De novo Design of Macrocyclic Molecular Glues

Abstract

The engineering of induced proximity has transformed drug discovery, yet the development of molecular glues remains largely serendipitous and restricted to the retrospective optimisation of accidental discoveries. Here, we present EvoBind-multimer, a deep learning framework for the de novo design of molecular glues directly from protein sequences. Unlike structure-based docking, our method generates small macrocyclic peptides that bridge user-defined protein pairs without requiring prior interface knowledge or existing ligands. We applied this framework to recruit the E3 ligase VHL to two challenging oncoproteins: KRAS and BRD4. Live-cell NanoBRET demonstrated robust design-induced proximity for both pairs. Mechanistic validation demonstrated that the generated macrocycles form functional VHL-target ternary complexes capable of driving Cullin-RING ligase-dependent proteasomal degradation and downstream signalling shutdown. Finally, evaluation in patient-derived xenograft neuroblastoma tumoroids revealed that ternary complex processing is deeply context-dependent: identical macrocycles acted as potent degraders in one patient model, yet functioned as stabilising "LOCKTACs" in another, driving VHL-dependent target sequestration without turnover. By enabling the de novo design of induced proximity from sequence alone, EvoBind-multimer provides a route towards designing new protein functions.