Abstract
The genus Artemisia consists of plants that are well known for their medicinal value. These are
used traditionally to manage or treat various conditions and diseases. Artemisia afra, which is
indigenous to South Africa, has been reported and claimed for the treatment of respiratory
symptoms, headaches, fever, and malaria. On the other hand, Artemisia annua, is globally
widespread, and mostly known for producing artemisinin- that is effective for treating malaria.
The Mediterranean Artemisia absinthium is mostly famous because of a historic drink
‘absinthe” that was made from it; however, there are controversial claims alluding to
neurotoxicity and neuroprotectivity of its compounds. The comprehensive phytochemical
landscape of all three plants remains enigmatic. Thus, this Chapter, a critical review, provides
an overview on plant-derived natural products, highlighting the health benefits of these
specialized metabolites from the plants, and current knowledge gaps and limitations in
characterizing these compounds and downstream applications. Furthermore, this Chapter
reviews the current knowledge on the three Artemisia plants, A. afra, A. annua and A.
absinthium, and their respective health claims. The Chapter ends with a brief account on
metabolomics, an omics science that offers ways to comprehensively characterize the chemical
space of plants, in this case, Artemisia plants. Furthermore, computational strategies and
frameworks in metabolomics aid in dereplication and semi-automated annotation of
metabolites. The Chapter points out the use of bioinformatics methods for biological
interpretation and predictive modelling of biological activities of plant-derived specialize
metabolites. Thus, this review Chapter attempts to situate this study in the current literature
context, pointing out current knowledge and gaps the study hopes to address, such as
comprehensive chemical maps of Artemisia plants, and potential biological activities of
Artemisia-derived metabolites.
Keywords: metabolomics, Artemisia, traditional medicine, computational tools, 4IR