Chemical modulation of proteins enables a mechanistic understanding of biology and represents the foundation of most therapeutics. However, despite decades of research, 80% of the human proteome lacks functional ligands. Chemical proteomics has advanced fragment-based ligand discovery toward cellular systems, but throughput limitations have stymied the scalable identification of fragment-protein interactions. We report proteome-wide maps of protein-binding propensity for 407 structurally diverse small-molecule fragments. We verified that identified interactions can be advanced to active chemical probes of E3 ubiquitin ligases, transporters, and kinases. Integrating machine learning binary classifiers further enabled interpretable predictions of fragment behavior in cells. The resulting resource of fragment-protein interactions and predictive models will help to elucidate principles of molecular recognition and expedite ligand discovery efforts for hitherto undrugged proteins.

Targeted protein degradation (TPD) relies on small molecules to recruit proteins to E3 ligases to induce their ubiquitylation and degradation by the proteasome. Only a few of the approximately 600 human E3 ligases are currently amenable to this strategy. This limits the actionable target space and clinical opportunities and thus establishes the necessity to expand to additional ligases. Here we identify and characterize SP3N, a specific degrader of the prolyl isomerase FKBP12. SP3N features a minimal design, where a known FKBP12 ligand is appended with a flexible alkylamine tail that conveys degradation properties. We found that SP3N is a precursor and that the alkylamine is metabolized to an active aldehyde species that recruits the SCF^FBXO22 ligase for FKBP12 degradation. Target engagement occurs via covalent adduction of Cys326 in the FBXO22 C-terminal domain, which is critical for ternary complex formation, ubiquitylation and degradation. This mechanism is conserved for two recently reported alkylamine-based degraders of NSD2 and XIAP, thus establishing alkylamine tethering and covalent hijacking of FBXO22 as a generalizable TPD strategy.

Despite being considered druggable and attractive therapeutic targets, most of the solute carrier (SLC) membrane transporters remain pharmacologically underexploited. One of the reasons for this is a lack of reliable chemical screening assays, made difficult by functional redundancies among SLCs. In this study we leveraged synthetic lethality between the lactate transporters SLC16A1 and SLC16A3 in a screening strategy that we call paralog-dependent isogenic cell assay (PARADISO). The system involves five isogenic cell lines, each dependent on various paralog genes for survival/fitness, arranged in a screening cascade tuned for the identification of SLC16A3 inhibitors. We screened a diversity-oriented library of ∼90,000 compounds and further developed our hits into slCeMM1, a paralog-selective and potent SLC16A3 inhibitor. By implementing chemoproteomics, we showed that slCeMM1 is selective also at the proteome-wide level, thus fulfilling an important criterion for chemical probes. This study represents a framework for the development of specific cell-based drug discovery assays.

Background: Alzheimer’s disease (AD) is a devastating neurodegenerative disorder which affects more than 50 million people across the globe. Unfortunately, the current pharmacotherapy options are very limited and provide only symptomatic relief. Several drug discovery efforts to treat AD have failed in the clinical trials which is a setback in discovering novel anti‐AD therapies. Considering the cost, time and risks involved in bringing a new drug from the bench‐to‐bedside, drug repurposing or discovering novel therapeutic indications for drugs already in the market is an attractive alternative to find novel AD therapies. Targeting the amyloid (Aβ) cascade event in AD is one of the several potential targets to develop novel anti‐AD agents. Our studies looked at the possibility of repurposing marketed selective serotonin reuptake inhibitors (SSRIs) fluvoxamine, fluoxetine, paroxetine, sertraline and escitalopram in AD and investigated their anti‐Aβ aggregation properties.Method: Experiments conducted include fluorescence aggregation kinetics using the dye thioflavin T (ThT), determining Aβ morphology in the presence and absence of SSRIs by transmission electron microscopy (TEM) and computational modeling using the software Discovery Studio Structure‐Based‐Design.Result: These experiments demonstrated that among the SSRIs tested, paroxetine in particular was able to prevent the aggregation of both Aβ40 and Aβ42 peptides. Computational studies were used to understand the interactions of paroxetine with Aβ40 and Aβ42 oligomer and fibrils models.Conclusion: These studies suggest that the antidepressant paroxetine has the potential to target the amyloid cascade in AD. Further studies are required to determine the suitability of repurposing paroxetine to treat AD.