Suppr超能文献

阿尔法折叠2与核磁共振光谱:理解蛋白质结构、动力学和功能的合作伙伴。

AlphaFold 2 and NMR Spectroscopy: Partners to Understand Protein Structure, Dynamics and Function.

作者信息

Laurents Douglas V

机构信息

Instituto de Química Física Rocasolano, Consejo Superior de Investigaciones Científicas (IQFR/CSIC), Madrid, Spain.

出版信息

Front Mol Biosci. 2022 May 17;9:906437. doi: 10.3389/fmolb.2022.906437. eCollection 2022.

Abstract

The artificial intelligence program AlphaFold 2 is revolutionizing the field of protein structure determination as it accurately predicts the 3D structure of two thirds of the human proteome. Its predictions can be used directly as structural models or indirectly as aids for experimental structure determination using X-ray crystallography, CryoEM or NMR spectroscopy. Nevertheless, AlphaFold 2 can neither afford insight into how proteins fold, nor can it determine protein stability or dynamics. Rare folds or minor alternative conformations are also not predicted by AlphaFold 2 and the program does not forecast the impact of post translational modifications, mutations or ligand binding. The remaining third of human proteome which is poorly predicted largely corresponds to intrinsically disordered regions of proteins. Key to regulation and signaling networks, these disordered regions often form biomolecular condensates or amyloids. Fortunately, the limitations of AlphaFold 2 are largely complemented by NMR spectroscopy. This experimental approach provides information on protein folding and dynamics as well as biomolecular condensates and amyloids and their modulation by experimental conditions, small molecules, post translational modifications, mutations, flanking sequence, interactions with other proteins, RNA and virus. Together, NMR spectroscopy and AlphaFold 2 can collaborate to advance our comprehension of proteins.

摘要

人工智能程序AlphaFold 2正在彻底改变蛋白质结构测定领域,因为它能准确预测三分之二的人类蛋白质组的三维结构。其预测结果可直接用作结构模型,或间接辅助使用X射线晶体学、冷冻电镜或核磁共振光谱法进行实验性结构测定。然而,AlphaFold 2既无法深入了解蛋白质如何折叠,也无法确定蛋白质的稳定性或动力学。罕见折叠或次要的替代构象也无法被AlphaFold 2预测,该程序也不会预测翻译后修饰、突变或配体结合的影响。预测效果较差的另外三分之一人类蛋白质组在很大程度上对应于蛋白质的内在无序区域。作为调节和信号网络的关键,这些无序区域常常形成生物分子凝聚物或淀粉样蛋白。幸运的是,核磁共振光谱法在很大程度上弥补了AlphaFold 2的局限性。这种实验方法能提供有关蛋白质折叠和动力学以及生物分子凝聚物和淀粉样蛋白的信息,以及它们如何受实验条件、小分子、翻译后修饰、突变、侧翼序列、与其他蛋白质、RNA和病毒的相互作用的影响。核磁共振光谱法和AlphaFold 2可以共同协作,增进我们对蛋白质的理解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bbe9/9152297/f70981fd9d13/fmolb-09-906437-g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验