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Drug Repurposing for Paracoccidioidomycosis Through a Computational Chemogenomics Framework.
Front Microbiol 2019; 10:1301FM

Abstract

Paracoccidioidomycosis (PCM) is the most prevalent endemic mycosis in Latin America. The disease is caused by fungi of the genus Paracoccidioides and mainly affects low-income rural workers after inhalation of fungal conidia suspended in the air. The current arsenal of chemotherapeutic agents requires long-term administration protocols. In addition, chemotherapy is related to a significantly increased frequency of disease relapse, high toxicity, and incomplete elimination of the fungus. Due to the limitations of current anti-PCM drugs, we developed a computational drug repurposing-chemogenomics approach to identify approved drugs or drug candidates in clinical trials with anti-PCM activity. In contrast to the one-drug-one-target paradigm, our chemogenomics approach attempts to predict interactions between drugs, and Paracoccidioides protein targets. To achieve this goal, we designed a workflow with the following steps: (a) compilation and preparation of Paracoccidioides spp. genome data; (b) identification of orthologous proteins among the isolates; (c) identification of homologous proteins in publicly available drug-target databases; (d) selection of Paracoccidioides essential targets using validated genes from Saccharomyces cerevisiae; (e) homology modeling and molecular docking studies; and (f) experimental validation of selected candidates. We prioritized 14 compounds. Two antineoplastic drug candidates (vistusertib and BGT-226) predicted to be inhibitors of phosphatidylinositol 3-kinase TOR2 showed antifungal activity at low micromolar concentrations (<10 μM). Four antifungal azole drugs (bifonazole, luliconazole, butoconazole, and sertaconazole) showed antifungal activity at low nanomolar concentrations, validating our methodology. The results suggest our strategy for predicting new anti-PCM drugs is useful. Finally, we could recommend hit-to-lead optimization studies to improve potency and selectivity, as well as pharmaceutical formulations to improve oral bioavailability of the antifungal azoles identified.

Authors+Show Affiliations

Laboratório de Biologia Molecular, Universidade Federal de Goiás, Goiânia, Brazil. Laboratório de Cheminformática, Centro Universitário de Anápolis, UniEVANGÉLICA, Anápolis, Brazil.Laboratório de Cheminformática, Centro Universitário de Anápolis, UniEVANGÉLICA, Anápolis, Brazil.Laboratório de Biologia Molecular, Universidade Federal de Goiás, Goiânia, Brazil.Laboratório de Biologia Molecular, Universidade Federal de Goiás, Goiânia, Brazil.Laboratório de Modelagem Molecular e Design de Medicamentos, Faculdade de Farmácia, Universidade Federal de Goiás, Goiânia, Brazil.Laboratório de Biologia Molecular, Universidade Federal de Goiás, Goiânia, Brazil.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

31244810

Citation

de Oliveira, Amanda Alves, et al. "Drug Repurposing for Paracoccidioidomycosis Through a Computational Chemogenomics Framework." Frontiers in Microbiology, vol. 10, 2019, p. 1301.
de Oliveira AA, Neves BJ, Silva LDC, et al. Drug Repurposing for Paracoccidioidomycosis Through a Computational Chemogenomics Framework. Front Microbiol. 2019;10:1301.
de Oliveira, A. A., Neves, B. J., Silva, L. D. C., Soares, C. M. A., Andrade, C. H., & Pereira, M. (2019). Drug Repurposing for Paracoccidioidomycosis Through a Computational Chemogenomics Framework. Frontiers in Microbiology, 10, p. 1301. doi:10.3389/fmicb.2019.01301.
de Oliveira AA, et al. Drug Repurposing for Paracoccidioidomycosis Through a Computational Chemogenomics Framework. Front Microbiol. 2019;10:1301. PubMed PMID: 31244810.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Drug Repurposing for Paracoccidioidomycosis Through a Computational Chemogenomics Framework. AU - de Oliveira,Amanda Alves, AU - Neves,Bruno Junior, AU - Silva,Lívia do Carmo, AU - Soares,Célia Maria de Almeida, AU - Andrade,Carolina Horta, AU - Pereira,Maristela, Y1 - 2019/06/12/ PY - 2019/02/11/received PY - 2019/05/24/accepted PY - 2019/6/28/entrez PY - 2019/6/28/pubmed PY - 2019/6/28/medline KW - Paracoccidioides species KW - drug repurposing KW - gene essentiality KW - genome-wide alignment KW - in vitro assays KW - molecular docking SP - 1301 EP - 1301 JF - Frontiers in microbiology JO - Front Microbiol VL - 10 N2 - Paracoccidioidomycosis (PCM) is the most prevalent endemic mycosis in Latin America. The disease is caused by fungi of the genus Paracoccidioides and mainly affects low-income rural workers after inhalation of fungal conidia suspended in the air. The current arsenal of chemotherapeutic agents requires long-term administration protocols. In addition, chemotherapy is related to a significantly increased frequency of disease relapse, high toxicity, and incomplete elimination of the fungus. Due to the limitations of current anti-PCM drugs, we developed a computational drug repurposing-chemogenomics approach to identify approved drugs or drug candidates in clinical trials with anti-PCM activity. In contrast to the one-drug-one-target paradigm, our chemogenomics approach attempts to predict interactions between drugs, and Paracoccidioides protein targets. To achieve this goal, we designed a workflow with the following steps: (a) compilation and preparation of Paracoccidioides spp. genome data; (b) identification of orthologous proteins among the isolates; (c) identification of homologous proteins in publicly available drug-target databases; (d) selection of Paracoccidioides essential targets using validated genes from Saccharomyces cerevisiae; (e) homology modeling and molecular docking studies; and (f) experimental validation of selected candidates. We prioritized 14 compounds. Two antineoplastic drug candidates (vistusertib and BGT-226) predicted to be inhibitors of phosphatidylinositol 3-kinase TOR2 showed antifungal activity at low micromolar concentrations (<10 μM). Four antifungal azole drugs (bifonazole, luliconazole, butoconazole, and sertaconazole) showed antifungal activity at low nanomolar concentrations, validating our methodology. The results suggest our strategy for predicting new anti-PCM drugs is useful. Finally, we could recommend hit-to-lead optimization studies to improve potency and selectivity, as well as pharmaceutical formulations to improve oral bioavailability of the antifungal azoles identified. SN - 1664-302X UR - https://www.unboundmedicine.com/medline/citation/31244810/Drug_Repurposing_for_Paracoccidioidomycosis_Through_a_Computational_Chemogenomics_Framework L2 - https://doi.org/10.3389/fmicb.2019.01301 DB - PRIME DP - Unbound Medicine ER -