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231226s2023 xx |||||o 00| ||eng c |
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|a 10.1002/jcc.26927
|2 doi
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|a pubmed24n1138.xml
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|a (DE-627)NLM341623938
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|a (NLM)35640228
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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|a Raßpe-Lange, Lukas
|e verfasserin
|4 aut
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|a Geometrical benchmarking and analysis of redox potentials of copper(I/II) guanidine-quinoline complexes
|b Comparison of semi-empirical tight-binding and DFT methods and the challenge of describing the entatic state (part III)
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|c 2023
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
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|2 rdacarrier
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|a Date Completed 02.01.2023
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|a Date Revised 31.03.2023
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a © 2022 The Authors. Journal of Computational Chemistry published by Wiley Periodicals LLC.
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|a Copper guanidine-quinoline complexes are an important class of bioinorganic complexes that find utilization in electron and atom transfer processes. By substitution of functional groups on the quinoline moiety the electron transfer abilities of these complexes can be tuned. In order to explore the full substitution space by simulations, the accurate theoretical description of the effect of functional groups is essential. In this study, we compare three different methods for the theoretical description of the structures. We use the semi-empirical tight-binding method GFN2-xTB, the density functional TPSSh and the double-hybrid functional B2PLYP. We evaluate the methods on five different complex pairs (Cu(I) and Cu(II) complexes), and compare how well calculated energies can predict the redox potentials. We find even though B2PLYP and TPSSh yield better accordance with the experimental structures. GFN2-xTB performs surprisingly well in the geometry optimization at a fraction of the computational cost. TPSSh offers a good compromise between computational cost and accuracy of the redox potential for real-life complexes
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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|a DFT
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|a copper
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|a guanidines
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|a redox potentials
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|a semi-empirical tight-binding
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|a Copper
|2 NLM
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| 650 |
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|a 789U1901C5
|2 NLM
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| 650 |
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|a Guanidine
|2 NLM
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| 650 |
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|a JU58VJ6Y3B
|2 NLM
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| 650 |
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|a Quinolines
|2 NLM
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| 700 |
1 |
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|a Hoffmann, Alexander
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Gertig, Christoph
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Heck, Joshua
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Leonhard, Kai
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Herres-Pawlis, Sonja
|e verfasserin
|4 aut
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| 773 |
0 |
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|i Enthalten in
|t Journal of computational chemistry
|d 1984
|g 44(2023), 3 vom: 30. Jan., Seite 319-328
|w (DE-627)NLM098138448
|x 1096-987X
|7 nnns
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| 773 |
1 |
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|g volume:44
|g year:2023
|g number:3
|g day:30
|g month:01
|g pages:319-328
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|u http://dx.doi.org/10.1002/jcc.26927
|3 Volltext
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|h 319-328
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