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Updated: Feb 6, 2026

Mass Spectrometry-Guided Genome Mining as a Tool to Uncover Novel Natural Products
Published on: March 12, 2020
Identification of steroid-like natural products as antiplasmodial agents by 2D and 3D similarity-based virtual
Elumalai Pavadai1, Gurminder Kaur1, Sergio Wittlin2,3
1Department of Chemistry , University of Cape Town , Rondebosch 7701 , South Africa . Email: elumalai.pavadai.a@gmail.com ; Email: Kelly.Chibale@uct.ac.za ; ; Tel: +1 (305) 348 6661 ; Tel: +27 21 650 2553.
Abstract:
The emergence of drug resistance in Plasmodium falciparum to available antimalarial drugs has challenged current antimalarial treatments. New antimalarials, particularly those with novel mechanisms of action and no cross resistance to current drugs, are therefore urgently needed. To identify new growth inhibitors of Plasmodium falciparum, 2D and 3D similarity-based virtual screening methods were employed in parallel with an in-house database of steroid-type natural products using fusidic acid as a search query. The resulting hit compounds were further filtered based on the predicted partition coefficient, log P. The virtual screening strategy resulted in the identification of nine new compounds that inhibited parasite growth with IC50 values of <20 μM. Four compounds exhibited IC50 values in the range of 1.39-3.45 μM and three of which showed a promising selectivity index. Further, the predicted ADME properties of the four most active compounds were found to be comparable to fusidic acid. These compounds can be further explored using structural modifications in the identification and development of more potent parasite growth inhibitors with improved selectivity.
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