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Repurposing of known drugs for leishmaniasis treatment using bioinformatic predictions, in vitro validations and pharmacokinetic simulations

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Abstract

Leishmaniasis is a neglected tropical disease caused by Leishmania parasites and is associated to more than 1.3 million cases annually. Some of the pharmacological options for treating the disease are pentavalent antimonials, pentamidine, miltefosine, and amphotericin B. However, all are associated with a wide range of adverse effects and contraindications, as well as resistance from the parasite. In the present study, we looked for pharmacological alternatives to treat leishmaniasis, with a focus on drug repurposing. This was done by detecting potential homologs between proteins targeted by approved drugs and proteins of the parasite. The proteins were analyzed using an interaction network, and the drugs were subjected to in vitro evaluations and pharmacokinetics simulations to compare probable plasma concentrations with the effective concentrations detected experimentally. This strategy yielded a list of 33 drugs with potential anti-Leishmania activity, and more than 80 possible protein targets in the parasite. From the drugs tested, two reported high in vitro activity (perphenazine EC50 = 1.2 µg/mL and rifabutin EC50 = 8.5 µg/mL). These results allowed us to propose these drugs as candidates for further in vivo studies and evaluations of the effectiveness on their topical forms.

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Acknowledgements

This Project was funded by the Departamento Administrativo de Ciencia y Tecnología e Innovación-Colciencias, under the contract number 534–2013 and Project code 1115–569-33419. The authors acknowledge Dr. Andres Zuluaga and Dr. Carlos Rodriguez for their support and advisory in the pharmacokinetic analysis, and Professor Jaime Hincapie for his collaboration in the study design.

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Correspondence to Carlos Muskus.

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Bustamante, C., Ochoa, R., Asela, C. et al. Repurposing of known drugs for leishmaniasis treatment using bioinformatic predictions, in vitro validations and pharmacokinetic simulations. J Comput Aided Mol Des 33, 845–854 (2019). https://doi.org/10.1007/s10822-019-00230-y

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