AIM OF THE STUDY: This study aimed to use a computational target fishing approach to predict the possible therapeutic effect of Marantodes pumilum and evaluated their effectivity.
MATERIALS AND METHODS: This study involves a computational approach to identify the potential targets by using target fishing. Several databases were used: PubChem database to obtain the chemical structure of interested compounds; Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) server and the SWISSADME web tool to identify and select the compounds having drug-likeness properties; PharmMapper was used to identify top ten target protein of the selected compounds and Online Mendelian Inheritance in Man (OMIM) was used to predict human genetic problems; the gene id of top-10 proteins was obtained from UniProtKB to be analyzed by using GeneMANIA server to check the genes' function and their co-expression; Gene Pathway established by Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) of the selected targets were analyzed by using EnrichR server and confirmed by using DAVID (The Database for Annotation, Visualization and Integrated Discovery) version 6.8 and STRING database. All the interaction data was analyzed by Cytoscape version 3.7.2 software. The protein structure of most putative proteins was obtained from the RCSB protein data bank. Thedocking analysis was conducted using PyRx biological software v0.8 and illustrated by BIOVIA Discovery Studio Visualizer version 20.1.0. As a preliminary evaluation, a cell viability assay using Sulforhodamine B was conducted to evaluate the potential of the predicted therapeutic effect.
RESULTS: It was found that four studied compounds are highly correlated with three proteins: EFGR, CDK2, and ESR1. These proteins are highly associated with cancer pathways, especially breast cancer and prostate cancer. Qualitatively, cell proliferation assay conducted shown that the extract has IC50 of 88.69 μg/ml against MCF-7 and 66.51 μg/ml against MDA-MB-231.
CONCLUSIONS: Natural herbs are one of the most common forms of complementary and alternative medicine, and they play an important role in disease treatment. The results of this study show that in addition to being used traditionally to maintain women's health, the use of Marantodes pumilum indirectly has the potential to protect against the development of cancer cells, especially breast cancer. Therefore, further research is necessary to confirm the potential of this plant to be used in the development of anti-cancer drugs, especially for breast cancer.
OBJECTIVES: To measure the level of COVID-19 information overload (COVIO) and assess the association between COVIO and sociodemographic characteristics among the general public.
METHODS: A cross-sectional online survey was conducted between April and May 2020 using a modified Cancer Information Overload scale. The survey was developed and posted on four social media platforms. The data were only collected from those who consented to participate. COVIO score was classified into high vs. low using the asymmetrical distribution as a guide and conducted a binary logistic regression to examine the factors associated with COVIO.
RESULTS: A total number of 584 respondents participated in this study. The mean COVIO score of the respondents was 19.4 (± 4.0). Sources and frequency of receiving COVID-19 information were found to be significant predictors of COVIO. Participants who received information via the broadcast media were more likely to have high COVIO than those who received information via the social media (adjusted odds ratio ([aOR],14.599; 95% confidence interval [CI], 1.608-132.559; p = 0.017). Also, participants who received COVID-19 information every minute (aOR, 3.892; 95% CI, 1.124-13.480; p = 0.032) were more likely to have high COVIO than those who received information every week.
CONCLUSION: The source of information and the frequency of receiving COVID-19 information were significantly associated with COVIO. The COVID-19 information is often conflicting, leading to confusion and overload of information in the general population. This can have unfavorable effects on the measures taken to control the transmission and management of COVID-19 infection.