ArticlePharmaceutics2023
A Mechanistic Pharmacodynamic Modeling Framework for the Assessment and Optimization of Proteolysis Targeting Chimeras (PROTACs).
Article in Pharmaceutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Harnessing the ubiquitin-proteasome system: advances and challenges of PROTACs in breast cancer.Molecular biology reports · 2026Review
- Generalizable Strategies for the Synthesis of Cereblon-Recruiting PROTAC Prodrugs.Angewandte Chemie (International ed. in English) · 2026Article
- Delivering Degradation: Nanomedicine and Programmable Proximity Platforms for Targeted Protein Degradation.Pharmaceutics · 2026Review
- From undruggable to degradable: A deep learning-enabled framework for precision orthopaedic protein degradation.Journal of orthopaedic translation · 2026Review
- Knowledge mapping and bibliometric insights of scientific research on targeted protein degradation in oncology.Journal of cancer research and clinical oncology · 2026Review
- Reimagining GSK-3β Therapeutics in Alzheimer's Disease: From Inhibition to Activity Normalization and Targeted Degradation.Journal of molecular neuroscience : MN · 2026Review
- Proteolysis-targeting Chimera efficacy prediction using a deep-learning-QSP model.Journal of cheminformatics · 2026Article
- Exploiting Pharmacokinetic/Pharmacodynamic Methods for Optimizing and Accelerating Drug Development of Innovative Anti-Infectives.ChemMedChem · 2026Review
- Review
- Targeted degradation of CDK9 potently disrupts the MYC-regulated network.Cell chemical biology · 2025Article
- Review
- Methylarginine targeting chimeras for lysosomal degradation of intracellular proteins.Nature chemical biology · 2024Article
- Realizing the promise of Project Optimus: Challenges and emerging opportunities for dose optimization in oncology drug development.CPT: pharmacometrics & systems pharmacology · 2024Review
- ATNC: Versatile Nanobody Chimeras for Autophagic Degradation of Intracellular Unligandable and Undruggable Proteins.Journal of the American Chemical Society · 2023Article
- Targeted Protein Degradation: Advances, Challenges, and Prospects for Computational Methods.Journal of chemical information and modeling · 2023Review
- Proximity-Based Modalities for Biology and Medicine.ACS central science · 2023Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The field of targeted protein degradation is growing exponentially. Yet, there is an unmet need for pharmacokinetic/pharmacodynamic models that provide mechanistic insights, while also being practically useful in a drug discovery setting. Therefore, we have developed a comprehensive modeling framework which can be applied to experimental data from routine projects to: (1) assess PROTACs based on accurate degradation metrics, (2) guide compound optimization of the most critical parameters, and (3) link degradation to downstream pharmacodynamic effects. The presented framework contains a number of first-time features: (1) a mechanistic model to fit the hook effect in the PROTAC concentration-degradation profile, (2) quantification of the role of target occupancy in the PROTAC mechanism of action and (3) deconvolution of the effects of target degradation and target inhibition by PROTACs on the overall pharmacodynamic response. To illustrate applicability and to build confidence, we have employed these three models to analyze exemplary data on various compounds from different projects and targets. The presented framework allows researchers to tailor their experimental work and to arrive at a better understanding of their results, ultimately leading to more successful PROTAC discovery. While the focus here lies on in vitro pharmacology experiments, key implications for in vivo studies are also discussed.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.