In-silico investigation of curcumin drug-likeness, gene-targets and prognostic relevance of the targets in panels of human cancer cohorts

David B Oshevire 1, Aishatu Mustapha 2, Blessing U. Alozieuwa 3, Hassana H. Badeggi 2, Abdulfatai Ismail 4, Opeyemi N. Hassan 5, Peter I Ugwunnaji 6, Jonathan Ibrahim 7, Bashir Lawal 8, * and Eustace B. Berinyu 9

1 Senior Medical Officer, Hayok Medicare, Abuja, Nigeria.
2 Biological Science Department, Niger State Polytechnic Zungeru, Nigeria.
3 Veritas University Abuja, Bwari, FCT-Abuja, P.M.B. 7084.
4 Department of Animal Biology, Federal University of Technology Minna, Nigeria.
5 Centre International Universitaire Des Meilleurs (C.I.U.M), Bestower International University Seme-Podji-Republique Du Benin.
6Department of Chemistry, Michael Okpara University of Agriculture, Umudike, P.M.B 7267, Umuahia, Abia State, Nigeria
7Gombe State College of Health Science and Technology, Kaltungo, Nigeria
8Graduate Institute for Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
9 Faculty of Medicine and Biomedical Science, University of Yaoundé 1, Cameroon.
 
Research Article
GSC Biological and Pharmaceutical Sciences, 2021, 14(01), 037-046.
Article DOI: 10.30574/gscbps.2021.14.1.0002
Publication history: 
Received on 05 December 2020; revised on 06 January 2021; accepted on 07 January 2021
 
Abstract: 
Despite advancements in diagnostic and standard treatment modalities, cancer survival rate remains disappointing globally. It has however, been recognized that exploring the therapeutic properties of secondary metabolite from natural products may alleviate the problems of drug resistance and toxicity that besiege the conventional therapies, and hence improve the overall prognosis of cancer patient. To this end curcumin, a polyphenolic natural compound has been widely studied for it anticancer activities in in vitro and in vivo models. Computational technology has significantly improved the success rate of drug discovery and development, hence, it has become a widely explore tool in drug candidate identification. In this study we used computational approached to identify 12 genes that are potential druggable candidate for curcumin. The genes identified were found to be enriched in cancer and drug resistance associated signaling pathways. Interestingly, the top 3 identified genes; Microtubule-associated protein tau (MAPT), Toll-like receptor 9 (TLR9) and Tyrosyl-DNA phosphodiesterase 1 (TDP1) were observed to be over expressed in multiple cancer cohorts and were associated with poor prognoses of the patients. Curcumin has good physicochemical, bioavailability and ADMET properties. Importantly, it met the Lipinski's Rule of 5 for drug likeness and thus worthy of further in vitro and in vivo confirmation studies.
 
Keywords: 
Curcumin, Cancer; In silico studies; Drug-likeness; Drug target; Protein-protein interactions.
 
Full text article in PDF: 
Share this