Revolutionizing drug discovery: an AI-powered transformation of molecular docking

AI-based molecular docking, a computational technique fueled by artificial intelligence (AI) algorithms, is transforming the landscape of drug discovery. This method, crucial for predicting atomic-level interactions between small molecules (ligands) and target proteins (receptors), addresses the lim...

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Bibliographic Details
Published in:Medicinal chemistry research 2024, Vol.33 (12), p.2187-2203
Main Authors: Fadahunsi, Adeola Abraham, Uzoeto, Henrietta Onyinye, Okoro, Nkwachukwu Oziamara, Cosmas, Samuel, Durojaye, Olanrewaju Ayodeji, Odiba, Arome Solomon
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
Biochemistry
Biomedical and Life Sciences
Biomedicine
Bioorganic Chemistry
Deep learning
Drug discovery
Inorganic Chemistry
Ligands
Machine learning
Medicinal Chemistry
Molecular docking
Neural networks
Pharmacology/Toxicology
Receptors
Review Article
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Summary:AI-based molecular docking, a computational technique fueled by artificial intelligence (AI) algorithms, is transforming the landscape of drug discovery. This method, crucial for predicting atomic-level interactions between small molecules (ligands) and target proteins (receptors), addresses the limitations of traditional approaches by leveraging machine learning (ML) techniques. Key enhancements include the improvement of scoring functions through training on large datasets, exploration of conformational spaces for ligands and receptors, and the application of deep learning, particularly neural networks. This study reviews some of the newest cutting-edge AI-based docking methodologies, each designed to tackle specific challenges in drug discovery.
ISSN:1054-2523
1554-8120
DOI:10.1007/s00044-024-03253-9