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: 10686748
• 负责人: Donald Lo
• 金额: $ 77.54万
• 依托单位: NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10686748
• 关键词: 2019-nCoV; Address; Advanced Development; Antibodies; Antiviral Agents; Artificial Intelligence; Autophagocytosis; Biological; Biological Assay; Biological Availability; Biological Models; Biological Products; Biomedical Research; Biotechnology; COVID-19; COVID-19 assay; COVID-19 pandemic; COVID-19 patient; COVID-19 pneumonia; COVID-19 therapeutics; COVID-19 treatment; COVID-19 vaccine; Cell Death; Cell Surface Receptors; Cells; Clinical; Clinical Investigator; Clinical Trials; Collaborations; Collection; Communities; Data; Data Set; Databases; Deposition; Development; Disease; Drug Combinations; Drug Kinetics; Ebola virus; Enzymes; Fluorescence Resonance Energy Transfer; Formulation; GS-441524; Government; Host Defense Mechanism; Human; Industry; Infection; Investigation; Investigational Drugs; Investigational New Drug Application; Joints; Journals; Laboratories; Leadership; Luciferases; Measures; Mediating; Methods; Modeling; Mutation; Names; National Center for Advancing Translational Sciences; Nature; Neutralization Tests; Peptide Hydrolases; Pharmaceutical Preparations; Pharmacologic Substance; Pharmacology; Plasmids; Play; Positioning Attribute; Process; Proteins; Protocols documentation; Public Health; Publishing; RNA; RNA-Directed RNA Polymerase; Rapid screening; Reporter; Reporter Genes; Research; Research Activity; Research Institute; Research Personnel; Research Support; Resources; Role; SARS-CoV-2 entry inhibitor; SARS-CoV-2 spike protein; SARS-CoV-2 variant; Safety; Scientist; Signal Transduction; Societies; Standardization; System; Testing; Texas; Therapeutic; Therapeutic Intervention; Time; Toxicology; Transfection; Translational Research; Treatment Efficacy; United States National Institutes of Health; Universities; Vaccinated; Vaccines; Variant; Viral; Viral Packaging; Viral Proteins; Virus; Virus Replication; Work; Zika Virus; atypical pneumonia; base; betacoronavirus; clinical candidate; clinical development; clinical efficacy; clinical investigation; cofactor; cost; data portal; drug candidate; drug development; drug metabolism; drug repurposing; effectiveness evaluation; efficacy evaluation; efficacy testing; experience; high throughput screening; model development; mutant; nanobodies; novel; novel strategies; novel therapeutics; online resource; open data; operation; pandemic disease; particle; pharmacokinetic model; pharmacokinetics and pharmacodynamics; public-private partnership; research clinical testing; response; screening; sharing platform; small molecule; surveillance data; therapeutic candidate; therapeutic development; therapeutic vaccine; vaccine effectiveness; viral RNA; viral detection; virtual; virtual model; virtual screening

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.

TDB科学家在开发新型治疗候选者以及重新利用现有治疗方法方面具有丰富的经验。药物重新利用试图探索已经拥有详细的药理学，配方和安全数据的现有药物和治疗候选者的新用途，这可以减少为新指示进行临床测试的时间。为了应对公共卫生危机，TDB进行了几次专注于SARS-COV-2的合作。正在研究的靶标包括通过病毒尖峰蛋白与人类细胞表面受体的相互作用，病毒式进入辅助因子/共肽和病毒RNA依赖RNA依赖性RNA聚合酶（RDRP）的相互作用，包括细胞自噬，病毒进入细胞的宿主防御机制。 TDB已进行了许多重新利用的筛选工作以及GS-441524的指定发展。后者包括药物代谢和药代动力学（PK）研究，人类PK建模，毒理学研究，药物制造和制剂研究。 TDB科学家还进行了辅助的虚拟化合物筛选，以识别潜在的COVID-19治疗方法。 TDB科学家还为开放数据门户提供了分析数据和协议，该门户网站是NCAT创建的，旨在容纳与SARS-COV-2相关的测定法对NCATS Pharmaceutical Collection（NPC）中所有认可的药物产生的数据集。这项工作旨在在开放数据共享平台中分享相关数据，以允许研究科学家，临床研究人员和公共卫生官员优先考虑有希望的化合物和重新使用的药物，以进一步开发Covid-19。此外，TDB科学家通过使用SARS-COV-2伪分型粒子（PP）进入测定法参加了COVID-19 Actiac Trace计划，以测试当前疗法的效率，并通过对新兴的SARS-COV-2变体进行疫苗接种人类血清，从而提供NIH的领导力和科学界，从而为NIH的领导和科学社区提供了重要的数据，从而提供了重要的数据。 列出特定的协作 我们曾与NIH内外的专家合作，开发了几种重新利用批准的药物收集屏幕的测定方法，以鉴定有效的SARS-COV-2的化合物，并评估针对新兴SARS-COV-2变体的治疗疗法的功效。从此类筛选中鉴定出的化合物具有临床试验的潜力，例如单个药物或药物组合，以治疗COVID-19患者。 （1）SARS-COV-2伪型粒子（PP）条目测定。与加里·惠特克（Gary Whittaker）（康奈尔大学）合作，使用包含MLV GAG-POL，COV SPIKE和LUCIFERASE REPORTER基因的三个质粒转染系统生成PPS。在测定过程中，PPS通过尖峰介导的细胞进入向宿主细胞传递荧光素酶报告基因RNA。该测定法已用于筛选SARS-COV-2进入的抑制剂，以及从其他测定中鉴定出的其他化合物的机械研究。我们已经使用该测定法支持针对SARS-COV-2的纳米机构开发。我们还将该测定法应用于新兴的SARS-COV-2尖峰突变，并开发了约20种伪型粒子（PP）输入测定，其中包含突变峰蛋白，包括来自Alpha，Delta和Omicron变体的蛋白质。 （2）确定疫苗和治疗剂对SARS-COV-2变体的有效性。 COVID-19 Activ Trace倡议是加速Covid-19治疗干预措施和疫苗（ACTIV）公私合作伙伴关系下的任务。随着SARS-COV-2病毒的不断发展，随着时间的流逝，变异突变的监视及其对Covid-19-19疫苗和治疗学的影响是涉及多个政府组织的关键任务。 TDB科学家已针对SARS-COV-2尖峰蛋白的变体采用SARS-COV-2伪分型粒子进入测定法，以测试SARS-COV-2疫苗接种的血清的中和效力，并针对包括Delta和Omicron在内的20多个SARS-COV-2变体。使用NCATS Opendata Portal（用于研究社区的基于网络的资源），所有数据都已快速并公开传播。他们的工作为NIH领导力，行业，学术合作伙伴和外部研究社区提供了全面的标准化评估，对当前的治疗和疫苗如何受到新兴SARS-COV-2变体影响。 （3）与南方研究所（SRI）合作的VERO 6细胞中的SARS-COV-2细胞疗法测定法。 NCATY和外部合作者的化合物和抗体使用NCATS在SRI的BSL-3实验室中制备的测定板进行了筛选。该测定也已用于评估和确认从NCATSS BSL-2分析中鉴定的化合物的抗SARS-COV-2活性。 （4）SARS-COV-2 3CL蛋白酶（也称为主要蛋白酶）测定法。这种病毒蛋白酶在SARS-COV-2病毒复制中起关键作用。我们已经开发并优化了该酶测定法，并筛选了大约10,000种化合物的集合。我们还应用了3clPro的虚拟建模屏幕，其中包含整个NCATS化合物和商业化合物。所有数据都已存入Opendata门户，以供公共访问。 （5）实时SARS-COV-2病毒检测的同质高通量筛选测定法。我们已经开发了两个均质测定法，包括α分析和TR-FRET（HTRF）测定法以检测N蛋白。这种类型的测定法测量了用作细胞中SARS-COV-2病毒复制的指标的病毒蛋白。这是对SARS-COV-2的细胞质效应（CPE）测定的另一种活病毒测定法，该测定法使用替代读数（细胞死亡）进行宿主细胞感染。我们目前正在使用其BSL-3实验室中使用该测定法的德克萨斯生物医学研究所合作，以鉴定新的抗病毒药化合物。 （6）虚拟化合物筛选。人工智能（AI）辅助虚拟化合物筛选最近已成为一种新的方法，用于访问内部和商业化合物。优点包括快速筛选过程，降低化合物筛选成本以及访问大型化合物收集，而无需物理购买和筛选大多数这些化合物。我们已经开发了一种称为基于生物活动的建模（BABM）方法的新建模系统。这种新的虚拟筛选方法采用了在过去15年中在NCAT数据库中积累的多个测定中建立的复合活动概况，作为签名，以预测针对新目标的新命中。通过基于高通量筛查数据来鉴定寨卡和埃博拉病毒的候选抗病毒药物来验证这种方法。然后，将BABM模型应用于预测对SARS-COV-2潜在活性的311种化合物，该化合物已发表在《自然生物技术杂志》上。