COVID-19: Identification and Development of Clinical Candidates to Treat SARS-CoV-2

COVID-19:识别和开发治疗 SARS-CoV-2 的临床候选药物

基本信息

项目摘要

TDB scientists have extensive experience in developing novel therapeutic candidates as well as repurposing existing treatments for novel therapeutic purposes. Drug repurposing seeks to explore new uses for existing drugs and therapeutic candidates that already possess detailed pharmacology, formulation, and safety data, which can reduce the time to reach clinical testing for the new indication. In response to the public health crisis, TDB has engaged in several collaborations focused on SARS-CoV-2. Targets under investigation include host defense mechanisms, such as cellular autophagy, viral entry into cells through interaction of the viral spike protein with human cell surface receptors, viral entry cofactors/coreceptors, and viral RNA-dependent RNA polymerase (RdRp). TDB has performed a number of repurposing screening efforts and the IND-directed development of GS-441524. The latter included drug metabolism and pharmacokinetic (PK) studies, human PK modeling, toxicology studies, drug substance manufacture and formulation studies. TDB scientists also have performed AI- assisted virtual compound screens to identify therapeutics for potential COVID-19 treatments. TDB scientists are also contributing assay data and protocols to the Open Data Portal, a resource created by NCATS to house a collection of datasets generated from SARS-CoV-2-related assays against all approved drugs in the NCATS Pharmaceutical Collection (NPC). This effort aims to share COVID-19 related data in an open data-sharing platform to allow research scientists, clinical investigators and public health officials to prioritize promising compounds and repurposed drugs for further development in treating COVID-19. In addition, TDB scientists have participated in the COVID-19 ACTIV TRACE initiative by using the SARS-CoV-2 pseudotyped particle (PP) entry assays to test the efficacies of current therapeutics and vaccinated human sera against the emerging SARS-CoV-2 variants, providing the NIH leadership and scientific community with the important data for surveillance of virus mutations. List specific collaborations We have worked in collaboration with experts in and outside of NIH on the development of several assays for repurposing screens of approved drug collections to identify compounds active against SARS-CoV-2 and evaluate efficacies of therapeutics against emerging SARS-CoV-2 variants. The compounds identified from such screens have potential for clinical trials as single agents or in drug combinations to treat COVID-19 patients. (1) SARS-CoV-2 pseudotyped particle (PP) entry assay. In collaboration with Gary Whittaker (Cornell University), the PPs were generated with three plasmid transfection system containing MLV gag-pol, CoV spike, and luciferase reporter gene w/ viral packaging signal. In the assay process, the PPs deliver luciferase reporter RNA to host cells via spike-mediated cell entry. This assay has been used for screen the inhibitors of SARS-CoV-2 entry as well as the mechanistic study of other compounds identified from other assays. We have used this assay to support the nanobody development against SARS-CoV-2. We also have applied this assay to emerging SARS-CoV-2 spike mutations and have developed about 20 pseudotyped particle (PP) entry assays that containing mutant spike proteins including those from alpha, delta and omicron variants. (2) Determining the effectiveness of vaccines and therapeutics on SARS-CoV-2 variants. The COVID-19 ACTIV TRACE initiative that is a task under the Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) public-private partnership. As the SARS-CoV-2 virus continues to evolve over time, the surveillance of variant mutations, and their impact on COVID-19 vaccines and therapeutics is a critical task that involves multiple government organizations. TDB scientists have employed the SARS-CoV-2 pseudotyped particle entry assay for variants of SARS-CoV-2 spike proteins to test the neutralization potency of SARS-CoV-2 vaccinated sera and therapeutics against more than 20 SARS-CoV-2 variants, including delta and omicron. All the data have been quickly and openly disseminated using the NCATS OpenData Portal, a web-based resource for the research community. Their work has provided the NIH leadership, industry, academic partners, and the external research community with a comprehensive, standardized assessment of how current therapeutics and vaccines are impacted by emerging SARS-CoV-2 variants. (3) A SARS-CoV-2 cytopathic effect assay in Vero 6 cells in collaboration with the Southern Research Institute (SRI). The compounds and antibodies from NCATYS and outside collaborators were screened using assay ready plates, prepared by NCATS, in the BSL-3 lab at SRI. This assay has also been used to evaluate and confirm anti-SARS-CoV-2 activities of compounds identified from NCATSs BSL-2 assays. (4) A SARS-CoV-2 3CL protease (also named main protease) assay. This viral protease plays a critical role in SARS-CoV-2 viral replication. We have developed and optimized this enzyme assay and screened a collection of approximately 10,000 compounds. We also applied a virtual modeling screen of 3CLpro with the entire NCATS compound collection and commercial compounds. All the data have been deposited into the OpenData portal for public access. (5) Homogenous high throughput screening assays for live SARS-CoV-2 virus detection. We have developed two homogeneous assays including the AlphaLISA assay and TR-FRET (HTRF) assay to detect the N-proteins. This type of assays measures the viral proteins that is used as an indicator of SARS-CoV-2 virus replication in cells. It is an alternative live virus assay to the cytopathic effect (CPE) assay of SARS-CoV-2 which uses a surrogate readout (cell death) for host cell infection. We are currently collaborating with the Texas Biomedical Research Institute for compound screening using this assay in their BSL-3 laboratory to identify new antiviral compounds. (6) Virtual compound screening. Artificial intelligence (AI) assisted virtual compound screening has emerged recently as a new approach to access large compound collections, both internal and commercial ones. The advantages include rapid screening process, reduction of compound screening cost, and accessing large compound collections without physically purchasing and screening most of these compounds. We have developed a new modeling system called biological activity-based modeling (BABM) approach. This new virtual screening method employs compound activity profiles established across multiple assays that have been accumulated in NCATS databased over last 15 years as signatures to predict new hits against new targets. This approach was validated by identifying candidate antivirals for Zika and Ebola viruses based on high-throughput screening data. BABM models were then applied to predict 311 compounds with potential activity against SARS-CoV-2 that has been published in the journal of Nature Biotechnology.

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(1)

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Donald Lo其他文献

Donald Lo的其他文献

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{{ truncateString('Donald Lo', 18)}}的其他基金

Studies of Tumor-Penetrating Microparticles for Pancreatic Cancer
肿瘤穿透微粒治疗胰腺癌的研究
  • 批准号:
    10470633
  • 财政年份:
  • 资助金额:
    $ 77.54万
  • 项目类别:
Studies of Tumor-Penetrating Microparticles for Pancreatic Cancer
肿瘤穿透微粒治疗胰腺癌的研究
  • 批准号:
    10685882
  • 财政年份:
  • 资助金额:
    $ 77.54万
  • 项目类别:
HDAC/PI3K Dual Inhibitors for Treatment of Rare Cancers
HDAC/PI3K 双重抑制剂治疗罕见癌症
  • 批准号:
    10470638
  • 财政年份:
  • 资助金额:
    $ 77.54万
  • 项目类别:
Evaluation of ACT1 to Treat Diabetic Keratopathy
ACT1 治疗糖尿病角膜病的评价
  • 批准号:
    10470634
  • 财政年份:
  • 资助金额:
    $ 77.54万
  • 项目类别:
Helping to End Addiction Long-term (HEAL): Development of Clinical Candidate Drugs for Pain, Addiction and Overdose
帮助长期戒除成瘾 (HEAL):开发治疗疼痛、成瘾和药物过量的临床候选药物
  • 批准号:
    10686744
  • 财政年份:
  • 资助金额:
    $ 77.54万
  • 项目类别:
HDAC/PI3K Dual Inhibitors for Treatment of Rare Cancers
HDAC/PI3K 双重抑制剂治疗罕见癌症
  • 批准号:
    10259368
  • 财政年份:
  • 资助金额:
    $ 77.54万
  • 项目类别:
COVID-19: Identification and Development of Clinical Candidates to Treat SARS-CoV-2
COVID-19:识别和开发治疗 SARS-CoV-2 的临床候选药物
  • 批准号:
    10259371
  • 财政年份:
  • 资助金额:
    $ 77.54万
  • 项目类别:
Development of Nogo Receptor Decoy for the Treatment of Spinal Cord Injury
用于治疗脊髓损伤的 Nogo 受体诱饵的开发
  • 批准号:
    10686732
  • 财政年份:
  • 资助金额:
    $ 77.54万
  • 项目类别:
HDAC/PI3K Dual Inhibitors for Treatment of Rare Cancers
HDAC/PI3K 双重抑制剂治疗罕见癌症
  • 批准号:
    10686743
  • 财政年份:
  • 资助金额:
    $ 77.54万
  • 项目类别:
HEAL: Development of Clinical Candidate Drugs for Pain, Addiction and Overdose
HEAL:开发治疗疼痛、成瘾和药物过量的临床候选药物
  • 批准号:
    10259369
  • 财政年份:
  • 资助金额:
    $ 77.54万
  • 项目类别:

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