METHODS
Data collection and curation . The dataset includes 514 redox potentials from 239 unique enzyme/cofactor pairs consisting of metal ions (Cu, Fe, Mo), flavins, hemes, and multinuclear iron-sulfur clusters. Proteins are indexed by their UniProt ID, and approximately half are associated with high-resolution structures deposited in the Protein Data Bank [51]. Redox potentials are normalized to the standard hydrogen electrode and pH-corrected to pH 7.0. Redox potentials were only included if the midpoint potential could unequivocally be assigned to a particular cofactor.
ProtReDox database construction . Redox potentials and associated data are stored in a Google Firebase Cloud Firestore database [52]. The ProtReDox website is rendered using the Firebase Web v.9 modular JavaScript SDK in combination with React.js (v. 18.2) (react.dev). The website user interface comprises a navigation, logo, searchable redox dataset table, and a form to input new redox potentials and associated information. User-contributed additions to the dataset will be marked for review and evaluated manually.
Feature-redox correlation analysis . To better understand the key features controlling redox potential, 486 features were calculated as previously described[53] for a set of 42 protein structures with type 1 copper sites with experimentally identified reduction potentials. These features covered ten categories of physicochemical properties based on how they were calculated: solvation, electrostatics, hydrogen bonding, van der Waals, geometry, pocket void, secondary structure of the backbone region of the protein directly interacting to the redox site, amino acid angles, pocket lining, and surface area. The property values for sites on different chains of the same protein structure were averaged. Any features for which all structures had the same value were removed, leaving 446 features. Pearson correlation coefficients between features and reduction potential were then calculated using the python library SciPy [54]. For each structure, the reduction potential with an experimental pH closest to the crystallization pH was selected. When no crystallization pH was available, the reduction potential with the most neutral pH was selected. These reduction potentials were then normalized to pH 7.0 for further analysis (eq. 1).
Mapping redox energetics on the SpAN . The SpAN is a network representation of protein electron transfer pathways with nodes corresponding to classes of protein microenvironments surrounding the redox cofactor (termed modules) and edges reflecting instances in the PDB where two modules are within electron transfer proximity (cofactor-cofactor distance < 14 Å). The generation of this network was described in our previous work [16, 17]. The 2020 version of the SpAN was used in this study.