Degradation-based protein profiling in target identification and early-stage drug discovery of bioactive natural products

Abstract

Identifying the molecular targets of bioactive natural products (NPs) remains a critical bottleneck in drug discovery and the modernization of Traditional Chinese Medicine (TCM). Conventional target deconvolution strategies, such as affinity chromatography and activity-based protein profiling (ABPP), are often constrained by strict chemical modification requirements, incomplete proteome coverage, and difficulties in capturing weak or transient interactions. To overcome these limitations, this review highlights degradation-based protein profiling (DBPP), an emerging chemoproteomic strategy that applies proteolysis targeting chimera (PROTAC) technology to target identification. Unlike traditional occupancy-driven methods, DBPP employs an event-driven mechanism, converting complex physical binding events into amplified, detectable protein depletion signals via the ubiquitin-proteasome system. We systematically outline the core framework of DBPP, with particular emphasis on the rationally designed 'PROTAC toolbox', the probe-mixed strategy, and the dual-path orthogonal validation that integrates quantitative degradation proteomics with immunoprecipitation-mass spectrometry (IP-MS). Representative case studies involving NPs such as celastrol and artemisinin illustrate the potential of DBPP to identify elusive targets, including non-catalytic and weak-binding proteins, as well as reducing false positives through orthogonal validation. Finally, we discuss current methodological limitations and explore possible prospects for integrating DBPP with artificial intelligence (AI), single-cell omics, and spatial transcriptomics techniques as an effective way toward deciphering the polypharmacology of complex NPs.

Acknowledgments

This work was supported by the National Natural Science Foundation of China (Grant Nos 82125034, 82330115), the National Key R&D Program of China (Grant Nos 2021YFA1300200, 2021YFA1302100), the Beijing Outstanding Young Scientist Program (Grant No. JWZQ20240101007), and the Beijing Frontier Research Center for Biological Structure.

Ethical statements

Not applicable.

Author contributions

The authors confirm their contributions to the work as follows: study conception: Rao Y; draft manuscript preparation: Rao Y, Ni Z, Shi Y. All authors reviewed the results and approved the final version of the manuscript.

Data availability

Data sharing is not applicable to this review as no datasets were generated or analyzed.

Conflict of interest

The authors declare that they have no conflict of interest.

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