Screening core

核心2：筛选 总结 持续的COVID-19大流行需要紧急开发新药，并进一步强调了 美国迫切需要建立一个广泛作用的抗病毒药物库，用于大流行的RNA病毒。 潜力QCRG大流行应对计划将开发3 - 6个优化的临床前和 我们的制药合作伙伴的临床开发。为了完成这一使命，QCRG将起诉15名 在七个病毒家族的八个靶类中的抗病毒靶点。六个项目将与八个核心合作， 遵循严格的药物发现工作流程，从目标表征，命中识别，命中到铅 优化和铅优化。筛选核心将推动命中识别，与项目合作 1-6提供30 - 40个经验证的命中与初步的结构-活性关系（SAR）和定义的机制 行动计划（MoA），以启动命中到铅。在Hit-to-Lead期间，筛选核心将进一步支持项目1 - 6 通过生物物理分析和人工检测筛选来表征MoA，并支持选择性面板 以及通过分析自动化进行组合研究。筛选核心将与项目密切合作， 生物化学核心，药物化学核心，体外病毒学核心和蛋白质组学核心，以确保 最有前途的化学系列被开发成先导物。完成命中的发现和验证 就项目1 - 6而言，筛选核心将实现以下具体目标：目标1。识别化学物质 在多个病毒家族中的12个抗病毒靶类。每个项目的筛选策略将基于 目标生物学、分析能力和适当的化学库。至少有两种技术，包括HTS， 超大型文库对接和基于片段的筛选将应用于每个项目。图书馆可用于 这些项目包括30亿种用于对接的化合物，约25.5万种用于高温超导的化合物， ~6000个不同片段和1600个混合二硫化物用于片段筛选。SARS-CoV2的命中将被测试 针对一组来自其他病毒的同源靶标。目标二。通过计数器的活性分子 筛选和生物物理测定。从筛选中选择的分子可以通过非药物样MoA起作用。 项目1 - 6将利用一套计数器筛选和生物物理分析，旨在确定化合物 聚集、结合可逆性（需要时）和结合化学计量。细胞活性化合物将是 进行磷脂沉积症的评估，这是一种常见的抗病毒伪影。目标3：通过以下方式建立化学品易处理性 片段优化和命中扩展。已确认的命中从命中识别过渡到命中到销售线索 IC 50/KD值应在低µ M范围内，初步SAR表明其化学易处理性。的 通过HTS和共价方法发现的化合物可能已经具有该范围内的亲和力;如果是这样， 目录化学和合成将侧重于开发合成孔径雷达。碎片可能需要化学物质 通过对接和结构生物学指导的片段连接、合并和设计进行优化。这些目标 将在Hit-to-Lead期间产生30 - 40个经验证的命中以进行优化。

CORE 2: SCREENING SUMMARY The ongoing COVID-19 pandemic requires urgent development of new drugs, and furthermore highlights the critical need for the US to build an arsenal of broadly acting antiviral drugs for RNA viruses with pandemic potential. The QCRG Pandemic Response Program will develop 3-6 Optimized Leads for preclinical and clinical development by our pharmaceutical partners. To achieve this mission, the QCRG will prosecute fifteen antiviral targets in eight target classes across seven virus families. Six Projects will work with eight Cores, following a rigorous drug-discovery workflow from Target Characterization, Hit Identification, Hit-to-Lead optimization, and Lead Optimization. The Screening Core will drive Hit Identification, collaborating with Projects 1-6 to deliver 30-40 validated hits with preliminary structure-activity relationships (SAR) and defined mechanisms of action (MoA) to initiate Hit-to-Lead. During Hit-to-Lead, the Screening Core will further support Projects 1-6 to characterize MoA through biophysical assays and artifact-detecting screens, and to support selectivity panels and combination studies through assay automation. The Screening Core will work closely with the Projects, Biochemistry Core, Medicinal Chemistry Core, In Vitro Virology Core, and Proteomics Core to ensure that the most promising chemical series are developed into leads. To accomplish the discovery and validation of hits for Projects 1-6, the Screening Core will achieve the following Specific Aims: Aim 1. Identify chemical matter for twelve antiviral target classes in multiple viral families. Screening strategy for each Project will based on the target biology, assay-ability, and appropriate chemical libraries. At least two technologies, including HTS, ultra-large library docking, and fragment-based screening, will be applied to each project. Libraries available for the projects include 3 billion enumerated compounds for docking, ~255,000 diverse compounds for HTS, and ~6000 diverse fragments and 1600 mixed disulfides for fragment screens. Hits from SARS-CoV2 will be tested against a panel of homologous targets from other viruses. Aim 2. Validate active molecules through counter screens and biophysical assays. Molecules selected from screens can act through non-drug-like MoA. Projects 1-6 will utilize a suite of counter screens and biophysical assays designed to identify compound aggregation, binding reversibility (where desired), and binding stoichiometry. Cell-active compounds will be evaluated for phospholipidosis, a common antiviral artifact. Aim 3. Establish chemical tractability through fragment optimization and hit expansion. Validated hits transitioning from Hit Identification to Hit-to-Lead should have IC50/KD values in the low µM range, with preliminary SAR to indicate their chemical tractability. The compounds discovered through HTS and covalent approaches may already have affinities in this range; if so, chemistry-by-catalog and synthesis will focus on developing SAR. Fragments will likely require chemical optimization via fragment linking, merging, and design, guided by docking and structural biology. These Aims will yield 30-40 validated hits for optimization during Hit-to-Lead.