Antiviral targeting to suppress drug resistance

抗病毒靶向抑制耐药性

• 批准号: 10513871
• 负责人: John Damon Chodera
• 金额: $ 213.26万
• 依托单位: SLOAN-KETTERING INST CAN RESEARCH
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-16 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10513871
• 关键词: Drug resistance; Structure

The last decades have emphasized the pandemic potential of the flaviviruses, picornaviruses and coronaviruses. Traditional drug discovery approaches for antiviral agents have generally focused on direct-acting inhibitors of viral targets, usually enzymes, that disrupt function and thus inhibit viral growth. However, the effectiveness of loss-of-function antivirals can be rapidly overcome by the outgrowth of drug-resistant variants. Multi-drug therapy is an effective solution to this problem that has been employed for HIV and hepatitis C viruses. Unfortunately, multi-drug therapy remains an expensive, long-term approach ill-suited to rapid response to new pandemic viruses and use in impoverished settings. To address this challenge in antiviral drug development, Project 1 will use a combination of genetic strategies and deep mutational analysis to identify specific viral proteins and small molecule targeting strategies with the aim of suppressing the selection of drug-resistant viral variants. We will focus on identifying proteins that have the potential, when bound to inhibitors, to be 'dominant disruptors' of viral RNA replication or virion function by producing or acting as 'molecular poisons' towards all developing viruses inside an infected cell. In this scenario, the drug-susceptible parent viruses can act as dominant killers of drugresistant variants, thus blocking the propagation of resistance. Our data have identified both viral proteases and capsid protein targets as having potential to induce dominant-disruptor phenotypes upon binding smallmolecules drugs. In addition, deep mutational scanning and biochemical methods will enable us to identify specific small-molecule binding sites on diverse viral targets that further avoid resistance by targeting locations at which mutations are not tolerated due to fitness cost. The combination of these approaches will yield both genetically validated viral targets, and particular regions of viral targets, that can suppress the formation of drug resistance as well as approaches for small-molecule targeting that are unlikely to allow the selection for resistance through classical mutational variation. These targets can then enter the consortium pipeline for rapid progression to screening, hit-to-lead development and validation in animal models of infection.

最后几十年强调了黄病毒，picornavirus和冠状病毒的大流行潜力。 抗病毒药物的传统药物发现方法通常集中于直接作用抑制剂 病毒靶标，通常是酶，会破坏功能，从而抑制病毒生长。但是，有效性 功能丧失的抗病毒药可以通过抗药性变体的生长来迅速克服。多药疗法 是解决此问题的有效解决方案，该问题已用于HIV和丙型肝炎病毒。很遗憾， 多药疗法仍然是一种昂贵的长期方法，不适合快速反应新大流行 病毒并在贫困的环境中使用。为了应对抗病毒药物开发中的这一挑战，项目1将 结合遗传策略和深层突变分析来鉴定特定的病毒蛋白和小 分子靶向策略，目的是抑制抗药性病毒变异的选择。我们将 专注于识别有可能与抑制剂成为病毒的“主要破坏者”的蛋白质 RNA复制或病毒粒子功能通过产生或作用于所有发育中的病毒的“分子毒物” 在感染的细胞内。在这种情况下，药物敏感的母病毒可以充当耐药的杀手 变体，因此阻止了电阻的传播。我们的数据已经确定了病毒蛋白酶和 衣壳蛋白靶标具有在结合小分子后诱导显性干扰表型的潜力 毒品。此外，深度突变扫描和生化方法将使我们能够识别 特定的小分子结合位点在不同的病毒靶标上 由于健身成本，未能容忍突变。这些方法的结合将既产生 经遗传验证的病毒靶标和病毒靶标的特定区域，可以抑制药物的形成 电阻以及小分子靶向的方法，不太可能允许选择 通过经典突变变异的抗性。然后，这些目标可以进入联盟管道以快速 在感染动物模型中筛查，命中率发育和验证。