Computational Investigation of the Bisphenolic Drug Metabolism by Cytochrome P450: What Factors Favor Intramolecular Phenol Coupling

CHEMICAL RESEARCH IN TOXICOLOGY(2022)

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摘要
Intramolecular phenol coupling reactions of alkaloids can lead to active metabolites catalyzed by the mammalian cytochrome P450 enzyme (P450); however, the mechanistic knowledge of such an "unusual" process is lacking. This work performs density functional theory computations to reveal the P450-mediated metabolic pathway leading from R-reticuline to the morphine precursor salutaridine by exploring possible intramolecular phenol coupling mechanisms involving diradical coupling, radical addition, and electron transfer. The computed results show that the outer-sphere electron transfer with a high barrier (>20.0 kcal/mol) is unlikely to happen. However, for intersphere intramolecular phenol coupling, it reveals that intramolecular phenol coupling of R-reticuline proceeds via the diradical mechanism consecutively by compound I and protonated compound II of P450 rather than the radical addition mechanism. The existence of a much higher radical rebound barrier than that of H-abstraction in the quartet high-spin state can endow the R- reticuline phenoxy radical with a sufficient lifetime to enable intramolecular phenol coupling, while the H-abstraction/radical rebound mode with a negligible rebound barrier leading to phenol hydroxylation can only happen in the doublet low-spin state. Therefore, the ratio [coupling]/[hydroxylation] can be approximately reflected by the relative yield of the high-spin and low-spin H- abstraction by P450, which thus can provide a theoretical ratio of 16:1 for R-reticuline, which is in accordance with previous experimental results. Especially, the high rebound barrier of the phenoxy radical derived from the weak electron-donating ability of the phenoxy radical is revealed as an intrinsic nature. Therefore, the revealed intramolecular phenol coupling mechanism can be potentially extended to several other bisphenolic drugs to infer groups of unexpected metabolites in organisms.
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