Computational Molecular Biology 2024 Vol.14, No.3, 95-96 http://bioscipublisher.com/index.php/cmb 96 remind us that while AI provides powerful tools, it cannot yet replace the nuanced understanding gained through hands-on experimentation. The discourse between these two leading scientists encapsulates the dual nature of AI's impact on structural biology. On one hand, AI represents a monumental leap forward, dramatically enhancing our data acquisition capabilities and opening new avenues for scientific inquiry. On the other, it underscores the continued necessity of traditional experimental approaches to validate and expand upon AI-generated predictions. As we move forward, the integration of AI in structural biology should be approached with a balanced perspective. Embracing AI’s capabilities while remaining vigilant about its limitations will be key to advancing our understanding of biomolecular structures and their functions. By fostering a collaborative environment where AI and experimental techniques complement each other, we can unlock new levels of scientific discovery and innovation. In conclusion, the contributions of AI, as showcased by AlphaFold 3, are undeniably transformative. However, the insights from both Professor Shi Yigong and Yan Ning remind us that the path to comprehensive biological understanding is multifaceted, requiring both computational prowess and experimental diligence. Together, these approaches hold the promise of a future where the mysteries of life at the molecular level are unraveled with unprecedented clarity and precision. References Abramson J., Adler J., Dunger J., Evans R., Green T., Pritzel A., Ronneberger O., Willmore L., Ballard A.J., Bambrick J., Bodenstein S.W., Evans D.A., Chia C.H., O’Neill M., Reiman D., Tunyasuvunakool K., Wu Z., Žemgulytė A., Arvaniti E., Beattie C., Bertolli O., Bridgland A., Cherepanov A., Congreve M., Cowen-Rivers A.I., Cowie A., Figurnov M., Fuchs F.B., Gladman H., Jain R., Khan Y.A., Low C.M.R., Perlin K., Potapenko A., Savy P., Singh S., Stecula A., Thillaisundaram A., Tong C., Yakneen S., Zhong E.D., Zielinski M., Žídek A., Bapst V., KohliP., Jaderberg M., Hassabis D., and Jumper J.M., 2024, Accurate structure prediction of biomolecular interactions with AlphaFold 3, Nature, 1-3. https://doi.org/10.1038/s41586-024-07487-w
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