If you have any problems related to the accessibility of any content (or if you want to request that a specific publication be accessible), please contact us at email@example.com.
Computational Study of Nonadiabatic Spin-Forbidden Processes in Metal-Sulfur Proteins
AuthorKaliakin, Danil S.
AdvisorVarganov, Sergey A.
AltmetricsView Usage Statistics
We investigate the role of nonadiabatic spin-forbidden transitions in the catalytic and electron transfer processes in the active sites of metal-sulfur proteins. We focus on two biologically important metal-sulfur proteins, namely the [NiFe]-hydrogenase enzyme capable of catalytic H2 oxidation and proton reduction, and the electron transfer protein rubredoxin. The synthetic analogs of [NiFe]-hydrogenase are the promising inexpensive alternative to platinum-based catalysts. Our studies indicate that nonadiabatic transitions between the electronic states with different spin multiplicities could be important for the catalytic activity of [NiFe]-hydrogenase. These transitions are mediated by spin-orbit coupling between the quasidegenerate singlet and triplet states of the Ni(II) center. As for rubredoxin, its ability to transfer electrons makes this small protein a promising starting model for the development of future self-sufficient biosensors and the novel catalysts. The presence of multiple low-lying electronic states with different spin multiplicities in the active site of rubredoxin indicates a possibility of nonadiabatic transitions during the electron transfer processes. The probabilities and the rates of nonadiabatic spin-forbidden transitions in the metal-sulfur proteins predicted using the nonadiabatic transition state theory (NA-TST). The NA-TST calculations require the knowledge of molecular properties at a minimum energy crossing point (MECP), an analog of transition state in the traditional transition state theory. Therefore, part of the work was dedicated to implementation of the MECP search algorithm for the fragment molecular orbital (FMO) method that can be applied to systems with thousands of atoms, including large models of metal-sulfur proteins. The last part of the dissertation is dedicated to the design and manufacture of the 3D-printed models of potential energy surfaces for different chemical reactions. These models proved to be valuable for the chemical dynamics and kinetics demonstrations in graduate and undergraduate chemistry classes.