Reshaping Protein-Based Nanoparticles: Innovative Artificial Intelligence-Driven Strategies for Structural Design and Applications Publisher



Mm Gomari Mohammad MAHMOUDI ; M Alidadi MEHDI ; N Rostami NEDA ; Sa Bencherif Sidi AHMED
Source: Advanced NanoBiomed Research Published:2025

Abstract

Nanoparticles (NPs) have become a pivotal technology in biomedical research due to their unique physicochemical properties and nanoscale size, allowing for targeted applications. Among NP materials, proteins and their derivatives stand out for their biocompatibility, engineering flexibility, and inherent biological functions, making them especially attractive for NP design. However, the structural and biochemical complexity of proteins has historically presented challenges in NP development. Recent advancements in artificial intelligence (AI) have transformed this field. Neural network models such as AlphaFold, ProteinMPNN, and RoseTTAFold, along with protein language models like evolutionary scale modeling, enable the design of protein-based NPs (PNPs) with diverse symmetries, shapes, and functionalities. These AI-driven approaches address traditional limitations, unlocking new possibilities in nanomedicine. This review explores the transformative role of AI in PNP design, emphasizing its potential to broaden applications, solve challenges, and drive innovative solutions in biotechnology and medical research. © 2025 Elsevier B.V., All rights reserved.