Statistical analysis of P-N clusters in Mo/VFe protein crystals using a bond valence method toward their electronic structures

RSC ADVANCES(2022)

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摘要
Nowadays, large numbers of MoFe proteins have been reported and their crystal data obtained by X-ray crystallography and uploaded to the Protein Data Bank (PDB). By big data analysis using a bond valence method, we make conclusions based on 79 selected P-N in all 119 P-clusters of 53 MoFe proteins and 10 P-clusters of 5 VFe proteins from all deposited crystallographic data of the PDB. In the condition of MoFe protein crystals, the resting state P-N clusters are proposed to have the formal oxidation state of 2Fe(iii)6Fe(ii), hiding two oxidized electron holes with high electron delocalization. The calculations show that Fe1, Fe2, Fe5, Fe6 and Fe7 perform unequivocally as Fe2+, and Fe3 is remarkably prone to Fe(iii), while Fe4 and Fe8 have different degrees of mixed valences. For P-N clusters in VFe protein crystals, Fe1, Fe2, Fe4, Fe5 and Fe6 tend to be Fe2+, but the electron distributions rearrange with Fe7 and Fe8 being more oxidized mixed valences, and Fe3 presenting a little more reductive mixed valence than that in MoFe proteins. In terms of spatial location, Fe3 and Fe6 in P-clusters of MoFe proteins are calculated as the most oxidized and reduced irons, which have the shortest distances from homocitrate in the FeMo-cofactor and [Fe4S4] cluster, respectively, and thus could function as potential electron transport sites. This work shows different electron distributions of P-N clusters in Mo/VFe protein crystals, from those obtained from previous data from solution with excess reducing agent from which it was concluded that P-N clusters are all ferrous according to Mossbauer and electron paramagnetic resonance spectra.
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