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Drug Repurposing for Paracoccidioidomycosis Through a Computational Chemogenomics Framework
- Source :
- Frontiers in Microbiology, Vol 10 (2019)
- Publication Year :
- 2019
- Publisher :
- Frontiers Media S.A., 2019.
-
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 (
Details
- Language :
- English
- ISSN :
- 1664302X
- Volume :
- 10
- Database :
- Directory of Open Access Journals
- Journal :
- Frontiers in Microbiology
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.38ec495674f24cacb46c16ec5bd266d9
- Document Type :
- article
- Full Text :
- https://doi.org/10.3389/fmicb.2019.01301