Preclinical discovery of novel farnesyltransferase inhibitors for the treatment of Alzheimer's disease and related tauopathies

用于治疗阿尔茨海默病和相关 tau蛋白病的新型法尼基转移酶抑制剂的临床前发现

• 批准号: 10367882
• 负责人: Steven H Olson
• 金额: $ 94.21万
• 依托单位: SANFORD BURNHAM PREBYS MEDICAL DISCOVERY INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-15 至 2025-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10367882
• 关键词: Affinity; Alzheimer' s Disease; Alzheimer' s disease patient; American; Amyloid beta-Protein; Animal Model; Artificial Intelligence; Attenuated; Back; Behavioral; Binding; Biological Assay; Brain; Chemicals; Clinic; Clinical; Clinical Trials; Computer Assisted; Crystallization; Custom; Data; Dementia; Disease; Disease Progression; Dose; Drug Design; Drug Kinetics; Drug Targeting; Elements; Family; Farnesyl Transferase Inhibitor; Goals; Guanosine Triphosphate Phosphohydrolases; Human; Human Development; Impaired cognition; Knowledge; Laboratories; Lead; Legal patent; Libraries; Lonafarnib; Longevity; Longitudinal Studies; Lysosomes; Malignant Neoplasms; Mediating; Methods; Mus; Neurodegenerative Disorders; Neurofibrillary Tangles; Pathologic; Pathology; Pathway interactions; Patients; Pharmaceutical Preparations; Pharmacodynamics; Pharmacology; Pharmacotherapy; Process; Property; Proteins; Public Health; Publishing; Pump; Reporting; Research; Research Design; Risk; Roentgen Rays; Senile Plaques; Small Interfering RNA; Structure; Tauopathies; Testing; Therapeutic; Translating; Validation; Work; aging population; amyloid formation; analog; artificial intelligence algorithm; base; cancer therapy; chemical property; design; drug candidate; drug discovery; effective therapy; efficacy study; efficacy testing; efflux pump; experience; extracellular; farnesylation; functional group; high throughput screening; in silico; in vivo; inhibitor; innovation; lead optimization; mouse model; neural network; neurofibrillary tangle formation; neuron loss; new therapeutic target; novel; pharmacodynamic model; pre-clinical; preclinical evaluation; prevent; protein degradation; proteostasis; small molecule; small molecule libraries; tau Proteins; tau aggregation; tau mutation; virtual

PROJECT SUMMARY Alzheimer’s disease (AD) is a fatal disease that currently afflicts almost six million Americans. With an aging population, we risk a public health crisis by 2050, unless effective treatments are identified. Despite extensive research, there are currently no drugs that slow or alter the course of disease. AD is defined by the presence of β-amyloid (Aβ) plaques and intraneuronal tau inclusions called neurofibrillary tangles (NFTs) in the brain. Drug candidates that reduce Aβ plaques have not, yet, been shown to have clinical benefit, and growing data suggests that it may be more important to target NFTs over Aβ plaques to prevent cognitive decline. Recently, the macroautophagy-lysosomal pathway of protein degradation has emerged as a compelling target for reducing pathogenic tau in the brain. Our hypothesis is that increasing the rate of tau degradation will reduce tau levels and stop, or greatly slow, the rate of tau aggregation. We recently discovered a novel pathway to accomplish this objective. Inhibiting the farnesylation of Rhes, a GTPase protein in the Ras family, activates the lysosome and results in the selective degradation of pathological tau. Confirmation of the therapeutic hypothesis was achieved by administering a farnesyltransferase inhibitor (FTI) in a mouse model of tauopathy, which reduced tau pathology and attenuated behavioral abnormalities in the mice. Known FTIs are not suitable for human development as CNS drugs. Optimized for cancer indications, they are efficiently pumped out of the brain by efflux proteins. We propose a three-pronged approach to identify chemical matter that can reach pharmacologically significant and dose-proportional brain levels. For two of the known inhibitors, L-778,123 and lonafarnib, we will make strategic changes to the structures, eliminating functional groups that serve as recognition substrates for the efflux pumps. Concurrently, we will initiate a high- throughput screen of a chemical library with chemical properties consistent with known CNS drugs. As a third step, we will engage in a multi-million compound artificial intelligence-based virtual screen with AtomWise to identify novel FTIs. By generating x-ray co-crystal structures of the most promising hits and using computer- aided drug design, we plan to accelerate the process of hit validation, lead discovery, and optimization to identify small molecule drug candidates. We will advance inhibitors to an in vivo pharmacodynamic model and select compounds with linear pharmacokinetic/pharmacodynamic (PK/PD) relationships that can be advanced into the clinic. Three of the top compounds will be tested for efficacy in a tauopathy animal model using doses derived from the PK/PD relationship. Short-term studies will identify compounds that reduce all pathogenic tau species. The most efficacious compound will be moved into long-term dosing studies to evaluate life-span extension and reduction in NFT formation.

项目总结 阿尔茨海默病(AD)是一种致命的疾病，目前困扰着近600万美国人。带着一个 随着人口老龄化，我们面临着到2050年公共卫生危机的风险，除非找到有效的治疗方法。尽管 广泛的研究表明，目前还没有延缓或改变病程的药物。广告由 β-淀粉样蛋白(A-β)斑块和称为神经原纤维缠结(NFT)的神经元内tau包涵体的存在 大脑。减少Aβ斑块的候选药物尚未被证明具有临床益处，以及 越来越多的数据表明，将NFT定位于Aβ斑块可能更重要，以防止认知 拒绝。最近，蛋白质降解的大自噬-溶酶体途径已经出现为一种 减少大脑中致病tau的引人注目的目标。我们的假设是，增加牛磺酸的比率 降解会降低tau的水平，并停止或极大地减缓tau的聚集速度。我们最近 发现了一条实现这一目标的新途径。抑制GTP酶Resh的法尼化 RAS家族中的蛋白质，激活溶酶体，导致病理性的选择性降解 陶先生。治疗假说的确认是通过给予法尼基转移酶抑制剂实现的 (FTI)在牛磺酸病小鼠模型中，该药减少了tau的病理变化并减轻了小鼠的行为异常 老鼠。 已知的FTI作为中枢神经系统药物不适合人类发育。针对癌症适应症进行了优化， 它们可以通过外流蛋白有效地从大脑中排出。我们提出了一个三管齐下的方法来识别 化学物质可以达到具有药理意义和剂量比例的大脑水平。对于其中两个 已知的抑制剂L-778,123和洛那法尼，我们将对结构进行战略性改变，消除 用作外排泵识别底物的官能团。同时，我们将启动一项高- 化学性质与已知中枢神经系统药物一致的化学文库的吞吐量筛选。作为第三人 一步，我们将参与到一个基于数百万复合人工智能的虚拟屏幕上，用Air Wise来 识别新的FTI。通过产生最有希望的HITS的X射线共晶结构，并使用计算机- 辅助药物设计，我们计划加快HIT验证、领先发现和优化的过程，以 确定小分子药物候选药物。我们将把抑制剂推进到体内药效学模型 并选择具有线性药代动力学/药效学(PK/PD)关系的化合物 进了诊所。其中三种顶级化合物将在直肠肌萎缩症动物模型中进行疗效测试 使用由PK/Pd关系得出的剂量。短期研究将确定能够降低所有 致病的tau物种。最有效的化合物将进入长期剂量研究，以 评估NFT地层的寿命延长和减少。