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Research Article

A close-up shot of protein-protein docking, from experiment to theory and reverse with the PROTAC performers

, , ORCID Icon, &
Received 11 Aug 2023, Accepted 14 Jan 2024, Published online: 29 Jan 2024
 

Abstract

PROTACs (Proteolysis Targeting Chimeras), heterobifunctional molecules, exhibit selectivity in degrading target proteins through E3 ubiquitin ligases. Designing effective PROTACs requires a deep understanding of the intricate binding interactions in the ternary complex (POI/PROTAC/E3 ligase), crucial for efficient target protein degradation. To address this challenge, we introduce a novel computational virtual screening method that considers essential amino acid interactions between the protein of interest and the chosen E3 ligase. This approach enhances accuracy and reliability, facilitating the strategic development of potent PROTACs. Utilizing a crystallized model of the VHL:PROTAC:SMARCA2BD ternary complex (PDB: 7Z6L), we assessed the effectiveness of our method. Our study reveals that increasing the number of essential restraints between the two proteins reduces the generated docking poses, leading to closer alignment with the experimental ternary complex. Specifically, utilizing three restraints showed the closest resemblance to the published complex, highlighting crucial interactions such as an H-bond between A:Gln 89 and B:Asn 67, along with two hydrophobic interactions: A:Gly 22 with B:Arg 69 and A:Glu 37 with B:Pro 99. This resulted in a significant decrease in the mean RMSD value from 31.8 and 31.0 Å to 24.4 Å, respectively. This underscores the importance of incorporating multiple essential restraints to enhance docking accuracy. Building on this progress, we introduce a systematic approach to design potential PROTACs between the Estrogen receptor and the E3 ligase, utilizing bridging intermediates with 4, 6, or 7 carbon atoms. By providing a more accurate and efficient means of identifying optimal PROTAC candidates, this approach has the potential to accelerate the development of targeted therapies and reduce the time and costs associated with drug discovery.

Communicated by Ramaswamy H. Sarma

Acknowledgment

The authors would like to thank the support of the management board as well as the HPC (high performance computer) team of Ton Duc Thang University.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Authors contribution

Thien Y VU: Software, Methodology, Writing—original draft

Khanh Linh Chung: Original idea

Huong Thi Thu Phung, Khanh Linh Chung: Writing—review & editing

Khanh Quynh Thi Nguyen, Hieu Hien Nguyen: Calculations—Figures, Tables presentations, SI supporting information.

Data available statement

Data is available upon request.

Additional information

Funding

The project is not funded from any source.

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