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