Artificial intelligence driven protein design and sustainable nanomedicine for advanced theranostics

The integration of artificial intelligence, protein engineering, and sustainable nanomedicine is driving a paradigm shift in theranostics by enabling highly precise disease diagnosis and targeted therapy. AI-driven methodologies, including machine learning and deep learning, facilitate the rapid analysis of complex biological and chemical datasets, accelerating protein structure prediction, molecular docking, and structure-activity relationship modeling. These capabilities support the rational design of proteins and peptides with enhanced specificity, therapeutic efficacy, and safety, while enabling personalized treatment strategies tailored to individual molecular profiles. In parallel, sustainable nanomedicine focuses on the development of biodegradable, biocompatible, and environmentally benign nanomaterials to improve drug bioavailability, stability, and controlled release. AI-assisted optimization further refines nanocarrier design by balancing therapeutic performance with safety and environmental impact. Advanced intelligent nanocarriers capable of real-time monitoring, adaptive drug release, and degradation into non-toxic by-products represent a significant advancement over conventional static systems. The theranostic paradigm has become central to precision medicine, particularly in oncology, especially where AI-designed nanoplatforms enable targeted delivery of imaging agents and therapeutics to tumors, while allowing continuous treatment monitoring and minimizing off-target effects. Emerging applications in neurological, infectious, and cardiovascular diseases further highlight the broad clinical potential of this approach. Accordingly, this review summarizes AI-driven protein design strategies, sustainable nanocarrier engineering, and their convergence in next-generation theranostic systems, critically discussing mechanistic insights, translational challenges, and design principles required for developing safe, scalable, and clinically adaptable intelligent nanomedicines.

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Publication Details

Journal
Bioactive Materials
Published
2026-01-30
DOI
https://doi.org/10.1016/j.bioactmat.2026.01.036
Citations
1
Primary Topic
Nanoparticle-Based Drug Delivery
Type
article
Field-Weighted Citation Impact
22.64
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article

Artificial intelligence driven protein design and sustainable nanomedicine for advanced theranostics

Ehsan Nazarzadeh Zare‬, Donya Esmaeilpour, Atefeh Zarepour, Hassan Karimi-Maleh et al.
1 citations
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22.64
article

Artificial intelligence driven protein design and sustainable nanomedicine for advanced theranostics

Ehsan Nazarzadeh Zare‬, Donya Esmaeilpour, Atefeh Zarepour, Hassan Karimi-Maleh, Ali Zarrabi, Arezoo Khosravi, Jianliang Shen, Michael R. Hamblin, Jianlin Cheng, Jian Liu, Mika Sillanpaa
article en
1 citations

Abstract

The integration of artificial intelligence, protein engineering, and sustainable nanomedicine is driving a paradigm shift in theranostics by enabling highly precise disease diagnosis and targeted therapy. AI-driven methodologies, including machine learning and deep learning, facilitate the rapid analysis of complex biological and chemical datasets, accelerating protein structure prediction, molecular docking, and structure-activity relationship modeling. These capabilities support the rational design of proteins and peptides with enhanced specificity, therapeutic efficacy, and safety, while enabling personalized treatment strategies tailored to individual molecular profiles. In parallel, sustainable nanomedicine focuses on the development of biodegradable, biocompatible, and environmentally benign nanomaterials to improve drug bioavailability, stability, and controlled release. AI-assisted optimization further refines nanocarrier design by balancing therapeutic performance with safety and environmental impact. Advanced intelligent nanocarriers capable of real-time monitoring, adaptive drug release, and degradation into non-toxic by-products represent a significant advancement over conventional static systems. The theranostic paradigm has become central to precision medicine, particularly in oncology, especially where AI-designed nanoplatforms enable targeted delivery of imaging agents and therapeutics to tumors, while allowing continuous treatment monitoring and minimizing off-target effects. Emerging applications in neurological, infectious, and cardiovascular diseases further highlight the broad clinical potential of this approach. Accordingly, this review summarizes AI-driven protein design strategies, sustainable nanocarrier engineering, and their convergence in next-generation theranostic systems, critically discussing mechanistic insights, translational challenges, and design principles required for developing safe, scalable, and clinically adaptable intelligent nanomedicines.

Bioactive MaterialsVol. 60
Shiraz University (IR), Duy Tan University (VN), Damghan University (IR), University of Johannesburg (ZA), Wenzhou Medical University (CN), Affiliated Eye Hospital of Wenzhou Medical College (CN), Quzhou City People's Hospital (CN), Istinye University (TR), Kocaeli Üniversitesi (TR), Chitkara University (IN), University of Missouri (US), Okan University (TR), Yuan Ze University (TW)
Openalex Percentile: Top 1%
Nanoparticle-Based Drug Delivery
22.64
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