Shotgun Approach for PROTAC Ternary Complex Modeling and Evaluation.

Area of Science:

• Biochemistry
• Structural Biology
• Drug Discovery

Background:

• Proteolysis targeting chimeras (PROTACs) are bifunctional molecules that induce targeted protein degradation by forming ternary complexes with a target protein and an E3 ubiquitin ligase.
• Structure-based linker design for PROTACs is promising but hindered by the flexibility and dynamic nature of these ternary complexes, making it difficult to obtain accurate structural information.

Purpose of the Study:

• To develop and validate a novel computational framework for modeling and evaluating protein of interest-degrader-E3 ligase ternary complexes.
• To address the limitations of static crystal structures and improve the accuracy of computational models for guiding PROTAC degrader design.

Main Methods:

• Utilized conformation distributions from multiple parallel molecular dynamics (MD) trajectories as a reference for ternary complex modeling.
• Developed a new modeling protocol and scoring function to generate and evaluate a ternary complex ensemble.
• Tested the framework on five cases involving protein of interest-degrader-E3 systems.

Main Results:

• The proposed protocol successfully generated ternary complex ensembles that cover or closely approximate high-density regions observed in MD trajectories.
• Demonstrated the framework's effectiveness in capturing the conformational diversity inherent in these dynamic systems.
• The approach is particularly suitable for systems with multiple stable conformations and protein-protein interactions (PPIs).

Conclusions:

• The developed framework provides a more accurate and reliable method for modeling ternary complexes compared to traditional approaches relying solely on crystal structures.
• This advancement offers a valuable tool for structure-based linker design in PROTACs, potentially accelerating the development of novel protein degradation therapies.
• The framework's ability to handle conformational flexibility enhances its applicability in drug discovery efforts targeting protein degradation.