Oxidation of Arg‐410 promotes the elimination of human serum albumin
Abstract
The effect of the oxidation of amino acid residues on albumin on its in vivo elimination was investigated using mutants and oxidized HSAs. The single-residue mutants (H146A, K199A, W214A, R218H, R410A, Y411A) and oxidized HSAs were produced by the recombinant DNA techniques and incubation with a metal ion-catalyzed oxidation (MCO) system for 12, 24, 48 or 72 h. Pharmacokinetics were evaluated in mice after labeling with 111In. Structural and functional properties were examined by several spectroscopic techniques. Time-dependent increase in carbonyl group content resulted in increase in the liver clearance of oxidized HSAs. Slight decreases in alpha-helical content as the result of oxidation was induced by the increases in accessible hydrophobic areas and the net negative charge on the HSA molecule. No significant change in the pharmacokinetics and structural properties was observed for the W214A, R218H and Y411A mutants, but the properties for the H146A, K199A and R410A mutants were affected (extent of effect: R410A > K199A > H146A). The liver clearance of these proteins is closely correlated to hydrophobicity (r = 0.929, P < 0.01) and the net charge of the proteins (r=0.930, P < 0.01). The rate of elimination of HSA is closely related to the hydrophobicity and net charge of the molecule. Further, the R410A mutants had a short half-life and structure similar to oxidized HSA after oxidation. Therefore, the modification of Arg-410 via oxidative stress may promote the elimination of HSA.
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The breakdown of serum albumin is complicated by the fact that after oxidation, glycation, or binding of pro-oxidative substances, serum albumin loses its antioxidant capacity and is more rapidly degraded than reduced unbound serum albumin.
“The breakdown of serum albumin is complicated by the fact that after oxidation, glycation, or binding of pro‐oxidative substances, serum albumin loses its antioxidant capacity and is more rapidly degraded than reduced unbound serum albumin.79, 80, 81, 82, 83”
From Hypoalbuminemia: Pathogenesis and Clinical Significance (2019) · cites this paper as [82]
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- Authors
- Iwao, Y., Anraku, M., Yamasaki, K., Kragh-Hansen, U., Kawai, K., Maruyama, T., & Otagiri, M.
- Affiliations
- Kumamoto University (JP)
- Kanazawa University (JP)
- Corresponding author
- Otagiri, Masaki
- Venue
- Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics
- Publisher
- Elsevier BV
- Published
- 2006-04
- Volume
- 1764
- Issue
- 4
- Pages
- 743-749
- ISSN
- 1570-9639 (ISSN-L)
- OpenAlex
- W2078562148
- Cited by
- 53
- References
- 45
- Citations by year
- 2026: 2 · 2025: 1 · 2023: 3 · 2022: 2 · 2021: 5 · 2020: 1 · 2019: 1 · 2018: 2 · 2017: 1 · 2016: 2 · 2014: 5 · 2013: 5 · 2012: 3
- FWCI
- 1.50
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Ministry of Education, Culture, Sports, Science and Technology (14370759)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Interaction Studies and Fluorescence Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein purification and stability
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Hemoglobin structure and function
- Keywords
- human serum albumin, protein oxidation, pharmacokinetics, hepatic clearance, hydrophobicity, net charge, alpha-helix content, carbonyl compounds, oxidative stress, protein half-life
- MeSH terms
- Amino Acid Sequence, Animals, Arginine, Half-Life, Humans, Ketoprofen, Liver, Male, Oxidation-Reduction, Protein Conformation, Serum Albumin, Warfarin, Point Mutation, Mice, Hydrophobic and Hydrophilic Interactions
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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