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Smith DGA, Lolinco AT, Glick ZL, Lee J, Alenaizan A, Barnes TA, Borca CH, Di Remigio R, Dotson DL, Ehlert S, Heide AG, Herbst MF, Hermann J, Hicks CB, Horton JT, Hurtado AG, Kraus P, Kruse H, Lee SJR, Misiewicz JP, Naden LN, Ramezanghorbani F, Scheurer M, Schriber JB, Simmonett AC, Steinmetzer J, Wagner JR, Ward L, Welborn M, Altarawy D, Anwar J, Chodera JD, Dreuw A, Kulik HJ, Liu F, Martínez TJ, Matthews DA, Schaefer HF, Šponer J, Turney JM, Wang LP, De Silva N, King RA, Stanton JF, Gordon MS, Windus TL, Sherrill CD, Burns LA. Quantum Chemistry Common Driver and Databases (QCDB) and Quantum Chemistry Engine (QCEngine): Automation and interoperability among computational chemistry programs. J Chem Phys 2021; 155:204801. [PMID: 34852489 DOI: 10.1063/5.0059356] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Community efforts in the computational molecular sciences (CMS) are evolving toward modular, open, and interoperable interfaces that work with existing community codes to provide more functionality and composability than could be achieved with a single program. The Quantum Chemistry Common Driver and Databases (QCDB) project provides such capability through an application programming interface (API) that facilitates interoperability across multiple quantum chemistry software packages. In tandem with the Molecular Sciences Software Institute and their Quantum Chemistry Archive ecosystem, the unique functionalities of several CMS programs are integrated, including CFOUR, GAMESS, NWChem, OpenMM, Psi4, Qcore, TeraChem, and Turbomole, to provide common computational functions, i.e., energy, gradient, and Hessian computations as well as molecular properties such as atomic charges and vibrational frequency analysis. Both standard users and power users benefit from adopting these APIs as they lower the language barrier of input styles and enable a standard layout of variables and data. These designs allow end-to-end interoperable programming of complex computations and provide best practices options by default.
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Affiliation(s)
- Daniel G A Smith
- Molecular Sciences Software Institute, Blacksburg, Virginia 24060, USA
| | | | - Zachary L Glick
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, and School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Jiyoung Lee
- Department of Chemistry, Iowa State University, Ames, Iowa 50011, USA
| | - Asem Alenaizan
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, and School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Taylor A Barnes
- Molecular Sciences Software Institute, Blacksburg, Virginia 24060, USA
| | - Carlos H Borca
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, and School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Roberto Di Remigio
- Department of Chemistry, Centre for Theoretical and Computational Chemistry, UiT, The Arctic University of Norway, N-9037 Tromsø, Norway
| | - David L Dotson
- Open Force Field Initiative, University of Colorado Boulder, Boulder, Colorado 80309, USA
| | - Sebastian Ehlert
- Mulliken Center for Theoretical Chemistry, Institut für Physikalische und Theoretische Chemie, Universität Bonn, Beringstraße 4, D-53115 Bonn, Germany
| | - Alexander G Heide
- Center for Computational Quantum Chemistry, University of Georgia, Athens, Georgia 30602, USA
| | - Michael F Herbst
- Applied and Computational Mathematics, RWTH Aachen University, Schinkelstr. 2, 52062 Aachen, Germany
| | - Jan Hermann
- FU Berlin, Department of Mathematics and Computer Science, 14195 Berlin, Germany
| | - Colton B Hicks
- Department of Chemistry, Stanford University, Stanford, California 94305, USA
| | - Joshua T Horton
- Department of Chemistry, Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - Adrian G Hurtado
- Institute for Advanced Computational Science, Stony Brook University, Stony Brook, New York 11794-5250, USA
| | - Peter Kraus
- School of Molecular and Life Sciences, Curtin University, GPO Box U1987, Perth 6845, WA, Australia
| | - Holger Kruse
- Institute of Biophysics of the Czech Academy of Sciences, Královopolská 135, 612 65 Brno, Czech Republic
| | | | - Jonathon P Misiewicz
- Center for Computational Quantum Chemistry, University of Georgia, Athens, Georgia 30602, USA
| | - Levi N Naden
- Molecular Sciences Software Institute, Blacksburg, Virginia 24060, USA
| | | | - Maximilian Scheurer
- Interdisciplinary Center for Scientific Computing, Heidelberg University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Jeffrey B Schriber
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, and School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Andrew C Simmonett
- Laboratory of Computational Biology, National Institutes of Health-National Heart, Lung and Blood Institute, Bethesda, Maryland 20892, USA
| | - Johannes Steinmetzer
- Institute of Physical Chemistry, Friedrich Schiller University Jena, Jena, Germany
| | - Jeffrey R Wagner
- Open Force Field Initiative, University of Colorado Boulder, Boulder, Colorado 80309, USA
| | - Logan Ward
- Data Science and Learning Division, Argonne National Laboratory, Lemont, Illinois 60439, USA
| | - Matthew Welborn
- Molecular Sciences Software Institute, Blacksburg, Virginia 24060, USA
| | - Doaa Altarawy
- Molecular Sciences Software Institute, Blacksburg, Virginia 24060, USA
| | - Jamshed Anwar
- Department of Chemistry, Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - John D Chodera
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA
| | - Andreas Dreuw
- Interdisciplinary Center for Scientific Computing, Heidelberg University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Heather J Kulik
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Fang Liu
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Todd J Martínez
- Department of Chemistry, Stanford University, Stanford, California 94305, USA
| | - Devin A Matthews
- The Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas 78712, USA
| | - Henry F Schaefer
- Center for Computational Quantum Chemistry, University of Georgia, Athens, Georgia 30602, USA
| | - Jiří Šponer
- Institute of Biophysics of the Czech Academy of Sciences, Královopolská 135, 612 65 Brno, Czech Republic
| | - Justin M Turney
- Center for Computational Quantum Chemistry, University of Georgia, Athens, Georgia 30602, USA
| | - Lee-Ping Wang
- Department of Chemistry, University of California Davis, Davis, California 95616, USA
| | - Nuwan De Silva
- Department of Chemistry, Iowa State University, Ames, Iowa 50011, USA
| | - Rollin A King
- Department of Chemistry, Bethel University, St. Paul, Minnesota 55112, USA
| | - John F Stanton
- Quantum Theory Project, The University of Florida, 2328 New Physics Building, Gainesville, Florida 32611-8435, USA
| | - Mark S Gordon
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - Theresa L Windus
- Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, USA
| | - C David Sherrill
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, and School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Lori A Burns
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, and School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
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Schriber JB, Sirianni DA, Smith DGA, Burns LA, Sitkoff D, Cheney DL, Sherrill CD. Optimized damping parameters for empirical dispersion corrections to symmetry-adapted perturbation theory. J Chem Phys 2021; 154:234107. [PMID: 34241276 DOI: 10.1063/5.0049745] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Symmetry-adapted perturbation theory (SAPT) has become an invaluable tool for studying the fundamental nature of non-covalent interactions by directly computing the electrostatics, exchange (steric) repulsion, induction (polarization), and London dispersion contributions to the interaction energy using quantum mechanics. Further application of SAPT is primarily limited by its computational expense, where even its most affordable variant (SAPT0) scales as the fifth power of system size [O(N5)] due to the dispersion terms. The algorithmic scaling of SAPT0 is reduced from O(N5)→O(N4) by replacing these terms with the empirical D3 dispersion correction of Grimme and co-workers, forming a method that may be termed SAPT0-D3. Here, we optimize the damping parameters for the -D3 terms in SAPT0-D3 using a much larger training set than has previously been considered, namely, 8299 interaction energies computed at the complete-basis-set limit of coupled cluster through perturbative triples [CCSD(T)/CBS]. Perhaps surprisingly, with only three fitted parameters, SAPT0-D3 improves on the accuracy of SAPT0, reducing mean absolute errors from 0.61 to 0.49 kcal mol-1 over the full set of complexes. Additionally, SAPT0-D3 exhibits a nearly 2.5× speedup over conventional SAPT0 for systems with ∼300 atoms and is applied here to systems with up to 459 atoms. Finally, we have also implemented a functional group partitioning of the approach (F-SAPT0-D3) and applied it to determine important contacts in the binding of salbutamol to G-protein coupled β1-adrenergic receptor in both active and inactive forms. SAPT0-D3 capabilities have been added to the open-source Psi4 software.
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Affiliation(s)
- Jeffrey B Schriber
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, USA
| | - Dominic A Sirianni
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, USA
| | - Daniel G A Smith
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, USA
| | - Lori A Burns
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, USA
| | - Doree Sitkoff
- Molecular Structure and Design, Bristol-Myers Squibb Company, P.O. Box 5400, Princeton, New Jersey 08543, USA
| | - Daniel L Cheney
- Molecular Structure and Design, Bristol-Myers Squibb Company, P.O. Box 5400, Princeton, New Jersey 08543, USA
| | - C David Sherrill
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, USA
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Schriber JB, Nascimento DR, Koutsoukas A, Spronk SA, Cheney DL, Sherrill CD. CLIFF: A component-based, machine-learned, intermolecular force field. J Chem Phys 2021; 154:184110. [PMID: 34241025 DOI: 10.1063/5.0042989] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Computation of intermolecular interactions is a challenge in drug discovery because accurate ab initio techniques are too computationally expensive to be routinely applied to drug-protein models. Classical force fields are more computationally feasible, and force fields designed to match symmetry adapted perturbation theory (SAPT) interaction energies can remain accurate in this context. Unfortunately, the application of such force fields is complicated by the laborious parameterization required for computations on new molecules. Here, we introduce the component-based machine-learned intermolecular force field (CLIFF), which combines accurate, physics-based equations for intermolecular interaction energies with machine-learning models to enable automatic parameterization. The CLIFF uses functional forms corresponding to electrostatic, exchange-repulsion, induction/polarization, and London dispersion components in SAPT. Molecule-independent parameters are fit with respect to SAPT2+(3)δMP2/aug-cc-pVTZ, and molecule-dependent atomic parameters (atomic widths, atomic multipoles, and Hirshfeld ratios) are obtained from machine learning models developed for C, N, O, H, S, F, Cl, and Br. The CLIFF achieves mean absolute errors (MAEs) no worse than 0.70 kcal mol-1 in both total and component energies across a diverse dimer test set. For the side chain-side chain interaction database derived from protein fragments, the CLIFF produces total interaction energies with an MAE of 0.27 kcal mol-1 with respect to reference data, outperforming similar and even more expensive methods. In applications to a set of model drug-protein interactions, the CLIFF is able to accurately rank-order ligand binding strengths and achieves less than 10% error with respect to SAPT reference values for most complexes.
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Affiliation(s)
- Jeffrey B Schriber
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30318, USA
| | - Daniel R Nascimento
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30318, USA
| | - Alexios Koutsoukas
- Molecular Structure and Design, Bristol Myers Squibb Company, P.O. Box 5400, Princeton, New Jersey 08543, USA
| | - Steven A Spronk
- Molecular Structure and Design, Bristol Myers Squibb Company, P.O. Box 5400, Princeton, New Jersey 08543, USA
| | - Daniel L Cheney
- Molecular Structure and Design, Bristol Myers Squibb Company, P.O. Box 5400, Princeton, New Jersey 08543, USA
| | - C David Sherrill
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry and School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30318, USA
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Smith DGA, Burns LA, Simmonett AC, Parrish RM, Schieber MC, Galvelis R, Kraus P, Kruse H, Di Remigio R, Alenaizan A, James AM, Lehtola S, Misiewicz JP, Scheurer M, Shaw RA, Schriber JB, Xie Y, Glick ZL, Sirianni DA, O’Brien JS, Waldrop JM, Kumar A, Hohenstein EG, Pritchard BP, Brooks BR, Schaefer HF, Sokolov AY, Patkowski K, DePrince AE, Bozkaya U, King RA, Evangelista FA, Turney JM, Crawford TD, Sherrill CD. Psi4 1.4: Open-source software for high-throughput quantum chemistry. J Chem Phys 2020; 152:184108. [PMID: 32414239 PMCID: PMC7228781 DOI: 10.1063/5.0006002] [Citation(s) in RCA: 301] [Impact Index Per Article: 75.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 04/12/2020] [Indexed: 12/13/2022] Open
Abstract
PSI4 is a free and open-source ab initio electronic structure program providing implementations of Hartree-Fock, density functional theory, many-body perturbation theory, configuration interaction, density cumulant theory, symmetry-adapted perturbation theory, and coupled-cluster theory. Most of the methods are quite efficient, thanks to density fitting and multi-core parallelism. The program is a hybrid of C++ and Python, and calculations may be run with very simple text files or using the Python API, facilitating post-processing and complex workflows; method developers also have access to most of PSI4's core functionalities via Python. Job specification may be passed using The Molecular Sciences Software Institute (MolSSI) QCSCHEMA data format, facilitating interoperability. A rewrite of our top-level computation driver, and concomitant adoption of the MolSSI QCARCHIVE INFRASTRUCTURE project, makes the latest version of PSI4 well suited to distributed computation of large numbers of independent tasks. The project has fostered the development of independent software components that may be reused in other quantum chemistry programs.
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Affiliation(s)
| | - Lori A. Burns
- Center for Computational Molecular Science and
Technology, School of Chemistry and Biochemistry, School of Computational Science and
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400,
USA
| | - Andrew C. Simmonett
- National Institutes of Health – National Heart,
Lung and Blood Institute, Laboratory of Computational Biology, Bethesda,
Maryland 20892, USA
| | - Robert M. Parrish
- Center for Computational Molecular Science and
Technology, School of Chemistry and Biochemistry, School of Computational Science and
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400,
USA
| | - Matthew C. Schieber
- Center for Computational Molecular Science and
Technology, School of Chemistry and Biochemistry, School of Computational Science and
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400,
USA
| | | | - Peter Kraus
- School of Molecular and Life Sciences, Curtin
University, Kent St., Bentley, Perth, Western Australia 6102,
Australia
| | - Holger Kruse
- Institute of Biophysics of the Czech Academy of
Sciences, Královopolská 135, 612 65 Brno, Czech
Republic
| | - Roberto Di Remigio
- Department of Chemistry, Centre for Theoretical
and Computational Chemistry, UiT, The Arctic University of Norway, N-9037
Tromsø, Norway
| | - Asem Alenaizan
- Center for Computational Molecular Science and
Technology, School of Chemistry and Biochemistry, School of Computational Science and
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400,
USA
| | - Andrew M. James
- Department of Chemistry, Virginia
Tech, Blacksburg, Virginia 24061, USA
| | - Susi Lehtola
- Department of Chemistry, University of
Helsinki, P.O. Box 55 (A. I. Virtasen aukio 1), FI-00014 Helsinki,
Finland
| | - Jonathon P. Misiewicz
- Center for Computational Quantum Chemistry,
University of Georgia, Athens, Georgia 30602, USA
| | - Maximilian Scheurer
- Interdisciplinary Center for Scientific
Computing, Heidelberg University, D-69120 Heidelberg,
Germany
| | - Robert A. Shaw
- ARC Centre of Excellence in Exciton Science,
School of Science, RMIT University, Melbourne, VIC 3000,
Australia
| | - Jeffrey B. Schriber
- Center for Computational Molecular Science and
Technology, School of Chemistry and Biochemistry, School of Computational Science and
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400,
USA
| | - Yi Xie
- Center for Computational Molecular Science and
Technology, School of Chemistry and Biochemistry, School of Computational Science and
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400,
USA
| | - Zachary L. Glick
- Center for Computational Molecular Science and
Technology, School of Chemistry and Biochemistry, School of Computational Science and
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400,
USA
| | - Dominic A. Sirianni
- Center for Computational Molecular Science and
Technology, School of Chemistry and Biochemistry, School of Computational Science and
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400,
USA
| | - Joseph Senan O’Brien
- Center for Computational Molecular Science and
Technology, School of Chemistry and Biochemistry, School of Computational Science and
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400,
USA
| | - Jonathan M. Waldrop
- Department of Chemistry and Biochemistry, Auburn
University, Auburn, Alabama 36849, USA
| | - Ashutosh Kumar
- Department of Chemistry, Virginia
Tech, Blacksburg, Virginia 24061, USA
| | - Edward G. Hohenstein
- SLAC National Accelerator Laboratory, Stanford
PULSE Institute, Menlo Park, California 94025,
USA
| | | | - Bernard R. Brooks
- National Institutes of Health – National Heart,
Lung and Blood Institute, Laboratory of Computational Biology, Bethesda,
Maryland 20892, USA
| | - Henry F. Schaefer
- Center for Computational Quantum Chemistry,
University of Georgia, Athens, Georgia 30602, USA
| | - Alexander Yu. Sokolov
- Department of Chemistry and Biochemistry, The
Ohio State University, Columbus, Ohio 43210, USA
| | - Konrad Patkowski
- Department of Chemistry and Biochemistry, Auburn
University, Auburn, Alabama 36849, USA
| | - A. Eugene DePrince
- Department of Chemistry and Biochemistry,
Florida State University, Tallahassee, Florida 32306-4390,
USA
| | - Uğur Bozkaya
- Department of Chemistry, Hacettepe
University, Ankara 06800, Turkey
| | - Rollin A. King
- Department of Chemistry, Bethel
University, St. Paul, Minnesota 55112, USA
| | | | - Justin M. Turney
- Center for Computational Quantum Chemistry,
University of Georgia, Athens, Georgia 30602, USA
| | | | - C. David Sherrill
- Center for Computational Molecular Science and
Technology, School of Chemistry and Biochemistry, School of Computational Science and
Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400,
USA
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Affiliation(s)
- Jeffrey B. Schriber
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30318, USA
- Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, USA
| | - Francesco A. Evangelista
- Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, USA
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Schriber JB, Hannon KP, Li C, Evangelista FA. A Combined Selected Configuration Interaction and Many-Body Treatment of Static and Dynamical Correlation in Oligoacenes. J Chem Theory Comput 2018; 14:6295-6305. [DOI: 10.1021/acs.jctc.8b00877] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Affiliation(s)
- Jeffrey B. Schriber
- Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States
| | - Kevin P. Hannon
- Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States
| | - Chenyang Li
- Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States
| | - Francesco A. Evangelista
- Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States
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Smith DGA, Burns LA, Sirianni DA, Nascimento DR, Kumar A, James AM, Schriber JB, Zhang T, Zhang B, Abbott AS, Berquist EJ, Lechner MH, Cunha LA, Heide AG, Waldrop JM, Takeshita TY, Alenaizan A, Neuhauser D, King RA, Simmonett AC, Turney JM, Schaefer HF, Evangelista FA, DePrince AE, Crawford TD, Patkowski K, Sherrill CD. Psi4NumPy: An Interactive Quantum Chemistry Programming Environment for Reference Implementations and Rapid Development. J Chem Theory Comput 2018; 14:3504-3511. [DOI: 10.1021/acs.jctc.8b00286] [Citation(s) in RCA: 73] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Daniel G. A. Smith
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, United States
| | - Lori A. Burns
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, United States
| | - Dominic A. Sirianni
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, United States
| | - Daniel R. Nascimento
- Department of Chemistry and Biochemistry, Florida State University, Tallahassee, Florida 32306-4390, United States
| | - Ashutosh Kumar
- Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, United States
| | - Andrew M. James
- Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, United States
| | - Jeffrey B. Schriber
- Department of Chemistry, Emory University, Atlanta, Georgia 30322, United States
| | - Tianyuan Zhang
- Department of Chemistry, Emory University, Atlanta, Georgia 30322, United States
| | - Boyi Zhang
- Center for Computational Quantum Chemistry, University of Georgia, Athens, Georgia 30602, United States
| | - Adam S. Abbott
- Center for Computational Quantum Chemistry, University of Georgia, Athens, Georgia 30602, United States
| | - Eric J. Berquist
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, United States
| | - Marvin H. Lechner
- Department of Chemistry, Technical University of Munich, 80333 Munich, Germany
| | - Leonardo A. Cunha
- The Technical Institute of Aeronautics, São José dos Campos, 12228-900, Brazil
| | - Alexander G. Heide
- Department of Chemistry, Bethel University, St. Paul, Minnesota 55112, United States
| | - Jonathan M. Waldrop
- Department of Chemistry and Biochemistry, Auburn University, Auburn, Alabama 36849, United States
| | - Tyler Y. Takeshita
- Department of Chemistry, University of California Berkeley, Berkeley, California 94720, United States
| | - Asem Alenaizan
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, United States
| | - Daniel Neuhauser
- Department of Chemistry and Biochemistry, University of California, Los Angeles, California 90095, United States
| | - Rollin A. King
- Department of Chemistry, Bethel University, St. Paul, Minnesota 55112, United States
| | - Andrew C. Simmonett
- National Institutes of Health - National Heart, Lung and Blood Institute, Laboratory of Computational Biology, 5635 Fishers Lane, T-900 Suite, Rockville, Maryland 20852, United States
| | - Justin M. Turney
- Center for Computational Quantum Chemistry, University of Georgia, Athens, Georgia 30602, United States
| | - Henry F. Schaefer
- Center for Computational Quantum Chemistry, University of Georgia, Athens, Georgia 30602, United States
| | | | - A. Eugene DePrince
- Department of Chemistry and Biochemistry, Florida State University, Tallahassee, Florida 32306-4390, United States
| | - T. Daniel Crawford
- Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, United States
| | - Konrad Patkowski
- Department of Chemistry and Biochemistry, Auburn University, Auburn, Alabama 36849, United States
| | - C. David Sherrill
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, United States
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Schriber JB, Evangelista FA. Adaptive Configuration Interaction for Computing Challenging Electronic Excited States with Tunable Accuracy. J Chem Theory Comput 2017; 13:5354-5366. [DOI: 10.1021/acs.jctc.7b00725] [Citation(s) in RCA: 56] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Jeffrey B. Schriber
- Department of Chemistry and
Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States
| | - Francesco A. Evangelista
- Department of Chemistry and
Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States
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Schriber JB, Evangelista FA. Communication: An adaptive configuration interaction approach for strongly correlated electrons with tunable accuracy. J Chem Phys 2016; 144:161106. [DOI: 10.1063/1.4948308] [Citation(s) in RCA: 161] [Impact Index Per Article: 20.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Jeffrey B. Schriber
- Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, USA
| | - Francesco A. Evangelista
- Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, USA
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