Publications by authors named "Runqian Song"

Compound-specific isotope analysis (CSIA) for natural isotope ratios has been recognized as a promising tool to elucidate biodegradation pathways of organic pollutants by microbial enzymes by relating reported kinetic isotope effects (KIEs) to apparent KIEs (AKIEs) derived from bulk isotope fractionations (ε). However, for many environmental reactions, neither are the reference KIE ranges sufficiently narrow nor are the mechanisms elucidated to the point that rate-determining steps have been identified unequivocally. In this work, besides providing reference KIEs and rationalizing AKIEs, good relationships have been explained by DFT computations for diverse biodegradation pathways with known enzymatic models between the theoretical isotope fractionations (ε) from intrinsic KIEs on the rate-determining steps and the observed ε.

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Metabolism, especially by CYP450 enzymes, is the main reason for mediating the toxification and detoxification of xenobiotics in humans, while some uncommon metabolic pathways, especially for emerging pollutants, probably causing idiosyncratic toxicity are easily overlooked. The pollution of sulfonamide antibiotics in aqueous system has attracted increasing public attention. Hydroxylation of the central amine group can trigger a series of metabolic processes of sulfonamide antibiotics in humans; however, this work parallelly reported the coupling and fragmenting initiated by amino H-abstraction of sulfamethoxazole (SMX) catalyzed by human CYP450 enzymes.

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Aromatic amines, the widely used raw materials in industry, cause long-term exposure to human bodies. They can be metabolized by cytochrome P450 enzymes to form active electrophilic compounds, which will potentially react with nucleophilic DNA to exert carcinogenesis. The short lifetime and versatility of the oxidant (a high-valent iron (IV)-oxo species, compound I) of P450 enzymes prompts us to use theoretical methods to investigate the metabolism of aromatic amines.

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Biotransformation, especially by human CYP450 enzymes, plays a crucial role in regulating the toxicity of organic compounds in organisms, but is poorly understood for most emerging pollutants, as their numerous "unusual" biotransformation reactions cannot retrieve examples from the textbooks. Therefore, in order to predict the unknown metabolites with altering toxicological profiles, there is a realistic need to develop efficient methods to reveal the "unusual" metabolic mechanism of emerging pollutants. Combining experimental work with computational predictions has been widely accepted as an effective approach in studying complex metabolic reactions; however, the full quantum chemical computations may not be easily accessible for most environmentalists.

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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 -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.

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Precision biotransformation is an envisioned strategy offering detailed insights into biotransformation pathways in real environmental settings using experimentally guided high-accuracy quantum chemistry. Emerging pollutants, whose metabolites are easily overlooked but may cause idiosyncratic toxicity, are important targets of such a strategy. We demonstrate here that complex metabolic reactions of tris(1,3-dichloro-2-propyl) phosphate (TDCIPP) catalyzed by human CYP450 enzymes can be mapped via a three-step synergy strategy: (i) screening the possible metabolites via high-throughout (moderate-accuracy) computations; (ii) analyzing the proposed metabolites by human liver microsomes and recombinant human CYP450 enzymes; and (iii) rationalizing the experimental data via precise mechanisms using high-level targeted computations.

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