Locating Minimum Energy Crossings of Different Spin States Using the Fragment Molecular Orbital Method.


Journal

Journal of chemical theory and computation
ISSN: 1549-9626
Titre abrégé: J Chem Theory Comput
Pays: United States
ID NLM: 101232704

Informations de publication

Date de publication:
12 Nov 2019
Historique:
pubmed: 14 9 2019
medline: 21 11 2019
entrez: 14 9 2019
Statut: ppublish

Résumé

Spin-dependent processes involving nonadiabatic transitions between electronic states with different spin multiplicities play important roles in the chemistry of complex systems. The rates of these processes can be predicted based on the molecular properties at the minimum energy crossing point (MECP) between electronic states. We present the development of the MECP search technique within the fragment molecular orbital (FMO) method applicable to large complex systems. The accuracy and scalability of the new method is demonstrated on several models of the metal-sulfur protein rubredoxin. The effect of the model size on the MECP geometry and relative energy is discussed. The fragment energy decomposition and spin density delocalization analyses reveal how different protein residues and solvent molecules contribute to stabilization of the spin states. The developed FMO-MECP method can help to clarify the role of nonadiabatic spin-dependent processes in complex systems and can be used for designing mutations aimed at controlling these processes in metalloproteins, including spin-dependent catalysis and electron transfer.

Identifiants

pubmed: 31518121
doi: 10.1021/acs.jctc.9b00641
doi:

Substances chimiques

Rubredoxins 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

6074-6084

Auteurs

Danil S Kaliakin (DS)

Department of Chemistry , University of Nevada, Reno , 1664 N. Virginia Street , Reno , Nevada 89557-0216 , United States.

Dmitri G Fedorov (DG)

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.

Yuri Alexeev (Y)

Computational Science Division and Argonne Leadership Computing Facility , Argonne National Laboratory , Argonne , Illinois 60439 , United States.

Sergey A Varganov (SA)

Department of Chemistry , University of Nevada, Reno , 1664 N. Virginia Street , Reno , Nevada 89557-0216 , United States.

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Classifications MeSH