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Updated: Jan 13, 2026

Author Spotlight: Evaluating Biophysical Assays for Characterizing PROTACS Ternary Complexes
Published on: January 12, 2024
PRosettaC outperforms AlphaFold3 for modeling PROTAC ternary complexes
Joseph M Schulz1, Sarah I Schürer2, Robert C Reynolds3
1Department of Molecular and Cellular Pharmacology, University of Miami, Miami, FL, USA.
None:
Targeted protein degradation via PROTACs offers a promising therapeutic strategy, yet accurate modeling of ternary complexes remains a critical challenge in degrader design. In this study, we systematically benchmark two leading structure prediction tools, AlphaFold-3 and PRosettaC, against a curated dataset of 36 crystallographically resolved ternary complexes. Using DockQ as a quantitative interface scoring metric, we assess the structural fidelity of predicted complexes under both scaffold-inclusive and stripped configurations. Our results demonstrate that AlphaFold-3's performance is often inflated by accessory proteins such as Elongin B/C or DDB1, which contribute to overall interface area but not degrader-specific binding. PRosettaC, on the other hand, leverages chemically defined anchor points to yield more geometrically accurate models in select systems, though it frequently fails when linker sampling is insufficient or misaligned. To overcome the limitations of static benchmarking, we introduce a dynamic evaluation strategy using molecular dynamics simulations of the crystal structures. This frame-resolved analysis reveals that several PRosettaC models, while poorly aligned to the static crystal conformation, transiently achieve high DockQ alignment with specific frames along the MD trajectory. These findings underscore the importance of incorporating protein flexibility into benchmarking workflows and suggest that transient conformational compatibility may be overlooked in conventional evaluations. By combining constraint-based modeling with dynamic frame matching, this study provides a more nuanced framework for assessing ternary complex predictions and informs the selection of in silico tools for rational PROTAC development.
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