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Enolase is a glycolytic enzyme that catalyzes the interconversion between 2-phosphoglycerate and phosphoenolpyruvate. In trypanosomatids, enolase was proposed as a key enzyme after in silico and in vivo analysis and it was validated as a protein essential for the survival of the parasite. Therefore, enolase constitutes an interesting enzyme target for the identification of drugs against Chagas disease. In this work, a combined virtual screening strategy was implemented, employing similarity virtual screening, molecular docking, and molecular dynamics. First, two known enolase inhibitors and the enzyme substrates were used as queries for the similarity screening on the Sweetlead database using five different algorithms. Compounds retrieved in the top 10 of at least three search algorithms were selected for further analysis, resulting in six compounds of medical use (etidronate, pamidronate, fosfomycin, acetohydroxamate, triclofos, and aminohydroxybutyrate). Molecular docking simulations and pose re-scoring predicted that binding with acetohydroxamate and triclofos would be weak, while fosfomycin and aminohydroxybutyrate predicted binding is experimentally implausible. Docking poses obtained for etidronate, pamidronate, and PEP were used for molecular dynamics calculations to describe their mode of binding. From the obtained results, we propose etidronate as a potential Tc ENO inhibitor and describe molecular motifs to be taken into account in the repurposing or design of drugs targeting this enzyme active site. Image 1 [ABSTRACT FROM AUTHOR]