Abriata Luciano A
School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, CH-1015, Lausanne, Switzerland.
Commun Biol. 2024 Oct 29;7(1):1409. doi: 10.1038/s42003-024-07113-5.
The work by Hassabis and Jumper on protein structure prediction together with Baker’s supremacy in de novo protein design set the stage for a future where AI not only deciphers biology at the atomic level but also designs new molecules for biotechnology, medicine, and beyond. I provide an overview of the recent past, the present, and the future of AI in structural biology, from how it all started with the Critical Assessment of Structure Prediction (CASP) experiments and a protein engineering lab, to how the field could further evolve with AI models that eventually “understand” biology holistically.
哈萨比斯和琼珀在蛋白质结构预测方面的工作，以及贝克在从头蛋白质设计方面的卓越成就，为一个未来奠定了基础，在这个未来中，人工智能不仅能在原子层面解读生物学，还能为生物技术、医学及其他领域设计新分子。我将概述人工智能在结构生物学领域的过去、现在和未来，从它如何起源于蛋白质结构预测关键评估（CASP）实验和一个蛋白质工程实验室，到该领域如何借助最终能全面“理解”生物学的人工智能模型进一步发展。
