Work

Artificial-intelligence-driven rational design of nanoparticle-mediated targeted protein degradation

Year: 2026

Type: article

Abstract: Targeted protein degradation (TPD) has emerged as a powerful therapeutic strategy to eliminate disease-associated proteins that are inaccessible to conventional inhibition. Among TPD approaches, nanoparticle-mediated degradation, particularly through nanoparticle-mediated targeting chimerics (NPTACs) that induce receptor-mediated endocytosis and lysosomal degradation, offers unique advantages in modular design, target selectivity, and delivery potential. However, the complexity of these systems, determined by factors including particle size, surface charge, PEGylation, and ligand properties, poses significant challenges in predicting which formulations will effectively mediate intracellular trafficking and protein degradation. This perspective proposes artificial intelligence (AI) as a transformative tool to enable rational, predictive, and personalized NPTAC design. By integrating curated datasets, machine learning, generative modeling, and mechanistic insights, AI can navigate vast design spaces and accelerate translation. We outline key opportunities, challenges, and a future vision for intelligent, patient-tailored degrader nanomedicines.

Source: Cell Biomaterials

DOI: 10.1016/j.celbio.2026.100443

Authors: Runhan Liu, Yang Liu, Xue Xia, Wei Deng, David Gallego Ortega, Bingyang Shi

Institution: University of Technology Sydney

Language: English

Topic: Protein Degradation and Inhibitors

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $9,350