TY - JOUR
T1 - Visualizing Phytochemical-Protein Interaction Networks: Momordica charantia and Cancer
T2 - Momordica charantia and Cancer
AU - Briones, Yumi L.
AU - Young, Alexander T.
AU - Dayrit, Fabian M
AU - De Jesus, Armando Jerome
AU - Rojas, Nina Rosario L
AU - de Jesus, Armando Jerome
N1 - Briones, Y. L., Young, A. T., Dayrit, F. M., De Jesus, A. J., & Rojas, N. R. L. (2021). Visualizing phytochemical-protein interaction networks: Momordica charantia and cancer. Frontiers in Bioinformatics, 1. https://doi.org/10.3389/fbinf.2021.768886
PY - 2021/12/13
Y1 - 2021/12/13
N2 - 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.
AB - 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.
KW - network visualization
KW - network pharmacology
KW - reverse screening
KW - medicinal plants
KW - phytochemicals
KW - Momordica charantia (bitter gourd)
KW - colorectal cancer
UR - https://archium.ateneo.edu/chemistry-faculty-pubs/164
UR - http://www.scopus.com/inward/record.url?scp=85174814682&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85174814682&partnerID=8YFLogxK
M3 - Article
VL - 1
JO - Chemistry Faculty Publications
JF - Chemistry Faculty Publications
M1 - 768886
ER -