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在晶体学中使用基于人工智能的模型的最佳实践及其对结构生物学的影响

Marc Graille¹, Sophie Sacquin-Mora², Antoine Taly²

¹Laboratoire de Biologie Structurale de la Cellule (BIOC), CNRS, École Polytechnique, Institut Polytechnique de Paris, 91120 Palaiseau, France.

Journal of chemical information and modeling

|June 12, 2023

概括

像AlphaFold2和RosettaFold这样的人工智能模型正在改变结构生物学. 这项研究提供了使用这些AI 3D结构预测在X射线晶体学分子替换中的指导方针.

科学领域:

结构生物学是结构生物学.
计算生物学是一种计算生物学.
科学中的人工智能.

背景情况:

像AlphaFold2 (AF2),RosettaFold (RF) 和大型语言模型 (LLM) 这样的AI工具已经彻底改变了3D结构预测.
这些人工智能模型已经证明了高精度,并在科学界产生了显著的热情.
人工智能驱动的3D结构预测的应用经常被公布,突出了它们的影响.

研究的目的:

为用户提供AI 3D结构预测模型提供的全面信息.
为有效利用这些模型在X射线晶体学中进行分子替代提供指导方针.
鼓励共享详细的使用信息,包括挑战和成功,以改善AI管道.

主要方法:

专注于AI 3D结构预测模型在X射线晶体学中的应用.
制定准则,准备用于分子替代 (MR) 试验的AI生成模型.
鼓励社区共享MR结果,包括预测失败的情况以及它们如何与实验数据相匹配.

主要成果:

人工智能模型提供了超出基本结构预测的宝贵信息.
具体的指导方针可以提高人工智能模型的实用性,用于解决晶体学中的相位问题.
社区的反对于完善人工智能模型应用程序和评估其质量至关重要.

结论:

为了最大限度地提高AI 3D结构预测模型的实用性,需要用户意识和特定的应用策略.
对分子替代制备的指导方针可以提高X射线结晶学中的成功率.
与人工智能模型合作分享研究经验对于推进结构生物学至关重要.

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X-ray Crystallography

X-ray Crystallography

The size of the unit cell and the arrangement of atoms in a crystal may be determined from measurements of the diffraction of X-rays by the crystal, termed X-ray crystallography.
Diffraction
Diffraction is the change in the direction of travel experienced by an electromagnetic wave when it encounters a physical barrier whose dimensions are comparable to those of the wavelength of the light. X-rays are electromagnetic radiation with wavelengths about as long as the distance between neighboring...

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X-ray diffraction or XRD is an analytical tool that utilizes X-rays to study ordered structures such as crystalline organic and inorganic samples, polycrystalline materials, proteins, carbohydrates, and drugs.
According to Bragg's law, when X-rays strike the sample positioned on a stage, the rays are scattered by the electron clouds around the sample atoms. The X-ray diffraction or scattering is caused by constructive interference of the X-ray waves that reflect off the internal...