Identification of Antagonistic Action of Pyrrolizidine Alkaloids in Muscarinic Acetylcholine Receptor M1 by Computational Target Prediction Analysis

Publication type:
Journal article
Metadata:
Autoren
Autoren-URL
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=fis-test-1&SrcAuth=WosAPI&KeyUT=WOS:001151213800001&DestLinkType=FullRecord&DestApp=WOS_CPL
DOI
10.3390/ph17010080
eISSN
1424-8247
Externe Identifier
  • Clarivate Analytics Document Solution ID: GF3O9
  • PubMed Identifier: 38256913
Ausgabe der Veröffentlichung
1
Zeitschrift
PHARMACEUTICALS
Schlüsselwörter
  • alkaloids
  • computational biology
  • herbal medicine
  • natural products
  • neurotoxicity
  • phytotherapy
  • virtual drug screening
Artikelnummer
ARTN 80
Datum der Veröffentlichung
2024
Status
Published
Titel
Identification of Antagonistic Action of Pyrrolizidine Alkaloids in Muscarinic Acetylcholine Receptor M1 by Computational Target Prediction Analysis
Sub types
  • Article
Ausgabe der Zeitschrift
17

Data source: Web of Science (Lite)

Other metadata sources:
Abstract
<jats:p>Pyrrolizidine alkaloids (PAs) are one of the largest distributed classes of toxins in nature. They have a wide range of toxicity, such as hepatotoxicity, pulmonary toxicity, neuronal toxicity, and carcinogenesis. Yet, biological targets responsible for these effects are not well addressed. Using methods of computational biology for target identification, we tested more than 200 PAs. We used a machine-learning approach that applies structural similarity for target identification, ChemMapper, and SwissTargetPrediction. The predicted targets with high probabilities were muscarinic acetylcholine receptor M1. The predicted interactions between these two targets and PAs were further studied by molecular docking-based binding energies using AutoDock and VinaLC, which revealed good binding affinities. The PAs are bound to the same binding pocket as pirenzepine, a known M1 antagonist. These results were confirmed by in vitro assays showing that PAs increased the levels of intracellular calcium. We conclude that PAs are potential acetylcholine receptor M1 antagonists. This elucidates for the first time the serious neuro-oncological toxicities exerted by PA consumption.</jats:p>
Autoren
DOI
10.3390/ph17010080
eISSN
1424-8247
Ausgabe der Veröffentlichung
1
Zeitschrift
Pharmaceuticals
Sprache
en
Online publication date
2024
Paginierung
80 - 80
Status
Published online
Herausgeber
MDPI AG
Herausgeber URL
http://dx.doi.org/10.3390/ph17010080
Datum der Datenerfassung
2024
Titel
Identification of Antagonistic Action of Pyrrolizidine Alkaloids in Muscarinic Acetylcholine Receptor M1 by Computational Target Prediction Analysis
Ausgabe der Zeitschrift
17

Data source: Crossref

Abstract
Pyrrolizidine alkaloids (PAs) are one of the largest distributed classes of toxins in nature. They have a wide range of toxicity, such as hepatotoxicity, pulmonary toxicity, neuronal toxicity, and carcinogenesis. Yet, biological targets responsible for these effects are not well addressed. Using methods of computational biology for target identification, we tested more than 200 PAs. We used a machine-learning approach that applies structural similarity for target identification, ChemMapper, and SwissTargetPrediction. The predicted targets with high probabilities were muscarinic acetylcholine receptor M1. The predicted interactions between these two targets and PAs were further studied by molecular docking-based binding energies using AutoDock and VinaLC, which revealed good binding affinities. The PAs are bound to the same binding pocket as pirenzepine, a known M1 antagonist. These results were confirmed by in vitro assays showing that PAs increased the levels of intracellular calcium. We conclude that PAs are potential acetylcholine receptor M1 antagonists. This elucidates for the first time the serious neuro-oncological toxicities exerted by PA consumption.
Addresses
  • Department of Pharmaceutical Biology, Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg University, Staudinger Weg 5, 55128 Mainz, Germany.
Autoren
DOI
10.3390/ph17010080
eISSN
1424-8247
Externe Identifier
  • PubMed Identifier: 38256913
  • PubMed Central ID: PMC10818892
Funding acknowledgements
  • Ministry of Social Affairs,Labor, Health and Demography, Rheinland-Pfalz, Germany.: PoUvPA 633-2
  • Ministry of Social Affairs, Labor, Health and Demography, Rhineland–Palatinate, Germany: PoUvPA 633-2
Open access
true
ISSN
1424-8247
Ausgabe der Veröffentlichung
1
Zeitschrift
Pharmaceuticals (Basel, Switzerland)
Sprache
eng
Medium
Electronic
Online publication date
2024
Open access status
Open Access
Paginierung
80
Datum der Veröffentlichung
2024
Status
Published
Publisher licence
CC BY
Datum der Datenerfassung
2024
Titel
Identification of Antagonistic Action of Pyrrolizidine Alkaloids in Muscarinic Acetylcholine Receptor M1 by Computational Target Prediction Analysis.
Sub types
  • research-article
  • Journal Article
Ausgabe der Zeitschrift
17

Files

https://www.mdpi.com/1424-8247/17/1/80/pdf?version=1704717586 https://europepmc.org/articles/PMC10818892?pdf=render

Data source: Europe PubMed Central

Abstract
Pyrrolizidine alkaloids (PAs) are one of the largest distributed classes of toxins in nature. They have a wide range of toxicity, such as hepatotoxicity, pulmonary toxicity, neuronal toxicity, and carcinogenesis. Yet, biological targets responsible for these effects are not well addressed. Using methods of computational biology for target identification, we tested more than 200 PAs. We used a machine-learning approach that applies structural similarity for target identification, ChemMapper, and SwissTargetPrediction. The predicted targets with high probabilities were muscarinic acetylcholine receptor M1. The predicted interactions between these two targets and PAs were further studied by molecular docking-based binding energies using AutoDock and VinaLC, which revealed good binding affinities. The PAs are bound to the same binding pocket as pirenzepine, a known M1 antagonist. These results were confirmed by in vitro assays showing that PAs increased the levels of intracellular calcium. We conclude that PAs are potential acetylcholine receptor M1 antagonists. This elucidates for the first time the serious neuro-oncological toxicities exerted by PA consumption.
Date of acceptance
2024
Autoren
Autoren-URL
https://www.ncbi.nlm.nih.gov/pubmed/38256913
DOI
10.3390/ph17010080
Externe Identifier
  • PubMed Central ID: PMC10818892
Funding acknowledgements
  • Ministry of Social Affairs,Labor, Health and Demography, Rheinland-Pfalz, Germany.: PoUvPA 633-2
ISSN
1424-8247
Ausgabe der Veröffentlichung
1
Zeitschrift
Pharmaceuticals (Basel)
Schlüsselwörter
  • alkaloids
  • computational biology
  • herbal medicine
  • natural products
  • neurotoxicity
  • phytotherapy
  • virtual drug screening
Sprache
eng
Country
Switzerland
PII
ph17010080
Datum der Veröffentlichung
2024
Status
Published online
Titel
Identification of Antagonistic Action of Pyrrolizidine Alkaloids in Muscarinic Acetylcholine Receptor M1 by Computational Target Prediction Analysis.
Sub types
  • Journal Article
Ausgabe der Zeitschrift
17

Data source: PubMed

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