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.
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