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Tryptophan extends the life of cytochrome P450.

Raheleh RavanfarYuling ShengHarry B GrayJay R Winkler
Published in: Proceedings of the National Academy of Sciences of the United States of America (2023)
Powerfully oxidizing enzymes need protective mechanisms to prevent self-destruction. The flavocytochrome P450 BM3 from Priestia megaterium (P450 BM3 ) is a self-sufficient monooxygenase that hydroxylates fatty acid substrates using O 2 and NADPH as co-substrates. Hydroxylation of long-chain fatty acids (≥C 14 ) is well coupled to O 2 and NADPH consumption, but shorter chains (≤C 12 ) are more poorly coupled. Hydroxylation of p -nitrophenoxydodecanoic acid by P450 BM3 produces a spectrophotometrically detectable product wherein the coupling of NADPH consumption to product formation is just 10%. Moreover, the rate of NADPH consumption is 1.8 times that of O 2 consumption, indicating that an oxidase uncoupling pathway is operative. Measurements of the total number of enzyme turnovers before inactivation (TTN) indicate that higher NADPH concentrations increase TTN. At lower NADPH levels, added ascorbate increases TTN, while a W96H mutation leads to a decrease. The W96 residue is about 7 Å from the P450 BM3 heme and serves as a gateway residue in a tryptophan/tyrosine (W/Y) hole transport chain from the heme to a surface tyrosine residue. The data indicate that two oxidase pathways protect the enzyme from damage by intercepting the powerfully oxidizing enzyme intermediate (Compound I) and returning it to its resting state. At high NADPH concentrations, reducing equivalents from the flavoprotein are delivered to Compound I by the usual reductase pathway. When NADPH is not abundant, however, oxidizing equivalents from Compound I can traverse a W/Y chain, arriving at the enzyme surface where they are scavenged by reductants. Ubiquitous tryptophan/tyrosine chains in highly oxidizing enzymes likely perform similar protective functions.
Keyphrases
  • reactive oxygen species
  • fatty acid
  • resting state
  • functional connectivity
  • electronic health record
  • deep learning
  • machine learning
  • big data