Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA.
Department of Computational Biophysics and Bioinformatics, Jagiellonian University, Krakow, Poland.
Expert Opin Drug Discov. 2023 Jul-Dec;18(11):1221-1230. doi: 10.1080/17460441.2023.2246881. Epub 2023 Aug 17.
Macromolecular X-ray crystallography and cryo-EM are currently the primary techniques used to determine the three-dimensional structures of proteins, nucleic acids, and viruses. Structural information has been critical to drug discovery and structural bioinformatics. The integration of artificial intelligence (AI) into X-ray crystallography has shown great promise in automating and accelerating the analysis of complex structural data, further improving the efficiency and accuracy of structure determination.
This review explores the relationship between X-ray crystallography and other modern structural determination methods. It examines the integration of data acquired from diverse biochemical and biophysical techniques with those derived from structural biology. Additionally, the paper offers insights into the influence of AI on X-ray crystallography, emphasizing how integrating AI with experimental approaches can revolutionize our comprehension of biological processes and interactions.
Investing in science is crucially emphasized due to its significant role in drug discovery and advancements in healthcare. X-ray crystallography remains an essential source of structural biology data for drug discovery. Recent advances in biochemical, spectroscopic, and bioinformatic methods, along with the integration of AI techniques, hold the potential to revolutionize drug discovery when effectively combined with robust data management practices.
目前,大分子 X 射线晶体学和 cryo-EM 是用于确定蛋白质、核酸和病毒三维结构的主要技术。结构信息对于药物发现和结构生物信息学至关重要。人工智能 (AI) 被整合到 X 射线晶体学中,在自动化和加速分析复杂结构数据方面显示出巨大的潜力,进一步提高了结构确定的效率和准确性。
这篇综述探讨了 X 射线晶体学与其他现代结构测定方法之间的关系。它检查了从不同的生化和生物物理技术获得的数据与从结构生物学中获得的数据的整合。此外,本文还探讨了 AI 对 X 射线晶体学的影响,强调了将 AI 与实验方法相结合如何彻底改变我们对生物过程和相互作用的理解。
由于其在药物发现和医疗保健进步中的重要作用,对科学的投资至关重要。X 射线晶体学仍然是药物发现结构生物学数据的主要来源。生化、光谱和生物信息学方法的最新进展,以及 AI 技术的整合,当与强大的数据管理实践相结合时,有可能彻底改变药物发现。