Discovery of Alternative Chemotherapy Options for Leishmaniasis through Computational Studies of Asteraceae

Leishmaniasis is a complex disease caused by over 20 Leishmania species that primarily affects populations with poor socioeconomic conditions. Currently available drugs for treating leishmaniasis include amphotericin B, paromomycin, and pentavalent antimonials, which have been associated with several limitations, such as low efficacy, the development of drug resistance, and high toxicity. Natural products are an interesting source of new drug candidates. The Asteraceae family includes more than 23 000 species worldwide. Secondary metabolites that can be found in species from this family have been widely explored as potential new treatments for leishmaniasis. Recently, computational tools have become more popular in medicinal chemistry to establish experimental designs, identify new drugs, and compare the molecular structures and activities of novel compounds. Herein, we review various studies that have used computational tools to examine various compounds identified in the Asteraceae family in the search for potential drug candidates against Leishmania. Star performer: In‐silico studies have been performed on Asteraceae secondary metabolites to find new structures with potential activity against Leishmania species. This review describes existing databases associated with Asteraceae and explores the results of studies that have used in silico methodologies (particularly machine learning and molecular docking) to identify new structures with potential anti‐Leishmania activities.