PreprintCited by 16Protein Degradation and InhibitorsProtein Structure and DynamicsComputational Drug Discovery Methods

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Benchmarking the Builders: A Comparative Analysis of PRosettaC and AlphaFold3 for Predicting PROTAC Ternary Complexes

Open access

Preprint — published as 10.1038/s41598-025-21502-8 · Paper page

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, AlphaFold3 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 AlphaFold3'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.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.21203/rs.3.rs-6866610/v1

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 18

  1. Zhao, L., Zhao, J., Zhong, K., Tong, A. & Jia, D. Targeted protein degradation: mechanisms, strategies and application. Signal. Transduct. Target. Ther. 7, 113 (2022). · DOI
  2. Callis, J. The ubiquitination machinery of the ubiquitin system. Arabidopsis Book. 12, e0174–e0174 (2014). · DOI
  3. Sobhia, M. E., Kumar, H. & Kumari, S. Bifunctional robots inducing targeted protein degradation. Eur. J. Med. Chem. 255, 115384 (2023). · DOI
  4. Khurshid, R. et al. Targeted degrader technologies as prospective SARS-CoV-2 therapies. Drug Discov Today. 29, 103847 (2024). · DOI
  5. Wang, H., Li, C., Liu, X. & Ma, M. Design, synthesis and activity study of a novel PI3K degradation by hijacking VHL E3 ubiquitin ligase. Bioorg. Med. Chem. 61, 116707 (2022). · DOI
  6. Wijaya, A. J., Farnaby, W. & Ciulli, A. Chapter Eleven - Crystallization of VHL-based PROTAC-induced ternary complexes. in Methods in Enzymology (ed Burslem, G. L.) vol. 681 241–263 (Academic, (2023).
  7. Drummond, L., Williams, I. & M. & Silico Modeling of PROTAC-Mediated Ternary Complexes: Validation and Application. J. Chem. Inf. Model. 59, 1634–1644 (2019). · DOI · Paper page
  8. Drummond, L., Henry, M., Li, A., Williams, I. & H. & Improved Accuracy for Modeling PROTAC-Mediated Ternary Complex Formation and Targeted Protein Degradation via New In Silico Methodologies. J. Chem. Inf. Model. 60, 5234–5254 (2020). · DOI · Paper page
  9. Zaidman, D., Prilusky, J. & London, N. P. R. C. Rosetta Based Modeling of PROTAC Mediated Ternary Complexes. J. Chem. Inf. Model. 60, 4894–4903 (2020). · DOI · Paper page
  10. Li, B., Ran, T. & Chen, H. 3D based generative PROTAC linker design with reinforcement learning. Brief. Bioinform. 24, bbad323 (2023). · DOI
  11. Evans, R. et al. Protein complex prediction with AlphaFold-Multimer. bioRxiv 2021.10.04.463034 (2022). 10.1101/2021.10.04.463034 · DOI · Paper page
  12. Abramson, J. et al. Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature 10.1038/s41586-024-07487-w (2024). · DOI · Paper page
  13. Basu, S., Wallner, B. & DockQ A Quality Measure for Protein-Protein Docking Models. PLoS One. 11, e0161879 (2016). · DOI · Paper page
  14. Mirabello, C. & Wallner, B. DockQ v2: improved automatic quality measure for protein multimers, nucleic acids, and small molecules. Bioinformatics 40, btae586 (2024). · DOI
  15. Teng, F. et al. Cryo-EM structure of the KLHL22 E3 ligase bound to an oligomeric metabolic enzyme. Structure 31, 1431–1440e5 (2023). · DOI
  16. Zhu, W., Chen, X., Zhang, J. & Xu, C. Structure of the CUL1-RBX1-SKP1-FBXO4 SCF ubiquitin ligase complex. Biochem. Biophys. Res. Commun. 735, 150811 (2024). · DOI
  17. Wu, K. Y., Hung, T. I. & Chang, C. A. PROTAC-induced Protein Functional Dynamics in Targeted Protein Degradation. bioRxiv 2024.05.05.592590 (2024). 10.1101/2024.05.05.592590 · DOI
  18. Bertoline, L. M. F., Lima, A. N., Krieger, J. E. & Teixeira, S. K. Before and after AlphaFold2: An overview of protein structure prediction. Front. Bioinf. 3, 1120370 (2023). · DOI

Metadata

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
2025-07-02
Volume
15
Issue
1
Pages
37620-37620
ISSN
2045-2322 (ISSN-L)
OpenAlex
W4415620002
Cited by
16
References
1
Citations by year
2026: 15 · 2025: 1
FWCI
4.81
Type
journal article
Language
en
Open access
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
  • Florida Department of Health (23B16)
  • Sylvester Comprehensive Cancer Center, University of Miami Health Systems (P30 CA 240139)
  • National Institutes of Health
  • National Cancer Institute (P30CA240139)
  • U.S. National Library of Medicine (R01LM013391, U01LM012630)
  • Congressionally Directed Medical Research Programs (GRANT1420842)
  • State of Florida
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
  • Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
Keywords
PROTACs, AlphaFold3, targeted protein degradation, protein-protein interface prediction, protein flexibility, Elongin B/C, DDB1

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review