Alpha-Fold 3: Revolutionizing Drug Design, Protein Stability, Allostery, and Ai-Driven Therapeutics
Year: 2025
Type: article
Abstract: AlphaFold, an AI-driven protein structure prediction system developed by DeepMind, has revolutionized structural biology by achieving remarkable accuracy in protein modeling. By leveraging deep learning techniques, AlphaFold provides high-resolution three-dimensional protein structures, surpassing traditional experimental methods in speed and efficiency. Its applications span drug discovery, cancer research, genomics, and bioengineering, aiding in mutation impact analysis, molecular simulations, and personalized medicine. Despite its success, AlphaFold faces challenges in modeling intrinsically disordered proteins, predicting allosteric mechanisms, and simulating protein dynamics. Future advancements in AI-driven structural biology, molecular modeling, and open-source collaboration will further expand its impact in biomedical research and therapeutic innovations. This study explores the methodologies, applications, and future prospects of AlphaFold, highlighting its transformative role in computational biology.
Authors: Sumaiya P.S, Sweety George, Thamanna R.P., Manesh D
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W6968034370
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