PRosettaC outperforms AlphaFold3 for modeling PROTAC ternary complexes
Open accessPublished version of a preprint
Abstract
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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Cites
Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764 · see citing works
Accurate structure prediction of biomolecular interactions with AlphaFold 3
Abramson, J., Adler, J., Dunger, J., Evans, R., Green, T., Pritzel, A., Ronneberger, O., Willmore, L., Ballard, A. J., Bambrick, J., et al. (2024) · Nature · doi:10.1038/s41586-024-07487-w · Cited by 15,861 · cited 1× · see citing works
“In the current study, we employed two state-of-the-art computational techniques, AlphaFold-3 (AF3) and PRosettaC, to model the arrangement of ternary complexes of PROTACs in silico 9,11,26 .”
Protein complex prediction with AlphaFold-Multimer
Evans, R., O’Neill, M., Pritzel, A., Antropova, N., Senior, A., Green, T., Žídek, A., Bates, R., Blackwell, S., Yim, J., et al. (2021) · doi:10.1101/2021.10.04.463034 · Cited by 3,808 · see citing works
DockQ: A Quality Measure for Protein-Protein Docking Models
Basu, S., & Wallner, B. (2016) · PLOS ONE · doi:10.1371/journal.pone.0161879 · Cited by 460 · see citing works
PRosettaC: Rosetta Based Modeling of PROTAC Mediated Ternary Complexes
Zaidman, D., Prilusky, J., & London, N. (2020) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.0c00589 · Cited by 224 · see citing works
Targeting cancer with small-molecule pan-KRAS degraders
Popow, J., Farnaby, W., Gollner, A., Kofink, C., Fischer, G., Wurm, M., Zollman, D., Wijaya, A., Mischerikow, N., Hasenoehrl, C., et al. (2024) · Science · doi:10.1126/science.adm8684 · Cited by 198 · see citing works
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- Authors
- Schulz, J. M., Schürer, S. I., Reynolds, R. C., & Schürer, S. C.
- Affiliations
- University of Miami (US)
- University of Alabama at Birmingham (US)
- Corresponding author
- Schürer, Sarah I.
- Schürer, Stephan C.
- Venue
- Scientific Reports
- Published
- 2025-10-28
- Volume
- 15
- Issue
- 1
- Pages
- 37620-37620
- ISSN
- 2045-2322 (ISSN-L)
- PMC
- PMC12568945
- OpenAlex
- W4415620002
- Cited by
- 16
- References
- 6
- Citations by year
- 2026: 15 · 2025: 1
- FWCI
- 4.81
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Scientific Reports (publishedVersion, cc-by-nc-nd)
- Research Square (acceptedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Congressionally Directed Medical Research Programs (GRANT1420842)
- Florida Department of Health (23B16)
- National Institutes of Health (U01LM012630)
- National Cancer Institute,United States (P30CA240139)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Degradation and Inhibitors
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Keywords
- PROTACs, AlphaFold3, targeted protein degradation, protein-protein interface prediction, protein flexibility, Elongin B/C, DDB1
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