AlphaFold2 artificial intelligence implication to the structure-based drug design and future of integrative structural biology

The rapid development of artificial intelligence in predicting the three-dimensional structure of proteins has broken down several important problems that have been faced by experimental structural biologics for decades. Structural biology has assisted in the discovery and development of many new dr...

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Bibliographic Details
Main Authors: Nugraha, Yudhi, Akbar, Nur Arifin, Ertanto, Yogi, Pramono, Andri P.
Format: Conference Proceeding
Language:English
Subjects:
Artificial intelligence
Biology
Collaboration
Cooperation
Crystallography
Design standards
Machine learning
Proteins
Structural design
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Summary:The rapid development of artificial intelligence in predicting the three-dimensional structure of proteins has broken down several important problems that have been faced by experimental structural biologics for decades. Structural biology has assisted in the discovery and development of many new drugs based on structural design. X-ray crystallography and Cryo-EM which have been the gold standard for determining the structure have many challenges in the cost of obtaining large quantities of pure protein samples, the emergence of AI has helped these problems. However, the current artificial intelligence technology actually still requires a database submitted by an experimental biologist for further machine learning material. In the future, stronger collaboration between AI and experimental structural biology is needed in the development of AI for structural biology. This collaboration bridge will provide many advances in the structure-based drug design and become an interesting technique that needs to be understood for integrative structural biology.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0173041