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Visualizing Phytochemical-Protein Interaction Networks: Momordica charantia and Cancer

The in silico study of medicinal plants is a rapidly growing field. Techniques such as reverse screening and network pharmacology are used to study the complex cellular action of medicinal plants against disease. However, it is difficult to produce a meaningful visualization of phytochemical-protein...

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Autores principales: Briones, Yumi L., Young, Alexander T., Dayrit, Fabian M., De Jesus, Armando Jerome, Rojas, Nina Rosario L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9580883/
https://www.ncbi.nlm.nih.gov/pubmed/36303742
http://dx.doi.org/10.3389/fbinf.2021.768886
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author Briones, Yumi L.
Young, Alexander T.
Dayrit, Fabian M.
De Jesus, Armando Jerome
Rojas, Nina Rosario L.
author_facet Briones, Yumi L.
Young, Alexander T.
Dayrit, Fabian M.
De Jesus, Armando Jerome
Rojas, Nina Rosario L.
author_sort Briones, Yumi L.
collection PubMed
description The in silico study of medicinal plants is a rapidly growing field. Techniques such as reverse screening and network pharmacology are used to study the complex cellular action of medicinal plants against disease. However, it is difficult to produce a meaningful visualization of phytochemical-protein interactions (PCPIs) in the cell. This study introduces a novel workflow combining various tools to visualize a PCPI network for a medicinal plant against a disease. The five steps are 1) phytochemical compilation, 2) reverse screening, 3) network building, 4) network visualization, and 5) evaluation. The output is a PCPI network that encodes multiple dimensions of information, including subcellular location, phytochemical class, pharmacokinetic data, and prediction probability. As a proof of concept, we built a PCPI network for bitter gourd (Momordica charantia L.) against colorectal cancer. The network and workflow are available at https://yumibriones.github.io/network/. The PCPI network highlights high-confidence interactions for further in vitro or in vivo study. The overall workflow is broadly transferable and can be used to visualize the action of other medicinal plants or small molecules against other diseases.
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spelling pubmed-95808832022-10-26 Visualizing Phytochemical-Protein Interaction Networks: Momordica charantia and Cancer Briones, Yumi L. Young, Alexander T. Dayrit, Fabian M. De Jesus, Armando Jerome Rojas, Nina Rosario L. Front Bioinform Bioinformatics The in silico study of medicinal plants is a rapidly growing field. Techniques such as reverse screening and network pharmacology are used to study the complex cellular action of medicinal plants against disease. However, it is difficult to produce a meaningful visualization of phytochemical-protein interactions (PCPIs) in the cell. This study introduces a novel workflow combining various tools to visualize a PCPI network for a medicinal plant against a disease. The five steps are 1) phytochemical compilation, 2) reverse screening, 3) network building, 4) network visualization, and 5) evaluation. The output is a PCPI network that encodes multiple dimensions of information, including subcellular location, phytochemical class, pharmacokinetic data, and prediction probability. As a proof of concept, we built a PCPI network for bitter gourd (Momordica charantia L.) against colorectal cancer. The network and workflow are available at https://yumibriones.github.io/network/. The PCPI network highlights high-confidence interactions for further in vitro or in vivo study. The overall workflow is broadly transferable and can be used to visualize the action of other medicinal plants or small molecules against other diseases. Frontiers Media S.A. 2021-12-13 /pmc/articles/PMC9580883/ /pubmed/36303742 http://dx.doi.org/10.3389/fbinf.2021.768886 Text en Copyright © 2021 Briones, Young, Dayrit, De Jesus and Rojas. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Bioinformatics
Briones, Yumi L.
Young, Alexander T.
Dayrit, Fabian M.
De Jesus, Armando Jerome
Rojas, Nina Rosario L.
Visualizing Phytochemical-Protein Interaction Networks: Momordica charantia and Cancer
title Visualizing Phytochemical-Protein Interaction Networks: Momordica charantia and Cancer
title_full Visualizing Phytochemical-Protein Interaction Networks: Momordica charantia and Cancer
title_fullStr Visualizing Phytochemical-Protein Interaction Networks: Momordica charantia and Cancer
title_full_unstemmed Visualizing Phytochemical-Protein Interaction Networks: Momordica charantia and Cancer
title_short Visualizing Phytochemical-Protein Interaction Networks: Momordica charantia and Cancer
title_sort visualizing phytochemical-protein interaction networks: momordica charantia and cancer
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9580883/
https://www.ncbi.nlm.nih.gov/pubmed/36303742
http://dx.doi.org/10.3389/fbinf.2021.768886
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