Ternary Complex Geometry and Lysine Positioning Guide the Generation of PROTAC-Induced Degradable Complexes.

Area of Science:

• Biochemistry
• Computational Biology
• Drug Discovery

Background:

• PROteolysis TArgeting Chimaeras (PROTACs) enable targeted protein degradation, revolutionizing drug discovery for previously undruggable targets.
• Rational PROTAC design is limited by challenges in evaluating ternary complex geometry, ubiquitination feasibility, and linker influence on degradation.

Purpose of the Study:

• To develop an integrative computational framework for systematic evaluation of PROTAC ternary complex geometry and degradation potential.
• To provide a mechanistically grounded and generalizable strategy for rational PROTAC development.

Main Methods:

• Integration of ternary complex generation, RMSD-based clustering, CRL2^VHL complex modeling, lysine proximity analysis, and structure-guided dynamics.
• Application of the framework to PTP1B, a phosphatase implicated in oncogenic signaling.
• Utilizing molecular dynamics, PCA, TICA, and Markov state modeling to analyze degradation-competent conformations.

Main Results:

• Over 6900 ternary complex poses were generated and filtered using automated Python scripts for pose clustering and lysine-to-E2 distance evaluation.
• Molecular dynamics simulations identified degradation-competent conformations and dynamic transitions.
• Arg69-guided docking enriched degradation-competent geometries, outperforming AlphaFold-Multimer in generating lysine-accessible poses.

Conclusions:

• The developed computational framework provides a systematic and mechanistically grounded approach to rational PROTAC design.
• This strategy facilitates the optimization of linker architecture and ternary complex geometry for enhanced protein degradation.
• The framework offers a generalizable solution for advancing PROTAC development across diverse therapeutic targets.