Automated modeling improves ternary complex accuracy in Protac drug discovery, indicating potential for therapeutic advances.
Proteolysis Targeting Chimeras (Protacs) are a new class of drugs which promote degradation of a protein of interest (POI) by hijacking the Ubiquitin-Proteasome system. Structural knowledge of an E3 ligase:Protac:POI ternary complex is required for Protac rational design, and computational modeling of such heteromeric complex structures is nontrivial. To date, few programs have been developed to address this challenge; however, there remains a need for readily accessible tools that can significantly improve ternary complex modeling accuracy. Particularly, programs that can also support the screening phase of Protac discovery, where speed and the ability to test multiple Protacs are essential to advance the field of Protac therapeutics. To bridge these gaps, we present P4ward, a free and fully automated Protac ternary complex modeling pipeline. P4ward achieves a hit rate of 76.5% with an average rank of 7.26 and substantially improves the rank of the near-native pose by 73-98% compared to earlier programs. We believe that P4ward could be a user-friendly, fast, and effective tool for gaining atomistic insights necessary for Protac modeling and optimization.
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Jofily et al. (2025) studied this question.
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