In silico identification of natural products with anticancer activity using a chemo-structural database of Brazilian biodiversity. (December 2019) - Galúcio, João Marcos; Monteiro, Elton Figueira; de Jesus, Deivid Almeida; Costa, Clauber Henrique; Siqueira, Raissa Caroline; Santos, Gabriela Bianchi dos; Lameira, Jerônimo; Costa, Kauê Santana da
Graphical abstract: Highlights: The predicted natural products with anticancer activity are widely distributed in 46 families and have at least 19 different molecular targets involved in cancer development and progression. The analysis of predicted target inhibition showed that some compounds were stable during MD simulations and exhibited similar interactions with the reference inhibitors. Some chemical classes revealed interesting chemotypes that could be further tested as cancer agents. Abstract: Cancer is one of the leading causes of death worldwide, and the number of patients has only increased each year, despite the considerable efforts and investments in scientific research. Since natural products (NPs) may serve as suitable sources for drug development, the cytotoxicity against cancer cells of 2221 compounds from the Nuclei of Bioassays, Ecophysiology, and Biosynthesis of Natural Products Database (NuBBE DB ) was predicted using CDRUG algorithm. Molecular modeling, chemoinformatics, and chemometric tools were then used to analyze the structural and physicochemical properties of these compounds. We compared the positive NPs with FDA-approved anticancer drugs and predicted the molecular targets involved in the anticancer activity. In the present study, 46 families comprising potential anticancer compounds and at least 19 molecular targets involved in oncogenesis. To the best of our knowledge, this is the first large-scale study conducted to evaluate the potentiality of NPs sourced from Brazilian biodiversity as anticancer agents, using in silico approaches. Our results provided interesting insights about the mechanism of action of these compounds, and also suggested that their structural diversity may aid structure-based optimization strategies for developing novel drugs for cancer therapy.