction from one terminal to the other terminal to sequentially construct the electronic states of a polymer, called a theoretical synthesis of polymers. In this study, an important region termed the central (C) part is targeted in a large polymer and the remainder are terminal (T) parts. The electronic structures along with polymer elongation are calculated repeatedly from both end T parts to the C central part at the same time. The important C part is treated with large basis sets (high level) and the other regions are treated with small basis sets (low level) in the ab initio theoretical framework. The electronic structures besides the C part can be reused for other systems with different structures at the C part, which renders the method computationally efficient. This multi-level layered elongation method was applied to the investigation on DNA single bulge recognition of small molecules (ligands). The reliability and validity of our approach were examined in comparison with the results obtained by direct calculations using a conventional quantum chemical method for the entire system. Furthermore, stabilization energies by the formation of the complex of bulge DNA and a ligand were estimated with basis set superposition error corrections incorporated into the elongation method.
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Affiliation(s)
- Keisuke Hisama
- Department of Interdisciplinary Engineering Sciences, Chemistry and Materials Science, Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, 6-1 Kasuga-Park, Fukuoka 816-8580, Japan
| | - Yuuichi Orimoto
- Department of Material Sciences, Faculty of Engineering Sciences, Kyushu University, 6-1 Kasuga-Park, Fukuoka 816-8580, Japan
| | - Anna Pomogaeva
- Department of Material Sciences, Faculty of Engineering Sciences, Kyushu University, 6-1 Kasuga-Park, Fukuoka 816-8580, Japan
| | - Kazuhiko Nakatani
- Department of Regulatory Bioorganic Chemistry, The Institute of Scientific and Industrial Research, Osaka University, 8-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan
| | - Yuriko Aoki
- Department of Material Sciences, Faculty of Engineering Sciences, Kyushu University, 6-1 Kasuga-Park, Fukuoka 816-8580, Japan
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7
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Gordon MS, Windus TL. Editorial: Modern Architectures and Their Impact on Electronic Structure Theory. Chem Rev 2020; 120:9015-9020. [DOI: 10.1021/acs.chemrev.0c00700] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Affiliation(s)
- Mark S. Gordon
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, United States
| | - Theresa L. Windus
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, United States
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8
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Fedorov DG. Three-Body Energy Decomposition Analysis Based on the Fragment Molecular Orbital Method. J Phys Chem A 2020; 124:4956-4971. [DOI: 10.1021/acs.jpca.0c03085] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Dmitri G. Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST), Central 2, Umezono 1-1-1, Tsukuba 305-8568, Japan
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9
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Gordon MS, Barca G, Leang SS, Poole D, Rendell AP, Galvez Vallejo JL, Westheimer B. Novel Computer Architectures and Quantum Chemistry. J Phys Chem A 2020; 124:4557-4582. [DOI: 10.1021/acs.jpca.0c02249] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Affiliation(s)
- Mark S. Gordon
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, United States
| | - Giuseppe Barca
- Research School of Computer Science, Australian National University, Canberra, ACT 2601, Australia
| | - Sarom S. Leang
- EP Analytics, 12121 Scripps Summit Drive, Suite 130, San Diego, California 92131, United States
| | - David Poole
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, United States
| | - Alistair P. Rendell
- College of Science and Engineering, Flinders University, Adelaide, SA 5042, Australia
| | - Jorge L. Galvez Vallejo
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, United States
| | - Bryce Westheimer
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, United States
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10
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Barca GMJ, Bertoni C, Carrington L, Datta D, De Silva N, Deustua JE, Fedorov DG, Gour JR, Gunina AO, Guidez E, Harville T, Irle S, Ivanic J, Kowalski K, Leang SS, Li H, Li W, Lutz JJ, Magoulas I, Mato J, Mironov V, Nakata H, Pham BQ, Piecuch P, Poole D, Pruitt SR, Rendell AP, Roskop LB, Ruedenberg K, Sattasathuchana T, Schmidt MW, Shen J, Slipchenko L, Sosonkina M, Sundriyal V, Tiwari A, Galvez Vallejo JL, Westheimer B, Włoch M, Xu P, Zahariev F, Gordon MS. Recent developments in the general atomic and molecular electronic structure system. J Chem Phys 2020; 152:154102. [PMID: 32321259 DOI: 10.1063/5.0005188] [Citation(s) in RCA: 518] [Impact Index Per Article: 129.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
A discussion of many of the recently implemented features of GAMESS (General Atomic and Molecular Electronic Structure System) and LibCChem (the C++ CPU/GPU library associated with GAMESS) is presented. These features include fragmentation methods such as the fragment molecular orbital, effective fragment potential and effective fragment molecular orbital methods, hybrid MPI/OpenMP approaches to Hartree-Fock, and resolution of the identity second order perturbation theory. Many new coupled cluster theory methods have been implemented in GAMESS, as have multiple levels of density functional/tight binding theory. The role of accelerators, especially graphical processing units, is discussed in the context of the new features of LibCChem, as it is the associated problem of power consumption as the power of computers increases dramatically. The process by which a complex program suite such as GAMESS is maintained and developed is considered. Future developments are briefly summarized.
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Affiliation(s)
- Giuseppe M J Barca
- Research School of Computer Science, Australian National University, Canberra, ACT 2601, Australia
| | - Colleen Bertoni
- Argonne Leadership Computing Facility, Argonne National Laboratory, Lemont, Illinois 60439, USA
| | - Laura Carrington
- EP Analytics, 12121 Scripps Summit Dr. Ste. 130, San Diego, California 92131, USA
| | - Dipayan Datta
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Nuwan De Silva
- Department of Physical and Biological Sciences, Western New England University, Springfield, Massachusetts 01119, USA
| | - J Emiliano Deustua
- Department of Chemistry, Michigan State University, East Lansing, Michigan 48824, USA
| | - Dmitri G Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST), Umezono 1-1-1, Tsukuba 305-8568, Japan
| | - Jeffrey R Gour
- Microsoft, 15590 NE 31st St., Redmond, Washington 98052, USA
| | - Anastasia O Gunina
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Emilie Guidez
- Department of Chemistry, University of Colorado Denver, Denver, Colorado 80217, USA
| | - Taylor Harville
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Stephan Irle
- Computational Science and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, USA
| | - Joe Ivanic
- Advanced Biomedical Computational Science, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21702, USA
| | - Karol Kowalski
- Physical Sciences Division, Battelle, Pacific Northwest National Laboratory, K8-91, P.O. Box 999, Richland, Washington 99352, USA
| | - Sarom S Leang
- EP Analytics, 12121 Scripps Summit Dr. Ste. 130, San Diego, California 92131, USA
| | - Hui Li
- Department of Chemistry, University of Nebraska, Lincoln, Nebraska 68588, USA
| | - Wei Li
- School of Chemistry and Chemical Engineering, Key Laboratory of Mesoscopic Chemistry of Ministry of Education, Institute of Theoretical and Computational Chemistry, Nanjing University, Nanjing 210023, People's Republic of China
| | - Jesse J Lutz
- Center for Computing Research, Sandia National Laboratories, Albuquerque, New Mexico 87185, USA
| | - Ilias Magoulas
- Department of Chemistry, Michigan State University, East Lansing, Michigan 48824, USA
| | - Joani Mato
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Vladimir Mironov
- Department of Chemistry, Lomonosov Moscow State University, Leninskie Gory 1/3, Moscow 119991, Russian Federation
| | - Hiroya Nakata
- Kyocera Corporation, Research Institute for Advanced Materials and Devices, 3-5-3 Hikaridai Seika-cho, Souraku-gun, Kyoto 619-0237, Japan
| | - Buu Q Pham
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Piotr Piecuch
- Department of Chemistry, Michigan State University, East Lansing, Michigan 48824, USA
| | - David Poole
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Spencer R Pruitt
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Alistair P Rendell
- Research School of Computer Science, Australian National University, Canberra, ACT 2601, Australia
| | - Luke B Roskop
- Cray Inc., a Hewlett Packard Enterprise Company, 2131 Lindau Ln #1000, Bloomington, Minnesota 55425, USA
| | - Klaus Ruedenberg
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | | | - Michael W Schmidt
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Jun Shen
- Department of Chemistry, Michigan State University, East Lansing, Michigan 48824, USA
| | - Lyudmila Slipchenko
- Department of Chemistry, Purdue University, West Lafayette, Indiana 47907, USA
| | - Masha Sosonkina
- Department of Computational Modeling and Simulation Engineering, Old Dominion University, Norfolk, Virginia 23529, USA
| | - Vaibhav Sundriyal
- Department of Computational Modeling and Simulation Engineering, Old Dominion University, Norfolk, Virginia 23529, USA
| | - Ananta Tiwari
- EP Analytics, 12121 Scripps Summit Dr. Ste. 130, San Diego, California 92131, USA
| | - Jorge L Galvez Vallejo
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Bryce Westheimer
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Marta Włoch
- 530 Charlesina Dr., Rochester, Michigan 48306, USA
| | - Peng Xu
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Federico Zahariev
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Mark S Gordon
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
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11
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Nakata H, Choi CH. Low-dimensional projection approach for efficient sampling of molecular recognition and polymer aggregation. Phys Chem Chem Phys 2020; 22:6953-6963. [PMID: 32182309 DOI: 10.1039/c9cp06964j] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The one-dimensional projection (ODP) approach is extended to two-dimensional umbrella sampling (TDUS) and is applied to three different complex systems in combination with a reactive force field (ReaxFF). TDUS is capable of showing detailed features of the free-energy surface (FES) of the double-proton transfer of the acetic acid dimer. It also revealed the direct relationship between the types of hydrogen bonding and binding strengths in the case of adrenaline molecular recognition by SIVSF (Serine, Isoleucine, Valine, Cysteine, and Phenylalanine). The study of polymer aggregation using TDUS shows that aggregation is preferred with a less-polar solvent, which is also consistent with the experimental observation of a tape-casting process. Therefore, TDUS can be generally useful in FES explorations from simple chemical reactions to complex processes of molecular recognition and polymer aggregation.
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Affiliation(s)
- Hiroya Nakata
- Kyocera Corporation, Research Institute for Advanced Materials and Devices, 3-5-3 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0237, Japan.
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12
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Alexander F, Almgren A, Bell J, Bhattacharjee A, Chen J, Colella P, Daniel D, DeSlippe J, Diachin L, Draeger E, Dubey A, Dunning T, Evans T, Foster I, Francois M, Germann T, Gordon M, Habib S, Halappanavar M, Hamilton S, Hart W, (Henry) Huang Z, Hungerford A, Kasen D, Kent PRC, Kolev T, Kothe DB, Kronfeld A, Luo Y, Mackenzie P, McCallen D, Messer B, Mniszewski S, Oehmen C, Perazzo A, Perez D, Richards D, Rider WJ, Rieben R, Roche K, Siegel A, Sprague M, Steefel C, Stevens R, Syamlal M, Taylor M, Turner J, Vay JL, Voter AF, Windus TL, Yelick K. Exascale applications: skin in the game. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2020; 378:20190056. [PMID: 31955678 PMCID: PMC7015298 DOI: 10.1098/rsta.2019.0056] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 12/11/2019] [Indexed: 05/21/2023]
Abstract
As noted in Wikipedia, skin in the game refers to having 'incurred risk by being involved in achieving a goal', where 'skin is a synecdoche for the person involved, and game is the metaphor for actions on the field of play under discussion'. For exascale applications under development in the US Department of Energy Exascale Computing Project, nothing could be more apt, with the skin being exascale applications and the game being delivering comprehensive science-based computational applications that effectively exploit exascale high-performance computing technologies to provide breakthrough modelling and simulation and data science solutions. These solutions will yield high-confidence insights and answers to the most critical problems and challenges for the USA in scientific discovery, national security, energy assurance, economic competitiveness and advanced healthcare. This article is part of a discussion meeting issue 'Numerical algorithms for high-performance computational science'.
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Affiliation(s)
| | - Ann Almgren
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - John Bell
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | | | | | - Phil Colella
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - David Daniel
- Los Alamos National Laboratory, Los Alamos, NM, USA
| | - Jack DeSlippe
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Lori Diachin
- Lawrence Livermore National Laboratory, Livermore, CA, USA
| | - Erik Draeger
- Lawrence Livermore National Laboratory, Livermore, CA, USA
| | - Anshu Dubey
- Argonne National Laboratory, Argonne, IL, USA
| | - Thom Dunning
- Pacific Northwest National Laboratory, Richland, WA, USA
| | - Thomas Evans
- Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Ian Foster
- Argonne National Laboratory, Argonne, IL, USA
| | | | - Tim Germann
- Los Alamos National Laboratory, Los Alamos, NM, USA
| | | | | | | | | | - William Hart
- Sandia National Laboratories, Albuquerque, NM, USA
| | | | | | - Daniel Kasen
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | | | - Tzanio Kolev
- Lawrence Livermore National Laboratory, Livermore, CA, USA
| | | | | | - Ye Luo
- Argonne National Laboratory, Argonne, IL, USA
| | | | - David McCallen
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | | | | | - Chris Oehmen
- Pacific Northwest National Laboratory, Richland, WA, USA
| | - Amedeo Perazzo
- SLAC National Accelerator Laboratory, Menlo Park, CA, USA
| | - Danny Perez
- Los Alamos National Laboratory, Los Alamos, NM, USA
| | - David Richards
- Lawrence Livermore National Laboratory, Livermore, CA, USA
| | | | - Rob Rieben
- Lawrence Livermore National Laboratory, Livermore, CA, USA
| | - Kenneth Roche
- Pacific Northwest National Laboratory, Richland, WA, USA
| | | | | | - Carl Steefel
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | | | | | - Mark Taylor
- Sandia National Laboratories, Albuquerque, NM, USA
| | - John Turner
- Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Jean-Luc Vay
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA
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13
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Pham BQ, Gordon MS. Development of the FMO/RI-MP2 Fully Analytic Gradient Using a Hybrid-Distributed/Shared Memory Programming Model. J Chem Theory Comput 2020; 16:1039-1054. [PMID: 31899632 DOI: 10.1021/acs.jctc.9b01082] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
The fully analytic gradient of the second-order Møller-Plesset perturbation theory (MP2) with the resolution-of-the-identity (RI) approximation in the fragment molecular orbital (FMO) framework is derived and implemented using a hybrid multilevel parallel programming model, a combination of the general distributed data interface (GDDI) and the OpenMP API. The FMO/MP2 analytic gradient contains three parts, i.e., the internal fragment component, the electrostatic potential (ESP) component, and the response terms. The RI approximation is applied to the internal fragment MP2 gradient term, whose MP2 densities and monomer MP2 Lagrangians are shared with the ESP and the response terms. The FMO/RI-MP2 analytic gradient implementation is validated against the numerical gradient (with errors ∼10-6-10-5 Hartree/Bohr) and the energy conservation in molecular dynamics (MD) simulations using NVE ensembles. The RI approximation introduces an error of ∼10-5 Hartree/Bohr with a speedup of 4.0-8.0× compared with the currently available GDDI FMO/MP2 gradient. The node linear scaling of the fragmentation framework due to multilevel parallelism is well-preserved and is demonstrated in single-point gradient calculations of large water clusters (e.g., 1120 and 2165 molecules) using 300-800 KNL compute nodes with a parallel efficiency of more than 90%.
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Affiliation(s)
- Buu Q Pham
- Department of Chemistry and Ames Laboratory , Iowa State University , Ames , Iowa 50011 , United States
| | - Mark S Gordon
- Department of Chemistry and Ames Laboratory , Iowa State University , Ames , Iowa 50011 , United States
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14
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Kumar A, Iyengar SS. Fragment-Based Electronic Structure for Potential Energy Surfaces Using a Superposition of Fragmentation Topologies. J Chem Theory Comput 2019; 15:5769-5786. [DOI: 10.1021/acs.jctc.9b00608] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Affiliation(s)
- Anup Kumar
- Department of Chemistry and Department of Physics, Indiana University, 800 East Kirkwood Avenue, Bloomington, Indiana-47405, United States
| | - Srinivasan S. Iyengar
- Department of Chemistry and Department of Physics, Indiana University, 800 East Kirkwood Avenue, Bloomington, Indiana-47405, United States
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15
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Pham BQ, Gordon MS. Hybrid Distributed/Shared Memory Model for the RI-MP2 Method in the Fragment Molecular Orbital Framework. J Chem Theory Comput 2019; 15:5252-5258. [DOI: 10.1021/acs.jctc.9b00409] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Buu Q. Pham
- Department of Chemistry, Iowa State University, Ames, Iowa 50011, United States
| | - Mark S. Gordon
- Department of Chemistry, Iowa State University, Ames, Iowa 50011, United States
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16
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Conrad JA, Kim S, Gordon MS. Ionic liquids from a fragmented perspective. Phys Chem Chem Phys 2019; 21:16878-16888. [PMID: 31359024 DOI: 10.1039/c9cp02836f] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
The efficacy of using fragmentation methods, such as the effective fragment potential, the fragment molecular orbital and the effective fragment molecular orbital methods is discussed. The advantages and current limitations of these methods are considered, potential improvements are suggested, and a prognosis for the future is provided.
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Affiliation(s)
- Justin A Conrad
- Department of Chemistry, Iowa State University, Ames, IA 50014, USA.
| | - Shinae Kim
- Department of Chemistry, Iowa State University, Ames, IA 50014, USA.
| | - Mark S Gordon
- Department of Chemistry, Iowa State University, Ames, IA 50014, USA.
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17
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Trajkovski M, Endoh T, Tateishi-Karimata H, Ohyama T, Tanaka S, Plavec J, Sugimoto N. Pursuing origins of (poly)ethylene glycol-induced G-quadruplex structural modulations. Nucleic Acids Res 2019; 46:4301-4315. [PMID: 29648656 PMCID: PMC5934638 DOI: 10.1093/nar/gky250] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2018] [Accepted: 03/28/2018] [Indexed: 01/18/2023] Open
Abstract
Molecular crowding conditions provided by high concentration of cosolutes are utilized for characterization of biomolecules in cell-mimicking environment and development of drug-delivery systems. In this context, (poly)ethylene glycols are often used for studying non-canonical DNA structures termed G-quadruplexes, which came into focus by emerging structural biology findings and new therapeutic drug design approaches. Recently, several reports were made arguing against using (poly)ethylene glycols in role of molecular crowding agents due to their direct impact on DNA G-quadruplex stability and topology. However, the available data on structural details underlying DNA interaction is very scarce and thus limits in-depth comprehension. Herein, structural and thermodynamic analyses were strategically combined to assess G-quadruplex-cosolute interactions and address previously reported variances regarding the driving forces of G-rich DNA structural transformations under molecular crowding conditions. With the use of complementary (CD, NMR and UV) spectroscopic methods and model approach we characterized DNA G-quadruplex in the presence of the smallest and one of the largest typically used (poly)ethylene glycols. Dehydration effect is the key contributor to ethylene-glycol-induced increased stability of the G-quadruplex, which is in the case of the large cosolute mainly guided by the subtle direct interactions between PEG 8000 and the outer G-quartet regions.
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Affiliation(s)
- Marko Trajkovski
- Slovenian NMR Centre, National Institute of Chemistry, Hajdrihova 19, Ljubljana, SI-1000, Slovenia
| | - Tamaki Endoh
- Frontier Institute for Biomolecular Engineering Research (FIBER), Konan University, 7-1-20 Minatojima-Minamimachi, Chuo-ku, Kobe 650-0047, Japan
| | - Hisae Tateishi-Karimata
- Frontier Institute for Biomolecular Engineering Research (FIBER), Konan University, 7-1-20 Minatojima-Minamimachi, Chuo-ku, Kobe 650-0047, Japan
| | - Tatsuya Ohyama
- Frontier Institute for Biomolecular Engineering Research (FIBER), Konan University, 7-1-20 Minatojima-Minamimachi, Chuo-ku, Kobe 650-0047, Japan
| | - Shigenori Tanaka
- Department of Computational Science, Graduate School of System Informatics, Kobe University, 1-1, Rokkodai, Nada-ku, Kobe 657-8501, Japan
| | - Janez Plavec
- Slovenian NMR Centre, National Institute of Chemistry, Hajdrihova 19, Ljubljana, SI-1000, Slovenia.,EN→FIST Centre of Excellence, Trg OF 13, SI-1000 Ljubljana, Slovenia.,Faculty of Chemistry and Chemical Technology, University of Ljubljana, Večna pot 113, p. p. 537, SI-1000 Ljubljana, Slovenia
| | - Naoki Sugimoto
- Frontier Institute for Biomolecular Engineering Research (FIBER), Konan University, 7-1-20 Minatojima-Minamimachi, Chuo-ku, Kobe 650-0047, Japan.,Graduate School of Frontiers of Innovative Research in Science and Technology (FIRST), Konan University, 7-1-20 Minatojima-Minamimachi, Kobe 650-0047, Japan
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18
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Development of a new parameter optimization scheme for a reactive force field based on a machine learning approach. J Comput Chem 2019; 40:2000-2012. [DOI: 10.1002/jcc.25841] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Revised: 02/17/2019] [Accepted: 03/27/2019] [Indexed: 12/14/2022]
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19
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Ricard TC, Iyengar SS. Efficiently Capturing Weak Interactions in ab Initio Molecular Dynamics with on-the-Fly Basis Set Extrapolation. J Chem Theory Comput 2018; 14:5535-5552. [DOI: 10.1021/acs.jctc.8b00803] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Affiliation(s)
- Timothy C. Ricard
- Department of Chemistry and Department of Physics, Indiana University, 800 E. Kirkwood Avenue, Bloomington, Indiana 47405, United States
| | - Srinivasan S. Iyengar
- Department of Chemistry and Department of Physics, Indiana University, 800 E. Kirkwood Avenue, Bloomington, Indiana 47405, United States
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20
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Xu P, Guidez EB, Bertoni C, Gordon MS. Perspective:Ab initioforce field methods derived from quantum mechanics. J Chem Phys 2018. [DOI: 10.1063/1.5009551] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Affiliation(s)
- Peng Xu
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Emilie B. Guidez
- Department of Chemistry, University of Colorado Denver, Denver, Colorado 80217, USA
| | - Colleen Bertoni
- Argonne Leadership Computing Facility, Argonne, Illinois 60439, USA
| | - Mark S. Gordon
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
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21
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Nishimoto Y, Fedorov DG. Adaptive frozen orbital treatment for the fragment molecular orbital method combined with density-functional tight-binding. J Chem Phys 2018; 148:064115. [DOI: 10.1063/1.5012935] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Affiliation(s)
- Yoshio Nishimoto
- Fukui Institute for Fundamental Chemistry, Kyoto University, 34-4 Takano Nishihiraki-cho, Sakyo-ku, Kyoto 606-8103, Japan
| | - Dmitri G. Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat), National Institute of Advanced Industrial Science and Technology (AIST), 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568, Japan
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22
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Giese TJ, York DM. Quantum mechanical force fields for condensed phase molecular simulations. JOURNAL OF PHYSICS. CONDENSED MATTER : AN INSTITUTE OF PHYSICS JOURNAL 2017; 29:383002. [PMID: 28817382 PMCID: PMC5821073 DOI: 10.1088/1361-648x/aa7c5c] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Molecular simulations are powerful tools for providing atomic-level details into complex chemical and physical processes that occur in the condensed phase. For strongly interacting systems where quantum many-body effects are known to play an important role, density-functional methods are often used to provide the model with the potential energy used to drive dynamics. These methods, however, suffer from two major drawbacks. First, they are often too computationally intensive to practically apply to large systems over long time scales, limiting their scope of application. Second, there remain challenges for these models to obtain the necessary level of accuracy for weak non-bonded interactions to obtain quantitative accuracy for a wide range of condensed phase properties. Quantum mechanical force fields (QMFFs) provide a potential solution to both of these limitations. In this review, we address recent advances in the development of QMFFs for condensed phase simulations. In particular, we examine the development of QMFF models using both approximate and ab initio density-functional models, the treatment of short-ranged non-bonded and long-ranged electrostatic interactions, and stability issues in molecular dynamics calculations. Example calculations are provided for crystalline systems, liquid water, and ionic liquids. We conclude with a perspective for emerging challenges and future research directions.
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23
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Han Y, Rasulev B, Kilin DS. Photofragmentation of Tetranitromethane: Spin-Unrestricted Time-Dependent Excited-State Molecular Dynamics. J Phys Chem Lett 2017; 8:3185-3192. [PMID: 28618779 DOI: 10.1021/acs.jpclett.7b01330] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
In this study, the photofragmentation dynamics of tetranitromethane (TNM) is explored by a spin-unrestricted time-dependent excited-state molecular dynamics (u-TDESMD) algorithm based on Rabi oscillations and principles similar to trajectory surface hopping, with a midintensity field approximation. The leading order process is represented by the molecule undergoing cyclic excitations and de-excitations. During excitation cycles, the nuclear kinetic energy is accumulated to overcome the dissociation barriers in the reactant and a sequence of intermediates. The dissociation pathway includes the ejection of NO2 groups followed by the formation of NO and CO. The simulated mass spectra at the ab initio level, based on the bond length in possible fragments, are extracted from simulation trajectories. The recently developed methodology has the potential to model and monitor photoreactions with open-shell intermediates and radicals.
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Affiliation(s)
- Yulun Han
- Department of Chemistry, University of South Dakota , Vermillion, South Dakota 57069, United States
- Department of Chemistry and Biochemistry, North Dakota State University , Fargo, North Dakota 58108, United States
| | - Bakhtiyor Rasulev
- Department of Coatings and Polymeric Materials, North Dakota State University , Fargo, North Dakota 58102, United States
| | - Dmitri S Kilin
- Department of Chemistry, University of South Dakota , Vermillion, South Dakota 57069, United States
- Department of Chemistry and Biochemistry, North Dakota State University , Fargo, North Dakota 58108, United States
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24
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Fedorov DG. The fragment molecular orbital method: theoretical development, implementation in
GAMESS
, and applications. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2017. [DOI: 10.1002/wcms.1322] [Citation(s) in RCA: 71] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Dmitri G. Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD‐FMat)National Institute of Advanced Industrial Science and Technology (AIST)TsukubaJapan
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25
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Chen GD, Weng J, Song G, Li ZH. Generalized Switch Functions in the Multilevel Many-Body Expansion Method and Its Application to Water Clusters. J Chem Theory Comput 2017; 13:2010-2020. [DOI: 10.1021/acs.jctc.7b00144] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Guo Dong Chen
- Collaborative Innovation Center of Chemistry for Energy Material, Shanghai Key Laboratory of Molecular Catalysis & Innovative Materials, Department of Chemistry, Fudan University, Shanghai 200433, China
| | - Jingwei Weng
- Collaborative Innovation Center of Chemistry for Energy Material, Shanghai Key Laboratory of Molecular Catalysis & Innovative Materials, Department of Chemistry, Fudan University, Shanghai 200433, China
| | - Guoliang Song
- Collaborative Innovation Center of Chemistry for Energy Material, Shanghai Key Laboratory of Molecular Catalysis & Innovative Materials, Department of Chemistry, Fudan University, Shanghai 200433, China
| | - Zhen Hua Li
- Collaborative Innovation Center of Chemistry for Energy Material, Shanghai Key Laboratory of Molecular Catalysis & Innovative Materials, Department of Chemistry, Fudan University, Shanghai 200433, China
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26
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Liu J, Qi LW, Zhang JZH, He X. Fragment Quantum Mechanical Method for Large-Sized Ion–Water Clusters. J Chem Theory Comput 2017; 13:2021-2034. [DOI: 10.1021/acs.jctc.7b00149] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Affiliation(s)
- Jinfeng Liu
- State
Key Laboratory of Natural Medicines, Department of Basic Medicine
and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
| | - Lian-Wen Qi
- State
Key Laboratory of Natural Medicines, Department of Basic Medicine
and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
| | - John Z. H. Zhang
- School
of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200062, China
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai, 200062, China
- Department
of Chemistry, New York University, New York, New York 10003, United States
| | - Xiao He
- School
of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200062, China
- NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai, 200062, China
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27
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Willow SY. Path integral molecular dynamics at zero thermal temperature. Chem Phys Lett 2017. [DOI: 10.1016/j.cplett.2017.02.038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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28
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Pruitt SR, Steinmann C. Mapping Interaction Energies in Chorismate Mutase with the Fragment Molecular Orbital Method. J Phys Chem A 2017; 121:1797-1807. [DOI: 10.1021/acs.jpca.6b12830] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Spencer R. Pruitt
- Academic & Research Computing, Worcester Polytechnic Institute, Worcester, Massachusetts 01602, United States
| | - Casper Steinmann
- Centre
for Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, United Kingdom
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29
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Nishimoto Y, Fedorov DG. Three-body expansion of the fragment molecular orbital method combined with density-functional tight-binding. J Comput Chem 2017; 38:406-418. [DOI: 10.1002/jcc.24693] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2016] [Revised: 11/14/2016] [Accepted: 11/17/2016] [Indexed: 12/20/2022]
Affiliation(s)
- Yoshio Nishimoto
- Fukui Institute for Fundamental Chemistry, Kyoto University; 34-4 Takano Nishihiraki-cho Sakyo-ku Kyoto 606-8103 Japan
| | - Dmitri G. Fedorov
- Research Center for Computational Design of Advanced Functional Materials (CD-FMat); National Institute of Advanced Industrial Science and Technology (AIST); 1-1-1 Umezono Tsukuba Ibaraki 305-8568 Japan
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30
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Ratcliff LE, Mohr S, Huhs G, Deutsch T, Masella M, Genovese L. Challenges in large scale quantum mechanical calculations. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2016. [DOI: 10.1002/wcms.1290] [Citation(s) in RCA: 70] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Laura E. Ratcliff
- Argonne Leadership Computing Facility Argonne National Laboratory Lemon IL USA
| | - Stephan Mohr
- Department of Computer Applications in Science and Engineering Barcelona Supercomputing Center (BSC‐CNS) Barcelona Spain
| | - Georg Huhs
- Department of Computer Applications in Science and Engineering Barcelona Supercomputing Center (BSC‐CNS) Barcelona Spain
| | - Thierry Deutsch
- University Grenoble Alpes INAC‐MEM Grenoble France
- CEA, INAC‐MEM Grenoble France
| | - Michel Masella
- Laboratoire de Biologie Structurale et Radiologie, Service de Bioénergétique, Biologie Structurale et Mécanisme Institut de Biologie et de Technologie de Saclay, CEA Saclay Gif‐sur‐Yvette Cedex France
| | - Luigi Genovese
- University Grenoble Alpes INAC‐MEM Grenoble France
- CEA, INAC‐MEM Grenoble France
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