Induced Proximity Beyond PROTACs: Computational Discovery of Molecular Glues, Degrader Mechanisms, Ternary Complexes, and Emerging Therapeutic Modalities

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Induced proximity has emerged as a transformative strategy in drug discovery, extending far beyond the classical PROTAC paradigm. This review explores computational approaches for the discovery of molecular glues, elucidation of degrader mechanisms, prediction and modeling of ternary complexes, and the development of emerging therapeutic modalities. Molecular glues stabilize protein–protein interactions without the need for a linker, offering new opportunities to degrade previously undruggable targets. Computational methods, including molecular dynamics simulations, docking, machine learning, and artificial intelligence-based platforms, have accelerated the identification of novel glues and the rational design of degraders. Understanding the structural and dynamic features of ternary complexes remains a critical challenge, as cooperativity and interface geometry dictate degradation efficiency and selectivity. Recent advances in cryo-electron microscopy, AlphaFold-based modeling, and free energy calculations have improved the prediction of ternary complex formation. Furthermore, emerging modalities such as lysosome-targeting chimeras, autophagy-based degraders, and antibody-based proximity inducers are expanding the therapeutic landscape. This review highlights integrative computational workflows that bridge chemistry, structural biology, and pharmacology, enabling the discovery of next-generation proximity-inducing agents with improved potency, selectivity, and drug-like properties. The convergence of these technologies promises to reshape the future of targeted protein degradation and induced proximity therapeutics.