Using a chemical biology approach to develop novel inhibitors of mitochondrial oxidative phosphorylation for the treatment of ovarian cancer

女退伍军人的数量正在迅速增加，预计将达到退伍军人总数的16%-17% 在接下来的二十年内，人口数量将会增加。再者，女性退伍军人属于老龄化人口，45-年龄 群体是最大的队列。随着女性退伍军人年龄的增长，预计将有越来越多的女性退伍军人 癌症。妇科肿瘤占退伍军人所有癌症的12%，卵巢恶性肿瘤是 在这个群体中第二常见。卵巢癌主要发生在绝经后女性。 因此，随着人口老龄化，这种癌症的发病率预计会增加。卵巢癌是一种 尤其是致命的癌症，没有一种现代治疗方案显示出对总存活率的重大好处 病人的数量。我们的研究重点是开发新型氧化磷酸化(OXPHOS)。 治疗卵巢癌的抑制剂。从这项工作中出现的治疗学线索具有巨大的潜力 这对女性退伍军人是有益的，对退伍军人医疗保健系统非常重要。复发性肿瘤、癌干 来自肿瘤微环境的细胞和非恶性细胞利用OXPHOS来满足其代谢需求。 因此，开发OXPHOS抑制剂作为治疗癌症的新药物重新引起了人们的兴趣。 癌症。我们已经确定了一组通过干扰泛醌来抑制OXPHOS的化合物 将电子从NADH和FADH2传输到分子氧。我们正在测试的化合物，柠檬醛， 白花黄素、姜黄素、阿托瓦酮等具有不饱和的羰基官能团，可模拟 泛醌的苯醌亚基结构。结果，这些化合物干扰了OXPHOS，导致迅速 细胞内氧自由基增加，破坏DNA，并通过激活P53诱导细胞凋亡。 因此，这种泛醌模拟物是癌症治疗的候选药物。然而，OXHPOS抑制剂WE 到目前为止已检测到的，显示出较差的效力和药代动力学特征。在本申请中，我们建议 使用快速和经济有效的计算方法来确定新的和有效的OXPHOS抑制剂 目标是开发用于治疗高级别浆液性卵巢肿瘤的引线。在目标1中，我们将开发 并验证数据挖掘管道，以从大量的测试数据中识别有效的和类似药物的OXPHOS抑制剂 在PubChem公共存储库中可用。在目标2中，我们将采用基于以前的机器学习模型 筛选数据，以指导在细胞生物分析报告中为迭代筛选选择新化合物 在OXPHOS途径的不同方面。在目标3中，我们将测试OXPHOS和PARP的组合剂量 卵巢癌模型中的协同效力和疗效的抑制剂。这里开发的方法可能是 通常应用于利用先前的化验数据来建立模型，该模型将迭代筛选作为更有效的 方法比标准的高通量筛选。拟议的研究应该有助于我们确定最 OXPHOS靶向治疗卵巢癌的有前景的生化靶点和抑制化合物类。 通过我们的方法发现的铅OXPHOS抑制剂将在未来的临床试验中进行测试，包括 女性退伍军人被诊断为高级别浆液性卵巢癌。

The number of women Veterans is rapidly increasing and expected to reach to 16-17% of the total Veteran population within the next two decades. Furthermore, female Veterans are an aging population, the 45-64 age group being the largest cohort. As female Veterans age, an increasing number are expected to present with cancers. Gynecologic tumors constitute 12% of all cancers in women Veterans with ovarian malignancy being the second most common in this group. Ovarian cancer predominantly develops in postmenopausal women. Therefore, the incidence of this cancer is expected to increase as the population ages. Ovarian cancer is an especially lethal cancer with none of the modern treatment regimens showing major benefits on overall survival of patients. Our proposed research focuses on the development of novel oxidative phosphorylation (OXPHOS) inhibitors for the treatment of ovarian cancer. Leads for therapeutics emerging from this work have great potential benefit to women Veterans and is highly significant to the VA Healthcare system. Recurrent tumors, cancer stem cells, and non-malignant cells from the tumor microenvironment engage OXPHOS for their metabolic needs. Therefore, there is renewed interest in developing OXPHOS inhibitors as novel agents for the treatment of cancer. We have identified a group of compounds that inhibit OXPHOS by interfering with ubiquinone in transporting electrons from NADH and FADH2 to molecular oxygen. The compounds we are testing, citral, plumbagin, curcumin, atovaquone and others, have an unsaturated carbonyl functional group that mimics ubiquinone’s benzoquinone substructure. As a result, these compounds interfere in OXPHOS, cause rapid increase in intracellular oxygen radicals that damage DNA, and induce apoptosis through the activation of p53. Such ubiquinone mimetics are therefore candidates for cancer therapy. However, the OXHPOS inhibitors we have examined so far, show poor potency and pharmacokinetic characteristics. In this application we propose to employ rapid and cost-effective computational approaches to identify novel and potent OXPHOS inhibitors with the goal of developing leads for treatment of high-grade serous ovarian tumors. In Aim 1, we will develop and validate a data mining pipeline to identify potent and drug-like OXPHOS inhibitors from extensive assay data available in PubChem public repository. In Aim 2 we will employ a machine learning model, based on previous screening data, to guide selection of new compounds for iterative screening in cell biological assays reporting on different aspects of the OXPHOS pathway. In Aim 3, we will test combination dosing of OXPHOS and PARP inhibitors for synergistic potency and efficacy in ovarian cancer models. The methods developed here could be applied generally in leveraging prior assay data to build models that guide iterative screening as a more efficient approach than standard high throughput screening. The proposed studies should help us to identify the most promising biochemical targets and inhibitory compound classes for OXPHOS-targeted ovarian cancer therapies. Lead OXPHOS inhibitors discovered through our approach will be tested in future clinical trials that include women Veterans diagnosed for high grade serous ovarian cancer.