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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Main Authors: Briones, Yumi L., Young, Alexander T., Dayrit, Fabian M, De Jesus, Armando Jerome, Rojas, Nina Rosario L
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Published: Archīum Ateneo 2021
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Online Access:https://archium.ateneo.edu/chemistry-faculty-pubs/164
https://archium.ateneo.edu/cgi/viewcontent.cgi?article=1163&context=chemistry-faculty-pubs
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Institution: Ateneo De Manila University
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spelling ph-ateneo-arc.chemistry-faculty-pubs-11632022-02-07T10:09:41Z 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 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. 2021-12-13T08:00:00Z text application/pdf https://archium.ateneo.edu/chemistry-faculty-pubs/164 https://archium.ateneo.edu/cgi/viewcontent.cgi?article=1163&context=chemistry-faculty-pubs Chemistry Faculty Publications Archīum Ateneo network visualization network pharmacology reverse screening medicinal plants phytochemicals Momordica charantia (bitter gourd) colorectal cancer Chemistry Diseases Oncology Pharmacology, Toxicology and Environmental Health Plant Sciences
institution Ateneo De Manila University
building Ateneo De Manila University Library
continent Asia
country Philippines
Philippines
content_provider Ateneo De Manila University Library
collection archium.Ateneo Institutional Repository
topic network visualization
network pharmacology
reverse screening
medicinal plants
phytochemicals
Momordica charantia (bitter gourd)
colorectal cancer
Chemistry
Diseases
Oncology
Pharmacology, Toxicology and Environmental Health
Plant Sciences
spellingShingle network visualization
network pharmacology
reverse screening
medicinal plants
phytochemicals
Momordica charantia (bitter gourd)
colorectal cancer
Chemistry
Diseases
Oncology
Pharmacology, Toxicology and Environmental Health
Plant Sciences
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
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.
format text
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.
title Visualizing Phytochemical-Protein Interaction Networks: Momordica charantia and Cancer
title_short 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_sort visualizing phytochemical-protein interaction networks: momordica charantia and cancer
publisher Archīum Ateneo
publishDate 2021
url https://archium.ateneo.edu/chemistry-faculty-pubs/164
https://archium.ateneo.edu/cgi/viewcontent.cgi?article=1163&context=chemistry-faculty-pubs
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