Back

Computational Analysis of Human Cysteine Redox Proteoforms Reveals Novel Insights

Cobley, J. N.; Chatzinikolaou, P. N.; Schmidt, C. A.

2024-09-19 biochemistry
10.1101/2024.09.18.613618 bioRxiv
Show abstract

Since cysteine redox proteoforms (i) are virtually unstudied, we derived novel insights by computationally analysing the human proteome. Our analysis revealed a vast, effectively infinite, theoretical i space housing 3.02 x 10169 unique cysteine redox proteoforms. For >80% and 99% of the human proteome, the i space comprises 6.83 x 108 and 1.76 x 1031 unique proteoforms, respectively. The heterogenous distribution of the i space by gene ontology terms, suggests, but does not prove, functional speciation. To theoretically limit the number of cysteine redox proteoforms that can be "downloaded" from the abstract i "cloud", we implement novel equations. Protein copy numbers limit the i space by 161-logs to 4.04 x 107 unique cysteine redox proteoforms per HeLa cell. An immutable law: the number of cysteine redox proteoform molecules (Ni) must equal the number of cysteine-containing protein molecules. We compute an Ni value of 1.70 x 109 per HeLa cell. While Ni will be displaced from thermodynamic equilibrium towards the reduced state (e.g., {approx}90%-reduced), it is possible that the number of partially oxidised cysteine redox proteoform molecules is in the order of 106-8 per HeLa cell. Consistent with this, 100%-oxidised forms were observed in 60% of the proteins studied to date. Our analysis advances understanding of redox biology at the proteoform level.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.