Structure-Guided In Silico Engineering of PROTACs for Targeted S100A16 Proteasomal Degradation via E3 Ligase Recruitment

Overview

Introduction Glioblastoma is a highly malignant brain tumor characterized by aggressive growth, frequent recurrence, and limited treatment options. Glioblastoma cells produce the S100A16 protein, which promotes tumor cell proliferation, migration, and invasion. Proteolysis Targeting Chimeras (PROTACs) are heterobifunctional small-molecule drugs designed to induce selective protein degradation. They function by simultaneously binding a target protein, such as S100A16, and an E3 ubiquitin ligase, thereby promoting ubiquitination and subsequent degradation through the ubiquitin–proteasome system. Aim This study aims to degrade Glioblastoma-associated proteins by identifying optimal binding interactions between S100A16 and an E3 ligase using the novel PROTAC molecule. Hypothesis If a PROTAC or its mutant variants bind effectively to predicted sites on S100A16 and the E3 ligase, then stable and favorable protein-ligand interactions will occur, enhancing targeted degradation. Method AlphaFold, a multifunctional Artificial Intelligence system that predicts protein three-dimensional structures from amino acid sequences, was used to model the S100A16 structure. Ten PROTAC mutants were generated using the Chemically Reasonable Mutations (CrEM) framework. Molecular docking simulations of S100A16–E3 ligase complexes with PROTAC mutants were conducted using the HDOCK server to evaluate binding interactions. Results Statistical analysis from molecular docking simulations indicated that PROTAC mutant P3 exhibited the strongest binding affinity, with a binding energy of −143.45 kcal/mol among the other PROTAC mutants compared. Conclusion These findings indicate with the aid of AI based tools demonstrate that binding energy is an effective metric for identifying promising PROTAC candidates and it will contribute to the development of targeted Glioblastoma therapies.

Competition history

• CSEF 2026 Biochemistry/ Molecular Biology (Junior Division) · Entry J-04-08

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