Artificial Intelligence for Natural Products Drug Discovery in Neurodegenerative Therapies: A Review

This review examines the application of Artificial Intelligence (AI) in the discovery and optimisation of neuroprotective natural products (NPs) for neurodegenerative diseases (NDDs), emphasising the transition from general computational drug discovery to AI-specific approaches designed to address the chemical complexity and bioactivity profiles of natural compounds. The discussion encompasses relevant datasets, AI models, illustrative case studies, and emerging protein and biological targets that may serve as potential points of intervention for the prevention and treatment of NDDs. The review is organised to guide the reader from foundational knowledge to applied strategies; it begins by outlining the chemical and biological principles underlying neuroprotective NPs, then presents AI-driven computational frameworks for NP discovery, followed by a detailed examination of recent case studies in NDDs. Subsequent sections address the key challenges, opportunities, and future directions in the field, concluding with an evaluation of prospects for interdisciplinary collaboration across medicinal chemistry, neuroscience, and artificial intelligence.

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Publication Details

Journal
Biomolecules
Published
2026-01-12
DOI
https://doi.org/10.3390/biom16010129
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial Intelligence for Natural Products Drug Discovery in Neurodegenerative Therapies: A Review

Emanuele Nardone, Francesco Fontanella, Caterina Vicidomini, Claudio De Stefano et al.
Biomolecules
Computational Drug Discovery Methods
article

Artificial Intelligence for Natural Products Drug Discovery in Neurodegenerative Therapies: A Review

Emanuele Nardone, Francesco Fontanella, Caterina Vicidomini, Claudio De Stefano, Tiziana D’Alessandro, Giovanni N. Roviello
article en

Abstract

This review examines the application of Artificial Intelligence (AI) in the discovery and optimisation of neuroprotective natural products (NPs) for neurodegenerative diseases (NDDs), emphasising the transition from general computational drug discovery to AI-specific approaches designed to address the chemical complexity and bioactivity profiles of natural compounds. The discussion encompasses relevant datasets, AI models, illustrative case studies, and emerging protein and biological targets that may serve as potential points of intervention for the prevention and treatment of NDDs. The review is organised to guide the reader from foundational knowledge to applied strategies; it begins by outlining the chemical and biological principles underlying neuroprotective NPs, then presents AI-driven computational frameworks for NP discovery, followed by a detailed examination of recent case studies in NDDs. Subsequent sections address the key challenges, opportunities, and future directions in the field, concluding with an evaluation of prospects for interdisciplinary collaboration across medicinal chemistry, neuroscience, and artificial intelligence.

BiomoleculesVol. 16(1)
Università degli studi di Cassino e del Lazio Meridionale (IT), Institute of Biostructure and Bioimaging (IT)
Openalex Percentile: Top 89%
Computational Drug Discovery Methods
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Artificial Intelligence for Natural Products Drug Discovery in Neurodegenerative Therapies: A Review — Emanuele Nardone, Francesco Fontanella, et al. · Biomolecules (2026) | TGRS Research Map | TGRS