  Due to the highly complex chemical structure of biomolecules, the extensive
understanding of the electronic information for proteomics can be challenging.
Here, we constructed a charge transfer database at residue level derived from
millions of electronic structure calculations among 20x20 possible amino acid
side-chains combinations, which were extracted from available high-quality
structures of thousands of protein complexes. Then, the data driven network
(D2Net) analysis was proposed to quickly identify the critical residue or
residue groups for any possible protein complex. As an initial evaluation, we
applied this model to scrutinize the charge transfer networks for two randomly
selected proteins, which highlighted the most critical residues with large node
degrees as network hubs. This work may provide us a promising computional
protocol for topologically understanding the electronic structure information
in the growing number of high-quality experimental proteins structures, with
minor computational costs.
