How do metabolites differ from their parent molecules and how are they excreted?
Abstract
Understanding which physicochemical properties, or property distributions, are favorable for successful design and development of drugs, nutritional supplements, cosmetics, and agrochemicals is of great importance. In this study we have analyzed molecules from three distinct chemical spaces (i) approved drugs, (ii) human metabolites, and (iii) traditional Chinese medicine (TCM) to investigate four aspects determining the disposition of small organic molecules. First, we examined the physicochemical properties of these three classes of molecules and identified characteristic features resulting from their distinctive biological functions. For example, human metabolites and TCM molecules can be larger and more hydrophobic than drugs, which makes them less likely to cross membranes. We then quantified the shifts in physicochemical property space induced by metabolism from a holistic perspective by analyzing a data set of several thousand experimentally observed metabolic trees. Results show how the metabolic system aims to retain nutrients/micronutrients while facilitating a rapid elimination of xenobiotics. In the third part we compared these global shifts with the contributions made by individual metabolic reactions. For better resolution, all reactions were classified into phase I and phase II biotransformations. Interestingly, not all metabolic reactions lead to more hydrophilic molecules. We were able to identify biotransformations leading to an increase of logP by more than one log unit, which could be used for the design of drugs with enhanced efficacy. The study closes with the analysis of the physicochemical properties of metabolites found in the bile, faeces, and urine. Metabolites in the bile can be large and are often negatively charged. Molecules with molecular weight >500 Da are rarely found in the urine, and most of these large molecules are charged phase II conjugates.
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Recently developed bioinformatics approaches aim to narrow the number of possible candidate structures matching an unknown query metabolite by taking into account the chemical and biological background of the sample.
“Moreover, recently developed bioinformatics approaches aim to narrow the number of possible candidate structures that match with an unknown query metabolite by taking into account the chemical and biological background of the sample (164).”
From The food metabolome: a window over dietary exposure (2014) · cites this paper as [164]
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The food metabolome: a window over dietary exposure
Scalbert, A., Brennan, L., Manach, C., Andres-Lacueva, C., Dragsted, L. O., Draper, J., Rappaport, S. M., van der Hooft, J. J., & Wishart, D. S. (2014) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.113.076133 · Cited by 519 · see citing works
- Authors
- Kirchmair, J., Howlett, A., Peironcely, J. E., Murrell, D. S., Williamson, M. J., Adams, S. E., Hankemeier, T., van Buren, L., Duchateau, G., Klaffke, W., & Glen, R. C.
- Affiliations
- University of Cambridge (GB)
- Leiden University (NL)
- Unilever Centre for Molecular Sciences Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, United Kingdom
- Unilever Research & Development, Olivier van Noortlaan, 3133 AT Vlaardingen, The Netherlands
- Unilever Research and Development Vlaardingen (NL)
- Corresponding author
- Glen, Robert C.
- Venue
- Journal of Chemical Information and Modeling
- Publisher
- American Chemical Society (ACS)
- Published
- 2013-01-25
- Volume
- 53
- Issue
- 2
- Pages
- 354-367
- ISSN
- 1549-9596 (ISSN-L)
- 1549-960X
- OpenAlex
- W1987494660
- Cited by
- 43
- References
- 46
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 1 · 2023: 2 · 2022: 5 · 2021: 4 · 2020: 4 · 2019: 3 · 2018: 3 · 2017: 3 · 2016: 1 · 2015: 3 · 2014: 4 · 2013: 5
- FWCI
- 4.74
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Chemical Information and Modeling (publishedVersion)
- PubMed (publishedVersion)
- TNO Repository (submittedVersion)
- Repository hosted by TU Delft Library (TU Delft) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmacogenetics and Drug Metabolism
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Keywords
- drug metabolites, human metabolites, traditional Chinese medicine, physicochemical properties, biotransformation, phase I metabolism, phase II conjugation, logD, xenobiotic removal, bile metabolites, urinary metabolites, fecal metabolites, drug design, molecular weight
- MeSH terms
- Bile, Biotransformation, Pharmaceutical Preparations, Drugs, Chinese Herbal, Feces, Humans, Small Molecule Libraries, Metabolome, Drug Discovery, Databases, Pharmaceutical
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