Drug Repurposing Screening for Rare and Neglected Diseases

罕见病和被忽视疾病的药物再利用筛查

基本信息

项目摘要

In collaboration with NIH and external academic and industry researchers, we have carried out assay development and performed drug repurposing screens for multiple projects across a range of therapeutic areas, including COVID-19, rare genetic disorders and rare drug resistant cancers. DISEASE MODELING USING PATIENT IPSC-DERIVED CELLS: Disease modeling using patient cells is an effective approach to enable establishment of new alternative / non-animal disease models. Human induced pluripotent stem cells (iPSCs) are generated from patient samples that can be further differentiated to various cell types such as neuronal cells, cardiomyocytes, and hepatocytes for disease modeling. These cell-based models are particularly useful for drug discovery and development for rare genetic diseases, as animal models are not always available. The patient derived iPSCs share the same genetic background with patients and have the same cellular disease phenotypes that are suitable for assay development to screen compounds. We have generated over 100 patient-derived iPSC lines for rare genetic diseases. In this period, we generated several iPSC lines from samples of Alagille Syndrome and healthy donors (Owusu-Ansah K et al., 2023. Stem Cell Res 71, 103135. PMID: 37393720). The iPSCs have been characterized and stably passaged over 10 passages. These iPSCs were differentiated to support generation of hepatocytes and liver organoids for ALGS disease modeling and assay development for repurposing screens. We have also deposited 6 patient iPSC lines previously generated, including for Mucopolysarcharidosis type I (MPS I) and Hunters syndrome (MPS II), to the Coriell Cell Repository as public resources to other researchers. DRUG-RESISTANT CANCER: Cancer drug resistance is a severe clinical problem that often results in patient death. We performed drug repurposing screens for drug-resistant cell lines of liver cancer, and ovarian cancer refractory to multiple standard care chemotherapies. Several approved drugs have been identified that either suppress the drug-resistant cancer cells directly or re-sensitize the cells to the anticancer activities of the standard drugs. We found that terfenadine re-sensitized doxorubicin activity in drug-resistant ovarian cancer cells via inhibition of CaMKII/CREB1-mediated ABCB1 expression (Huang W et al., 2022. Front Oncology 12, 1068443. PMID: 36439493). We also found that PD1938306, a MEK inhibitor, enhances the efficacy of sorafenib (a standard therapeutic for liver cancer) in hepatocellular carcinoma cells through a repurposing screen (Hong J eta al. 2023. Comb Chem High Throughput Screen. 26: 1364-74. PMID: 36043792). These results are useful for further studies of the mechanisms of drug resistance and cancer target identification for new drug development. SARS-CoV-2 and COVID-19: We have developed a SARS-CoV-2 pseudotyped particle entry assay for use in BSL-2 laboratories to screen compound libraries and evaluate compound efficacy as SARS-CoV-2 entry inhibitors (Xu M et al. 2022. SLAS Discovery. 27:86-94. PMID: 35086793). We have also developed a homogenous compound screening assay that detects the nucleocapsid protein of SARS-CoV-2 in the viral replication process for high throughput screening in our collaborators BSL-3 lab (Gorshkov K et al. 2022. ACS Pharmacol Transl Sci 5, 8-19. PMID: 35036857). We performed repurposing screens using the pseudotyped particle assay and another assay to target the fusion process of SARS-CoV-2 infection (Park SB et al. 2022. mBio. e0323821. PMID: 35012356). Additionally, we collaborated with other NIH researchers on COVID-19 screens related to a nanobody against the SARS-CoV-2 spike protein, TMPRSS2 inhibitors, heparan-spike interaction, and estrogen receptor-spike interaction (Fu Y et al. 2022. PLoS One. 17: e0272364. PMID: 35947606; Shrimp JH. Et al. 2022. ACS Infect Dis. 8:1191-03. PMID: 35648838; Zhang Q. et al. 2022. Sci Rep. 12:6294. PMID: 35440680; Solis O et al. 2022. Sci Adv 8, eadd4150. PMID: 36449624). FOXG1 SYNDROME: FOXG1 Syndrome is a rare and debilitating neurodevelopmental disorder causing severe cognitive impairment. The disease is caused by heterozygous mutations in the transcription factor Forkhead Box G1 (FOXG1). Currently, there is no approved therapy for FOXG1 Syndrome. BELIEVE IN A CURE is a non-profit organization focused on developing treatments for FOXG1 syndrome. NCATS collaborated with the foundation to perform a drug repurposing screen in a FOXG1 reporter assay to identify up-regulators of the FOXG1 gene. Hits from the primary screen were further tested in a Western blot assay in patient iPSC-derived neural stem cells. NGLY1 DEFICIENCY: This is a low incidence genetic disease that primarily affects the neuronal system, resulting in neuromotor impairment, intellectual disability, and neuropathy. We have generated brain organoids using the NGLY1 patient iPSCs for disease modeling. We found that the patient midbrain organoids show altered neuronal development and reduced dopaminergic neurons compared to wild type organoids (Abbott J. et al. 2023. Front Cell Dev Biol. 11: 1039182. PMID: 36875753). We also worked on a neuromuscular junction platform using the patient iPSC-derived motor neurons to study the pathogenesis of disease. We observed reduced axon length, increased and shortened axon branches, motor neuron action potential bursting, and decreased action potential firing rate and amplitude in this system (Sasserath T. et al. 2022. Adv Ther 5:2200009, PMID: 36589922). The NGLY1 brain organoids and motor neurons are useful models for the study of disease mechanisms and evaluation of therapeutic candidates. LEBER CONGENITAL AMAUROSIS (LCA): LCA is an inherited disease of the eye that causes loss of sight in early childhood and lacks effective treatment. We performed a drug repurposing screen using retinal organoids differentiated from the iPSCs from a model of Leber congenital amaurosis. Reserpine, a drug used for the treatment of hypertension, was identified among a few other compounds that maintains photoreceptor survival in retinal ciliopathy (Chen HY. Et al. 2023. Elife, 12:e83205. PMID: 36975211). Currently, further study of the mechanism of action and potential preclinical development are in process. AI-BASED MODELING AND VIRTUAL SCREENING: Recent advancements in artificial intelligence (AI)- based modeling have enabled virtual compound screening for lead compound identification. The advantages of this approach for drug discovery are (1) a reduction in physical compound screening experiments that significantly decreases project costs; and (2) a significantly increased screening capacity, as virtual screens can cover in-house compound collections as well as large commercial collections (i.e., millions of compounds), both of which save time during the lead identification process. We have developed and optimized several AI-based compound screening tools that have been applied to several projects. The experimental screening data from a small compound collection (such as the collection of 2800 approved drugs available at NCATS) is typically used to establish, train, and optimize a computer model for a given project that is then employed in a virtual compound screen of larger compound collections (up to millions of compounds) to identify hits. After computerized hit selection and confirmation, the top list compounds (typically 50 to 200) are selected and ordered for a laboratory experiment to evaluate their activities. We have published the method of AI-based modeling and virtual screening using the SARS-CoV-2 entry inhibitor project as an example (Gao P et al., 2023. J Chem Inf Model. 62: 1988-97. PMID: 35404596) with several other manuscripts under preparation.
我们与 NIH 以及外部学术和行业研究人员合作,为一系列治疗领域的多个项目进行了检测开发和药物再利用筛选,包括 COVID-19、罕见遗传性疾病和罕见耐药癌症。 使用患者 IPSC 衍生细胞进行疾病建模:使用患者细胞进行疾病建模是建立新的替代/非动物疾病模型的有效方法。人类诱导多能干细胞 (iPSC) 从患者样本中产生,可进一步分化为各种细胞类型,如神经元细胞、心肌细胞和肝细胞,用于疾病建模。这些基于细胞的模型对于罕见遗传疾病的药物发现和开发特别有用,因为动物模型并不总是可用。患者衍生的 iPSC 与患者具有相同的遗传背景,并具有相同的细胞疾病表型,适合用于筛选化合物的测定开发。我们已经生成了 100 多个源自患者的 iPSC 系,用于治疗罕见遗传病。在此期间,我们从 Alagille 综合征样本和健康供体样本中生成了多个 iPSC 系(Owusu-Ansah K et al., 2023. Stem Cell Res 71, 103135. PMID: 37393720)。 iPSC 已被表征并稳定传代超过 10 代。这些 iPSC 经过分化,可支持肝细胞和肝脏类器官的生成,用于 ALGS 疾病建模和重新用途筛选的测定开发。我们还将之前生成的 6 个患者 iPSC 系(包括粘多糖沉积症 I 型 (MPS I) 和 Hunters 综合征 (MPS II))存入 Coriell 细胞存储库,作为其他研究人员的公共资源。 耐药癌症:癌症耐药性是一个严重的临床问题,常常导致患者死亡。我们对多种标准护理化疗耐药的肝癌和卵巢癌耐药细胞系进行了药物再利用筛选。已经确定了几种批准的药物,可以直接抑制耐药癌细胞,或者使细胞对标准药物的抗癌活性重新敏感。我们发现特非那定通过抑制 CaMKII/CREB1 介导的 ABCB1 表达,使耐药卵巢癌细胞中的多柔比星活性重新敏感 (Huang W et al., 2022. Front Oncology 12, 1068443. PMID: 36439493)。 我们还发现,MEK 抑制剂 PD1938306 通过再利用筛选增强了索拉非尼(肝癌的标准治疗药物)在肝细胞癌细胞中的功效(Hong J 等人。2023。Comb Chem High Throughput Screen。26:1364-74 .PMID:36043792)。这些结果对于进一步研究耐药机制和新药开发的癌症靶点识别具有重要意义。 SARS-CoV-2 和 COVID-19:我们开发了一种 SARS-CoV-2 假型颗粒进入测定法,用于 BSL-2 实验室,以筛选化合物库并评估化合物作为 SARS-CoV-2 进入抑制剂的功效(Xu M 等)等,2022 年。SLAS 发现 27:86-94。PMID:35086793)。我们还开发了一种均质化合物筛选方法,可在我们的合作者 BSL-3 实验室中检测病毒复制过程中的 SARS-CoV-2 核衣壳蛋白,以进行高通量筛选(Gorshkov K 等人,2022 年。ACS Pharmacol Transl Sci 5, 8-19。PMID:35036857)。我们使用假型粒子测定和另一种针对 SARS-CoV-2 感染融合过程的测定进行了重新用途筛选(Park SB 等人 2022.mBio.e0323821.PMID:35012356)。此外,我们与其他 NIH 研究人员合作,进行了与针对 SARS-CoV-2 刺突蛋白的纳米抗体、TMPRSS2 抑制剂、乙酰肝素-刺突相互作用和雌激素受体-刺突相互作用相关的 COVID-19 筛选(Fu Y 等人,2022 年。 PLoS 17:e0272364。虾 JH 等人。 ACS Infect Dis. 8:1191-03;Zhang Q. 等人,2022 年。Sci Rep.12:6294;Solis O 等人,2022 年。Sci Adv 8,eadd4150。 。 FOXG1 综合征:FOXG1 综合征是一种罕见且使人衰弱的神经发育障碍,会导致严重的认知障碍。该疾病是由转录因子 Forkhead Box G1 (FOXG1) 的杂合突变引起的。目前,尚无批准的 FOXG1 综合征治疗方法。 BELIEVE IN A CURE 是一家致力于开发 FOXG1 综合征治疗方法的非营利组织。 NCATS 与该基金会合作,在 FOXG1 报告基因检测中进行药物再利用筛选,以鉴定 FOXG1 基因的上调因子。来自初级筛选的命中结果在患者 iPSC 衍生的神经干细胞中通过蛋白质印迹分析进行了进一步测试。 NGLY1 缺乏症:这是一种低发病率遗传病,主要影响神经系统,导致神经运动障碍、智力障碍和神经病。我们使用 NGLY1 患者 iPSC 生成了大脑类器官,用于疾病建模。我们发现,与野生型类器官相比,患者中脑类器官表现出神经元发育改变和多巴胺能神经元减少(Abbott J. et al. 2023. Front Cell Dev Biol. 11: 1039182. PMID: 36875753)。我们还开发了一个神经肌肉接头平台,利用患者 iPSC 衍生的运动神经元来研究疾病的发病机制。我们观察到该系统中轴突长度减少、轴突分支增加和缩短、运动神经元动作电位爆发以及动作电位放电率和幅度降低(Sasserath T. et al. 2022. Adv Ther 5:2200009, PMID: 36589922)。 NGLY1 脑类器官和运动神经元是研究疾病机制和评估候选治疗方法的有用模型。 莱伯先天性黑蒙 (LCA):LCA 是一种遗传性眼部疾病,会导致儿童早期失明,且缺乏有效的治疗方法。我们使用从莱伯先天性黑蒙模型的 iPSC 中分化出来的视网膜类器官进行了药物再利用筛选。利血平是一种用于治疗高血压的药物,与其他几种可维持视网膜纤毛病中光感受器存活的化合物一起被发现(Chen HY.等人2023.Elife,12:e83205.PMID:36975211)。目前,其作用机制和潜在临床前开发的进一步研究正在进行中。 基于人工智能的建模和虚拟筛选:基于人工智能 (AI) 的建模的最新进展使得虚拟化合物筛选能够用于先导化合物的识别。这种药物发现方法的优点是(1)减少物理化合物筛选实验,从而显着降低项目成本; (2) 筛选能力显着提高,因为虚拟筛选可以覆盖内部化合物集合以及大型商业集合(即数百万种化合物),这两者都可以节省先导化合物识别过程中的时间。我们开发并优化了多种基于人工智能的化合物筛选工具,并已应用于多个项目。来自小型化合物集合(例如 NCATS 提供的 2800 种已批准药物的集合)的实验筛选数据通常用于为给定项目建立、训练和优化计算机模型,然后将其用于更大的虚拟化合物筛选。化合物集合(多达数百万种化合物)来识别命中。经过计算机化的命中选择和确认后,将选择并订购最重要的化合物(通常为 50 至 200 种)进行实验室实验,以评估其活性。我们已经发表了以 SARS-CoV-2 进入抑制剂项目为例的基于 AI 的建模和虚拟筛选方法(Gao P et al., 2023. J Chem Inf Model. 62: 1988-97. PMID: 35404596)还有其他几份手稿正在准备中。

项目成果

期刊论文数量(100)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Drug Repurposing Screen for Compounds Inhibiting the Cytopathic Effect of SARS-CoV-2.
  • DOI:
    10.3389/fphar.2020.592737
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    5.6
  • 作者:
    Chen CZ;Shinn P;Itkin Z;Eastman RT;Bostwick R;Rasmussen L;Huang R;Shen M;Hu X;Wilson KM;Brooks BM;Guo H;Zhao T;Klump-Thomas C;Simeonov A;Michael SG;Lo DC;Hall MD;Zheng W
  • 通讯作者:
    Zheng W
Identification of novel anti-hepatitis C virus agents by a quantitative high throughput screen in a cell-based infection assay.
  • DOI:
    10.1016/j.antiviral.2015.10.018
  • 发表时间:
    2015-12
  • 期刊:
  • 影响因子:
    7.6
  • 作者:
    Hu Z;Hu X;He S;Yim HJ;Xiao J;Swaroop M;Tanega C;Zhang YQ;Yi G;Kao CC;Marugan J;Ferrer M;Zheng W;Southall N;Liang TJ
  • 通讯作者:
    Liang TJ
Identification of potent SENP1 inhibitors that inactivate SENP1/JAK2/STAT signaling pathway and overcome platinum drug resistance in ovarian cancer.
  • DOI:
    10.1002/ctm2.649
  • 发表时间:
    2021-12
  • 期刊:
  • 影响因子:
    10.6
  • 作者:
    Zhang Y;Wei H;Zhou Y;Li Z;Gou W;Meng Y;Zheng W;Li J;Li Y;Zhu W
  • 通讯作者:
    Zhu W
Development of a high-throughput homogeneous AlphaLISA drug screening assay for the detection of SARS-CoV-2 Nucleocapsid.
  • DOI:
    10.1101/2020.08.20.258129
  • 发表时间:
    2020-01-01
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Gorshkov, K.;Chen, C.Z.;Zheng, W.
  • 通讯作者:
    Zheng, W.
Generation of an induced pluripotent stem cell line (TRNDi003-A) from a Noonan syndrome with multiple lentigines (NSML) patient carrying a p.Q510P mutation in the PTPN11 gene.
  • DOI:
    10.1016/j.scr.2018.101374
  • 发表时间:
    2019-01
  • 期刊:
  • 影响因子:
    1.2
  • 作者:
    Rong Li;Amanda Baskfield;Yongshun Lin;J. Beers;J. Zou;Chengyu Liu;F. Jaffré;A. Roberts;E. Ottinger;M. Kontaridis;Wei Zheng
  • 通讯作者:
    Rong Li;Amanda Baskfield;Yongshun Lin;J. Beers;J. Zou;Chengyu Liu;F. Jaffré;A. Roberts;E. Ottinger;M. Kontaridis;Wei Zheng
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Wei Zheng其他文献

Wei Zheng的其他文献

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{{ truncateString('Wei Zheng', 18)}}的其他基金

Shanghai Womens Health Study
上海女性健康研究
  • 批准号:
    8634285
  • 财政年份:
    2014
  • 资助金额:
    $ 285.93万
  • 项目类别:
Shanghai Womens Health Study
上海女性健康研究
  • 批准号:
    9344545
  • 财政年份:
    2014
  • 资助金额:
    $ 285.93万
  • 项目类别:
Genome Sequencing to identify novel genetic factors for breast cancer risk
基因组测序识别乳腺癌风险的新遗传因素
  • 批准号:
    8826570
  • 财政年份:
    2012
  • 资助金额:
    $ 285.93万
  • 项目类别:
Genome Sequencing to identify novel genetic factors for breast cancer risk
基因组测序识别乳腺癌风险的新遗传因素
  • 批准号:
    9248682
  • 财政年份:
    2012
  • 资助金额:
    $ 285.93万
  • 项目类别:
Genome Sequencing to identify novel genetic factors for breast cancer risk
基因组测序识别乳腺癌风险的新遗传因素
  • 批准号:
    8468665
  • 财政年份:
    2012
  • 资助金额:
    $ 285.93万
  • 项目类别:
Genome Sequencing to identify novel genetic factors for breast cancer risk
基因组测序识别乳腺癌风险的新遗传因素
  • 批准号:
    8237390
  • 财政年份:
    2012
  • 资助金额:
    $ 285.93万
  • 项目类别:
Genome Sequencing to identify novel genetic factors for breast cancer risk
基因组测序识别乳腺癌风险的新遗传因素
  • 批准号:
    9026483
  • 财政年份:
    2012
  • 资助金额:
    $ 285.93万
  • 项目类别:
Survey and Biospecimen Shared Resource
调查和生物样本共享资源
  • 批准号:
    8180575
  • 财政年份:
    2010
  • 资助金额:
    $ 285.93万
  • 项目类别:
Genetic Factors for Breast Cancer- A genome Wide Study
乳腺癌的遗传因素——全基因组研究
  • 批准号:
    8265665
  • 财政年份:
    2008
  • 资助金额:
    $ 285.93万
  • 项目类别:
Genetic Factors for Breast Cancer- A genome Wide Study
乳腺癌的遗传因素——全基因组研究
  • 批准号:
    7848916
  • 财政年份:
    2008
  • 资助金额:
    $ 285.93万
  • 项目类别:

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ABCB1甲基化水平调控T淋巴细胞内CsA浓度引起CsA药效学差异的研究
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    20.1 万元
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  • 批准号:
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Immunoregulatory Therapeutics for Ulcerative Colitis
溃疡性结肠炎的免疫调节治疗
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    2023
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  • 项目类别:
Training the Next Generation of Psychiatrists-Scientists for Translational Research
培训下一代精神病学家-科学家进行转化研究
  • 批准号:
    10627452
  • 财政年份:
    2023
  • 资助金额:
    $ 285.93万
  • 项目类别:
Studies of P-glycoprotein Drug Interactions - Administrative Supplement for Undergraduate Summer Research
P-糖蛋白药物相互作用的研究 - 本科生暑期研究行政补充
  • 批准号:
    10810072
  • 财政年份:
    2022
  • 资助金额:
    $ 285.93万
  • 项目类别:
Multifunctional Nanotechnology Platform for Triple Negative Breast Cancer Treatment
用于三阴性乳腺癌治疗的多功能纳米技术平台
  • 批准号:
    10672232
  • 财政年份:
    2022
  • 资助金额:
    $ 285.93万
  • 项目类别:
Perioperative Precision Medicine: Translating Science to Clinical Practice to Improve Safety and Efficacy of Opioids in Neonates, Children and Nursing Mothers
围手术期精准医学:将科学转化为临床实践,提高阿片类药物对新生儿、儿童和哺乳期母亲的安全性和有效性
  • 批准号:
    10676237
  • 财政年份:
    2022
  • 资助金额:
    $ 285.93万
  • 项目类别:
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