de Oliveira Amanda Alves, Neves Bruno Junior, Silva Lívia do Carmo, Soares Célia Maria de Almeida, Andrade Carolina Horta, Pereira Maristela
Laboratório de Biologia Molecular, Universidade Federal de Goiás, Goiânia, Brazil.
Laboratório de Cheminformática, Centro Universitário de Anápolis, UniEVANGÉLICA, Anápolis, Brazil.
Front Microbiol. 2019 Jun 12;10:1301. doi: 10.3389/fmicb.2019.01301. eCollection 2019.
Paracoccidioidomycosis (PCM) is the most prevalent endemic mycosis in Latin America. The disease is caused by fungi of the genus 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 protein targets. To achieve this goal, we designed a workflow with the following steps: (a) compilation and preparation of 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 essential targets using validated genes from ; (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.
副球孢子菌病(PCM)是拉丁美洲最普遍的地方性真菌病。该疾病由 属真菌引起,主要影响低收入农村工人,他们在吸入空气中悬浮的真菌分生孢子后患病。目前的化疗药物库需要长期给药方案。此外,化疗与疾病复发频率显著增加、高毒性以及真菌未完全清除有关。由于当前抗PCM药物的局限性,我们开发了一种计算药物重新利用——化学基因组学方法,以识别在临床试验中具有抗PCM活性的已批准药物或候选药物。与单药单靶点模式不同,我们的化学基因组学方法试图预测药物与 蛋白质靶点之间的相互作用。为实现这一目标,我们设计了一个包含以下步骤的工作流程:(a) 属物种基因组数据的汇编和准备;(b) 分离株之间直系同源蛋白的鉴定;(c) 在公开可用的药物靶点数据库中鉴定同源蛋白;(d) 使用来自 的经过验证的基因选择 必需靶点;(e) 同源建模和分子对接研究;以及(f) 所选候选药物的实验验证。我们对14种化合物进行了优先排序。两种预计为磷脂酰肌醇3激酶TOR2抑制剂的抗肿瘤候选药物(vistusertib和BGT - 226)在低微摩尔浓度(<10 μM)下显示出抗真菌活性。四种抗真菌唑类药物(联苯苄唑、卢立康唑、布康唑和舍他康唑)在低纳摩尔浓度下显示出抗真菌活性,验证了我们的方法。结果表明我们预测新抗PCM药物的策略是有用的。最后,我们可以推荐从活性化合物到先导化合物的优化研究,以提高效力和选择性,以及改进所鉴定抗真菌唑类药物口服生物利用度的药物制剂。