AI-Guided Targeted Protein Degradation: PROTACs, Molecular Glues & Degrader Design

To provide participants with practical knowledge of targeted protein degradation, PROTAC and molecular-glue design, ternary-complex modelling, molecular-property analysis and AI-assisted degrader prioritisation for modern drug-discovery and therapeutic-research applications.

• Understand the biological principles of targeted protein degradation and event-driven pharmacology.
• Explore the ubiquitin–proteasome system and the role of E3 ligases in protein degradation.
• Understand PROTAC architecture, including target ligands, linkers and E3-ligase recruiters.
• Identify disease-relevant protein targets and suitable ligands for degrader development.
• Analyse target–PROTAC–E3 ternary-complex structures.
• Evaluate linker and molecular properties influencing degrader performance.
• Understand molecular-glue degraders and induced-proximity mechanisms.
• Generate molecular descriptors and fingerprints for degrader molecules.
• Build machine-learning models for degrader-activity prediction.
• Apply explainable AI and multi-parameter ranking for candidate prioritisation.

• Graduate and Postgraduate Students from Biotechnology, Bioinformatics, Biochemistry, Molecular Biology, Pharmacy, Pharmaceutical Sciences, Chemistry, Biomedical Sciences, Life Sciences, and related disciplines
• Ph.D. Scholars and Researchers working in drug discovery, cancer biology, protein science, medicinal chemistry, molecular pharmacology, structural biology, chemical biology, or computational biology
• Academicians and Faculty Members interested in targeted protein degradation, PROTACs, molecular glues, AI-enabled drug discovery, and computational therapeutic research
• Industry Professionals from pharmaceutical, biotechnology, CRO, medicinal chemistry, computational chemistry, bioinformatics, and AI/ML-driven drug-discovery teams

• Explain how targeted protein degradation differs from conventional drug inhibition.
• Identify suitable disease targets and E3 ligases for degrader development.
• Design the basic architecture of a PROTAC molecule.
• Interpret target–PROTAC–E3 ternary complexes.
• Evaluate linker and molecular properties affecting degrader behaviour.
• Understand the mechanism of molecular-glue degraders.
• Generate molecular descriptors and fingerprints for degrader molecules.
• Build and evaluate an ML model for degrader-activity prediction.
• Use explainable AI to identify important molecular features.
• Prioritise degrader candidates using structural, molecular and predicted activity information.
• Prepare a computationally supported degrader-design strategy for further research or experimental validation.