Transthyretin (TTR) is one of thirty non-homologous proteins whose misfolding, dissociation, aggregation, and deposition is linked to human amyloid diseases. Previous studies have identified that TTR amyloidogenesis can be inhibited through stabilization of the native tetramer state by small molecule binding to the thyroid hormone sites of TTR. We have evaluated a new series of β-aminoxypropionic acids (compounds 5–21), with a single aromatic moiety (aryl or fluorenyl) linked through a flexible oxime tether to a carboxylic acid. These compounds are structurally distinct from the native ligand thyroxine and typical halogenated biaryl NSAID-like inhibitors to avoid off-target hormonal or anti-inflammatory activity. Based on an in vitro fibril formation assay, five of these compounds showed significant inhibition of TTR amyloidogenesis, with two fluorenyl compounds displaying inhibitor efficacy comparable to the well-known TTR inhibitor diflunisal. Fluorenyl 15 is the most potent compound in this series and importantly does not show off-target anti-inflammatory activity. Crystal structures of the TTR∶inhibitor complexes, in agreement with molecular docking studies, revealed that the aromatic moiety, linked to the sp²-hybridized oxime carbon, specifically directed the ligand in either a forward or reverse binding mode. Compared to the aryl family members, the bulkier fluorenyl analogs achieved more extensive interactions with the binding pockets of TTR and demonstrated better inhibitory activity in the fibril formation assay. Preliminary optimization efforts are described that focused on replacement of the C-terminal acid in both the aryl and fluorenyl series (compounds 22–32). The compounds presented here constitute a new class of TTR inhibitors that may hold promise in treating amyloid diseases associated with TTR misfolding.

Cyclin-dependent kinase 5 (Cdk5) is an atypical proline-directed serine/threonine protein kinase well-characterized for its role in the central nervous system rather than in the cell cycle. Indeed, its dysregulation has been strongly implicated in the progression of synaptic dysfunction and neurodegenerative diseases, such as Alzheimer’s disease (AD) and Parkinson’s disease (PD), and also in the development and progression of a variety of cancers. For this reason, Cdk5 is considered as a promising target for drug design, and the discovery of novel small-molecule Cdk5 inhibitors is of great interest in the medicinal chemistry field. In this context, we employed a machine learning-based virtual screening protocol with subsequent molecular docking, molecular dynamics simulations and binding free energy evaluations. Our virtual screening studies resulted in the identification of two novel Cdk5 inhibitors, highlighting an experimental hit rate of 50% and thus validating the reliability of the in silico workflow. Both identified ligands, compounds CPD1 and CPD4, showed a promising enzyme inhibitory activity and CPD1 also demonstrated a remarkable antiproliferative activity in ovarian and colon cancer cells. These ligands represent a valuable starting point for structure-based hit-optimization studies aimed at identifying new potent Cdk5 inhibitors.