Machine learning (ML) accelerates PROTAC design by optimizing linkers and protein–ligase interactions, enabling selective protein degradation for therapeutic applications, particularly targeting previously undruggable proteins.
Targeting chimeras (TACs), such as PROTACs, LYTACs, AUTACs, and ATTECs, has emerged as a promising strategy for selectively degrading proteins. The linker of the TACs plays a critical role in determining the spatial arrangement, stabilizing the ternary complex, and determining degradation efficiency.
This review proposes the concept of proteolysis-targeting drug delivery system (ProDDS), surveys the recent research in various ProDDSs, summarizes their design principles, and provides an outlook on future opportunities.
This schematic illustrates the multidimensional optimization strategies for BRD4-targeting PROTACs, encompassing the rational design of the ternary complex, diverse controllable activation systems, and targeted delivery approaches.
High-throughput chemistry (HTC) and direct-to-biology (D2B) platforms allow for plate-based compound synthesis and biological evaluation of crude mixtures in cellular assays.