Figure 3.

Comparison of the CNN probability distributions for a, T, δ, K, and η (black) with the previously reported literature values (blue) where available: (i) SQ_B RC (L-H190-N_δ) – semiquinone (SQ) in the Q_B ubiquinone binding site of the reaction center from Rhodobacter sphaeroides interacting with N_δ of residue L-H190;²¹ (ii) SQ_B RC (L-G225-N_p) – same as previous for N_p of L-G225;²¹ (iii) SQ_H cyt aa₃ (H70-N_ε) – SQ in the Q_H high-affinity menaquinone binding site of the R70H mutant of cytochrome aa₃-600 menaquinol oxidase from Bacillus subtilis interacting with N_ε of residue H70;²² (iv) SQ_H cyt bo₃ (R71-N_ε) – semiquinone in the Q_H high-affinity ubiquinone binding site of the cytochrome bo₃ ubiquinol oxidase from Escherichia coli interacting with N_ε of residue R71;²³ (v) [2Fe-2S] rat mitoNEET (H87-N_δ) – reduced [2Fe-2S](Cys)₃(His)₁ cluster in rat mitoNEET interacting with N_δ of residue H87;²⁴ (vi) [2Fe-2S] rat mitoNEET (H87-N_ε) – same as previous for N_ε of residue H87;²⁴ [2Fe-2S] rat mitoNEET (N_p) – same as previous for N_p in the cluster environment;²⁴ (viii) VO²⁺ (Imidazole) – VO²⁺ ion interaction with coordinating imidazole ligand nitrogens;²⁵ and (ix) VO²⁺ (Histidine-N_α)₂ – VO²⁺ ion interaction with coordinating N_αH₂ of histidine ligands.²⁵ The final predictions and their standard deviation errors are determined by a Gaussian fit to the probability distributions (dashed red). It took ∼3 s for the machine learning algorithm to process the time-domain patterns and generate this figure on a desktop equipped with an Intel Core i5–4570 processor (3.2 GHz) and 16 GB of RAM.