Rationalizing PROTAC-mediated ternary complex formation using Rosetta

Abstract PROTACs are molecules that combine a target-binding warhead with an E3 ligase-recruiting moiety; by drawing the target protein into a ternary complex with the E3 ligase, PROTACs induce target protein degradation. While PROTACs hold exciting potential as chemical probes and as therapeutic agents, development of a PROTAC typically requires synthesis of numerous analogs to thoroughly explore variations on the chemical linker; without extensive trial and error, it is unclear how to link the two protein-recruiting moieties to promote formation of a productive ternary complex. Here, we describe a structure-based computational method for evaluating suitability of a given linker for ternary complex formation. Our method uses Rosetta to dock the protein components, then builds the PROTAC from its component fragments into each binding mode; complete models of the ternary complex are then refined. We apply this approach to retrospectively evaluate multiple PROTACs from the literature, spanning diverse target proteins. We find that modeling ternary complex formation is sufficient to explain both activity and selectivity reported for these PROTACs, implying that other cellular factors are not key determinants of activity in these cases. We further find that interpreting PROTAC activity is best approached using an ensemble of structures of the ternary complex rather than a single static conformation, and that members of a structurally-conserved protein family can be recruited by the same PROTAC through vastly different binding modes. To encourage adoption of these methods and promote further analyses, we disseminate both the computational methods and the models of ternary complexes. Significance Statement Recent years have brought a flood of interest in developing compounds that selectively degrade protein targets in cells, as exemplified by PROTACs. Fully realizing the promise of PROTACs to transform chemical biology by delivering degraders of diverse and undruggable protein targets has been impeded, however, by the fact that designing a suitable chemical linker between the functional moieties requires extensive trial and error. Here, we describe a structure-based computational method to predict PROTAC activity. We envision that this approach will allow design and optimization of PROTACs for efficient target degradation, selection of E3 ligases best suited for pairing with a given target protein, and understanding the basis by which PROTACs can exhibit different target selectivity than their component warheads.