ATTECs and several other emerging degrader technologies hijacking the lysosomal pathways greatly expand the spectrum of degradable targets and provide new opportunities for targeted drug discovery.

Aberrant activation of stimulator of interferon genes (STING) is tightly associated with multiple types of disease, including cancer, infection, and autoimmune diseases. However, the development of STING modulators for the therapy of STING‐related diseases is still an unmet clinical need. We employed a high‐throughput screening approach based on the interaction of small‐molecule chemical compounds with recombinant STING protein to identify functional STING modulators. Intriguingly, the cyclin‐dependent protein kinase (CDK) inhibitor Palbociclib was found to directly bind STING and inhibit its activation in both mouse and human cells. Mechanistically, Palbociclib targets Y167 of STING to block its dimerization, its binding with cyclic dinucleotides, and its trafficking. Importantly, Palbociclib alleviates autoimmune disease features induced by dextran sulphate sodium or genetic ablation of three prime repair exonuclease 1 (Trex1) in mice in a STING‐dependent manner. Our work identifies Palbociclib as a novel pharmacological inhibitor of STING that abrogates its homodimerization and provides a basis for the fast repurposing of this Food and Drug Administration‐approved drug for the therapy of autoinflammatory diseases.

The detection of small molecules has increasingly attracted the attention of researchers because of its important physiological function. In this manuscript, we propose a novel optical sensor which uses an optofluidic microbubble resonator (OFMBR) for the highly sensitive detection of small molecules. This paper demonstrates the binding of the small molecule biotin to surface-immobilized streptavidin with a detection limit reduced to 0.41 pM. Furthermore, binding specificity of four additional small molecules to surface-immobilized streptavidin is shown. A label-free OFMBR-based optical sensor has great potential in small molecule detection and drug screening because of its high sensitivity, low detection limit, and minimal sample consumption.

Significance Classical drug discovery identifies inhibitors that block the activities of pathogenic proteins. This typically relies on a measurable biochemical readout and accessible binding sites whose occupancy influences the activity of the target protein. These requirements make many pathogenic proteins “undruggable.” Here, we report a strategy to target these undruggable proteins: screening for compounds that directly bind to the undruggable target and rescue disease-relevant phenotypes. These compounds may suppress the target’s pathogenic functions via direct binding to it. We applied this strategy to the mutant HTT protein, which is an undruggable protein that causes Huntington’s disease (HD). We revealed desonide, an FDAapproved drug, as a possible lead compound for HD drug discovery.

Cervical cancer has high morbidity and mortality rates, affecting hundreds of thousands of women worldwide and requiring more accurate screening for early intervention and follow-up treatment. Cytology is the current dominant clinical screening approach, and though it has been used for decades, it has unsatisfactory sensitivity and specificity. In this work, fluorescence lifetime imaging microscopy (FLIM) was used for the imaging of exfoliated cervical cells in which an endogenous coenzyme involved in metabolism, namely, reduced nicotinamide adenine dinucleotide (phosphate) [NAD(P)H], was detected to evaluate the metabolic status of cells. FLIM images from 71 participants were analyzed by the unsupervised machine learning method to build a prediction model for cervical cancer risk. The FLIM method combined with unsupervised machine learning (FLIM-ML) had a sensitivity and specificity of 90.9% and 100%, respectively, significantly higher than those of the cytology approach. One cancer recurrence case was predicted as high-risk several months earlier using this method as compared to using current clinical methods, implying that FLIM-ML may be very helpful for follow-up cancer care. This study illustrates the clinical applicability of FLIM-ML as a detection method for cervical cancer screening and a convenient tool for follow-up cancer care.