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International Journal of Molecular Medical Science, 2024, Vol. 14, No. 3
Received: 10 May, 2024 Accepted: 16 May, 2024 Published: 30 May, 2024
The integration of artificial intelligence (AI) in structural biology has revolutionized medicine design, notably through AlphaFold 3's accurate prediction of biomolecular interactions. With AI predicting over 600 million protein structures, the vast database enhances the identification of novel drug targets and optimization of therapeutic molecules. However, AI's limitations in capturing protein dynamics highlight the continued need for experimental validation. The synergy between AI's predictive power and empirical methods like cryo-EM and NMR spectroscopy fosters comprehensive drug design, accelerating the development of personalized medicine. This perspective underscores the necessity of balancing AI and experimental approaches to unlock unprecedented therapeutic innovations.
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. Jim Mason
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. AI
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. Experimental validation
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