[Advances and future directions in discovery of active substances and target identification in traditional Chinese medicine: toward precision, efficiency, and intelligence].

The study of active substances in traditional Chinese medicine(TCM) is the foundation of TCM pharmacology, TCM quality control, and new drug development, and it is also one of the most popular directions in TCM modernization research in recent years. Due to their diverse chemical compositions and complex component-effect relationships, Chinese medicines often require the comprehensive use of multidisciplinary technologies such as chemistry, biology, and information science to reveal their active substances and targets. In this paper, we review the innovative breakthroughs made in the past 30 years in the discovery strategies and technological means for the research of active substances in traditional Chinese medicine from the perspective of technological changes, and focus on the new direction of the research of active substances in traditional Chinese medicine under the paradigm shift of scientific research brought about by artificial intelligence, with the aim of promoting research in related fields to move in the direction of more accurate, efficient, and intelligent, and providing innovative ideas for the research of active substances in traditional Chinese medicine under the new situation.

Detecting ALDH2 activity in live cells conditional metabolic labeling.

Detecting enzyme activity that catalyzes subtle functional group transformations in live cells remains a major challenge. We introduce a conditional metabolic labeling strategy for enzymatic activity detection (cMLEAD), which harnesses cellular metabolic pathways to deliver indirect yet reliable activity readouts. Unlike traditional metabolic labeling approaches relying on nonspecific incorporation of tagged biomolecules, cMLEAD employs a tagged precursor whose metabolic incorporation is strictly dependent on specific enzymatic activity, effectively transforming a metabolic labeling event into an enzyme-activity measurement.

Deconvoluting nitric oxide-protein interactions with spatially resolved multiplex imaging.

Simultaneous imaging of nitric oxide (NO) and its proximal proteins should facilitate the deconvolution of NO-protein interactions. While immunostaining is a primary assay to localize proteins in non-genetically manipulated samples, NO imaging probes with immunostaining-compatible signals remain unexplored. Herein, probe NOP-1 was developed with an NO-triggered proximal protein labeling capacity and fluorogenic signals.