Literature DB >> 22058661

Parameterization of a B3LYP specific correction for non-covalent interactions and basis set superposition error on a gigantic dataset of CCSD(T) quality non-covalent interaction energies.

Severin T Schneebeli1, Arteum D Bochevarov, Richard A Friesner.   

Abstract

A vast number of non-covalent interaction energies at the counterpoise corrected CCSD(T) level have been collected from the literature to build a diverse new dataset. The whole dataset, which consists of 2027 CCSD(T) energies, includes most of the published data at this level. A large subset of the data was then used to train a novel, B3LYP specific, empirical correction scheme for non-covalent interactions and basis set superposition error (abbreviated as B3LYP-MM). Results obtained with our new correction scheme were directly compared to benchmark results obtained with B3LYP-D3(1) and M06-2X(2) (two popular density functions designed specifically to accurately model non-covalent interactions). For non-covalent complexes dominated by dispersion or dipole-dipole interactions all three tested methods give accurate results with the medium size aug-cc-pVDZ(3-6) basis set with MUE's of 0.27 (B3LYP-MM), 0.32 (B3LYP-D3) and 0.47 kcal/mol (M06-2X) (with explicit counterpoise corrections). These results validate both B3LYP-D3 and M06-2X for interactions of this type using a much larger data set than was presented in prior work. However, our new dispersion correction scheme shows some clear advantages for dispersion and dipole-dipole dominated complexes with the small LACVP* basis set, which is very popular in use due to its low associated computational cost: The MUE for B3LYP-MM with the LACVP* basis set for this subset of complexes (without explicit counterpoise corrections) is only 0.28 kcal/mol, compared to 0.65 kcal/mol for M06-2X or 1.16 kcal/mol for B3LYP-D3. Additionally, our new correction scheme also shows major improvements in accuracy for hydrogen-bonded systems and for systems involving ionic interactions, for example cation-π interactions. Compared to B3LYP-D3 and M06-2X, we also find that our new B3LYP-MM correction scheme gives results of higher or equal accuracy for a large dataset of conformer energies of di- and tripeptides, sugars, and cysteine.

Entities:  

Year:  2011        PMID: 22058661      PMCID: PMC3206731          DOI: 10.1021/ct100651f

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  31 in total

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Authors:  Mutasem Omar Sinnokrot; C David Sherrill
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Journal:  J Chem Phys       Date:  2005-04-08       Impact factor: 3.488

3.  Semiempirical GGA-type density functional constructed with a long-range dispersion correction.

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Journal:  J Comput Chem       Date:  2006-11-30       Impact factor: 3.376

4.  Localized orbital corrections for the calculation of ionization potentials and electron affinities in density functional theory.

Authors:  Eric H Knoll; Richard A Friesner
Journal:  J Phys Chem B       Date:  2006-09-28       Impact factor: 2.991

5.  A unified density-functional treatment of dynamical, nondynamical, and dispersion correlations.

Authors:  Axel D Becke; Erin R Johnson
Journal:  J Chem Phys       Date:  2007-09-28       Impact factor: 3.488

6.  An efficient algorithm for the density-functional theory treatment of dispersion interactions.

Authors:  Jürgen Gräfenstein; Dieter Cremer
Journal:  J Chem Phys       Date:  2009-03-28       Impact factor: 3.488

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Authors:  S K Burley; G A Petsko
Journal:  Science       Date:  1985-07-05       Impact factor: 47.728

8.  Localized orbital corrections for the calculation of barrier heights in density functional theory.

Authors:  Michelle Lynn Hall; Dahlia A Goldfeld; Arteum D Bochevarov; Richard A Friesner
Journal:  J Chem Theory Comput       Date:  2009-11-10       Impact factor: 6.006

9.  Convergence of the CCSD(T) Correction Term for the Stacked Complex Methyl Adenine-Methyl Thymine: Comparison with Lower-Cost Alternatives.

Authors:  M Pitoňák; T Janowski; P Neogrády; P Pulay; P Hobza
Journal:  J Chem Theory Comput       Date:  2009-07-14       Impact factor: 6.006

10.  Structures and interaction energies of stacked graphene-nucleobase complexes.

Authors:  Jens Antony; Stefan Grimme
Journal:  Phys Chem Chem Phys       Date:  2008-03-05       Impact factor: 3.676

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  12 in total

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Authors:  Dmitry Lupyan; Yuriy A Abramov; Woody Sherman
Journal:  J Comput Aided Mol Des       Date:  2012-10-06       Impact factor: 3.686

Review 2.  Semiempirical Quantum Mechanical Methods for Noncovalent Interactions for Chemical and Biochemical Applications.

Authors:  Anders S Christensen; Tomáš Kubař; Qiang Cui; Marcus Elstner
Journal:  Chem Rev       Date:  2016-04-13       Impact factor: 60.622

3.  Hydrogen-Bond-Dependent Conformational Switching: A Computational Challenge from Experimental Thermochemistry.

Authors:  James Luccarelli; Robert S Paton
Journal:  J Org Chem       Date:  2019-01-09       Impact factor: 4.354

4.  A Minimum Quantum Chemistry CCSD(T)/CBS Data Set of Dimeric Interaction Energies for Small Organic Functional Groups: Heterodimers.

Authors:  Hsing-Hsiang Huang; Yi-Siang Wang; Sheng D Chao
Journal:  ACS Omega       Date:  2022-05-31

5.  Cation-π interactions of methylated ammonium ions: a quantum mechanical study.

Authors:  Chaya Rapp; Elizabeth Goldberger; Nasim Tishbi; Rachel Kirshenbaum
Journal:  Proteins       Date:  2014-02-18

6.  S66: A Well-balanced Database of Benchmark Interaction Energies Relevant to Biomolecular Structures.

Authors:  Jan Rezáč; Kevin E Riley; Pavel Hobza
Journal:  J Chem Theory Comput       Date:  2011-07-01       Impact factor: 6.006

7.  The price of flexibility - a case study on septanoses as pyranose mimetics.

Authors:  Christoph P Sager; Brigitte Fiege; Pascal Zihlmann; Raghu Vannam; Said Rabbani; Roman P Jakob; Roland C Preston; Adam Zalewski; Timm Maier; Mark W Peczuh; Beat Ernst
Journal:  Chem Sci       Date:  2017-11-08       Impact factor: 9.825

8.  Theoretical insight into the interaction between SnX2 (X = H, F, Cl, Br, I) and benzene.

Authors:  Piotr Matczak
Journal:  J Mol Model       Date:  2016-08-15       Impact factor: 1.810

9.  Precise through-space control of an abiotic electrophilic aromatic substitution reaction.

Authors:  Kyle E Murphy; Jessica L Bocanegra; Xiaoxi Liu; H-Y Katharine Chau; Patrick C Lee; Jianing Li; Severin T Schneebeli
Journal:  Nat Commun       Date:  2017-04-05       Impact factor: 17.694

10.  Electron density learning of non-covalent systems.

Authors:  Alberto Fabrizio; Andrea Grisafi; Benjamin Meyer; Michele Ceriotti; Clemence Corminboeuf
Journal:  Chem Sci       Date:  2019-09-09       Impact factor: 9.825

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