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.