Abstract
The bond-valence model is a reliable way to validate assumed oxidation states based on structural data. It has successfully been employed for analyzing metal-binding sites in macromolecule structures. However, inconsistent results for heme-based structures suggest that some widely used bond-valence R0 parameters may need to be adjusted in certain cases. Given the large number of experimental crystal structures gathered since these initial parameters were determined and the similarity of binding sites in organic compounds and macromolecules, the Cambridge Structural Database (CSD) is a valuable resource for refining metal-organic bond-valence parameters. R0 bond-valence parameters for iron(II), iron(III) and other metals have been optimized based on an automated processing of all CSD crystal structures. Almost all R0 bond-valence parameters were reproduced, except for iron-nitrogen bonds, for which distinct R0 parameters were defined for two observed subpopulations, corresponding to low-spin and high-spin states, of iron in both oxidation states. The significance of this data-driven method for parameter discovery, and how the spin state affects the interpretation of heme-containing proteins and iron-binding sites in macromolecular structures, are discussed.
Highlights
The bond-valence model relates the oxidation number of an atom to its immediate surroundings, and as such has been indispensable in a multitude of structural applications (Brown, 2009), including the analysis of metal-binding sites in proteins (Muller et al, 2003)
In cases involving iron and nitrogen, such as structures containing heme, we consistently obtained bond-valence sums that were significantly different from known oxidation states, prompting us to attempt a re-evaluation of bondvalence R0 parameters for iron-binding sites
Proteins and other large biological molecules possess metalbinding environments that are more similar to metal–organics than to inorganic minerals, and so Cambridge Structural Database (CSD)-derived data should be preferable over Inorganic Crystal Structure Database (ICSD)-derived data for modeling macromolecular metal-binding sites
Summary
The bond-valence model relates the oxidation number of an atom to its immediate surroundings, and as such has been indispensable in a multitude of structural applications (Brown, 2009), including the analysis of metal-binding sites in proteins (Muller et al, 2003). Proteins and other large biological molecules possess metalbinding environments that are more similar to metal–organics than to inorganic minerals, and so CSD-derived data should be preferable over ICSD-derived data for modeling macromolecular metal-binding sites. To this end, we have chosen the CSD as the starting point for our re-evaluation of bondvalence R0 parameters, since it contains a vast and diverse set of iron-binding sites in organic crystal structures with a much higher reliability than those observed in macromolecular crystal structures. The same protocol was applied to several other metals (Na, Mg, K, Ca and Zn), and in all these cases our values derived from the same data-driven procedure agreed with the previous parameters within statistical error
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