Dihydroartemisinin as a potential drug candidate for cancer therapy: a structural-based virtual screening for multitarget profiling.
Ibrahim MalamiAisha Muktar BunzaAlhassan Muhammad AlhassanMuhammad AliyuIbrahim Babangida AbubakarAbdulmajeed YunusaPeter M WaziriImaobong C EttiPublished in: Journal of biomolecular structure & dynamics (2020)
Cancer is a rapidly growing non-communicable disease worldwide that is responsible for high mortality rates, which account for 9.6 million death in 2018. Dihydroartemisinin (DHA) is an active metabolite of artemisinin, an active principle present in the Chinese medicinal plant Artemisia annua used for malaria treatment. Dihydroartemisinin possesses remarkable and selective anticancer properties however the underlying mechanism of the antitumor effects of DHA from the structural point of view is still not yet elucidated. In the present study, we employed molecular docking simulation techniques using Autodock suits to access the binding properties of dihydroartemisinin to multiple protein targets implicated in cancer pathogenesis. Its potential targets with comprehensive pharmacophore were predicted using a PharmMapper database. The co-crystallised structures of the protein were obtained from a Protein Data Bank and prepared for molecular docking simulation. Out of the 24 selected protein targets, DHA has shown about 29% excellent binding to the targets compared to their co-crystallised ligand. Additionally, 75% of the targets identified for dihydroartemisinin binding are protein kinases, and 25% are non-protein kinases. Hydroxyl functional group of dihydroartemisinin contributed to 58.5% of the total hydrogen interactions, while pyran (12.2%), endoperoxide (9.8%), and oxepane (19.5%) contributed to the remaining hydrogen bonding. The present findings have elucidated the possible antitumor properties of dihydroartemisinin through the structural-based virtual studies, which provides a lead to a safe and effective anticancer agent useful for cancer therapy.Communicated by Ramaswamy H. Sarma.
Keyphrases
- molecular docking
- cancer therapy
- protein protein
- binding protein
- amino acid
- molecular dynamics simulations
- drug delivery
- papillary thyroid
- drug administration
- squamous cell carcinoma
- fatty acid
- cardiovascular events
- climate change
- risk assessment
- small molecule
- deep learning
- risk factors
- plasmodium falciparum
- artificial intelligence
- smoking cessation
- virtual reality