Validation of NMR protein structures using FIRST and RCI

使用 FIRST 和 RCI 验证 NMR 蛋白质结构

• 批准号: BB/P020038/1
• 负责人: Michael Williamson
• 金额: $ 36.64万
• 依托单位: University of Sheffield
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FP020038%2F1
• 关键词: Validation; NMR; protein; structures; using

Protein structures are essential for understanding protein function, and for drug design. In order to make use of structures, it is vital for users to know how good the structures are. The structures are generated mainly from X-ray crystallography and NMR. For crystal structures, there are reliable ways of knowing how good the structure is. These are based on the fact that a structure can be used to calculate exactly what the input data should look like: a comparison with the actual diffraction data therefore gives a reliable quantitative measure of quality. For NMR, there is no such measure, meaning that so far it is very difficult to know how good an NMR structure is. This is a problem not only for users of structural information, but also for the scientists who calculate the structures, since they also have no way to judge how good their structures are.In this proposal we describe a method for calculating the quality of NMR structures (ie, validation), based on comparing two measures of local rigidity, one derived from the structures and one from the original input data. The first measure is calculated using an established method for identifying rigid clusters based on graph theory, called FIRST, and developed by our collaborator Dr Sljoka. The second method uses the Random Coil Index (RCI), which is a program based on the simple idea that the NMR frequencies ('chemical shifts') of protein backbone atoms have very characteristic 'random coil' shifts when the protein is locally disordered, and therefore that the experimentally measured shifts in a protein can be used to quantify to what extent a given amino acid residue is disordered. A comparison of these two measures of local rigidity therefore provides a residue-by-residue test of how well the rigidity of the structures compares to the experimentally determined 'true' rigidity. Although this is not a direct comparison between structure and input, it is likely to be as close as one can get for NMR structures, and is a major improvement in the NMR structure determination process. The proposal describes how we will go about implementing the comparison and checking that it works as expected, and then how we will make it available to the community and use it to examine NMR structures, for example by reporting on the quality of all existing protein NMR structures (objective 1).Having developed the validation tool, we then propose to apply it to some useful ends. The first of these (objective 2) is to identify sets of 'good' and 'bad' NMR structures. So far there has been no good way to know how good structures are: by identifying such structures we expect to generate an important resource for the structural biology community by marking out quality criteria and therefore stimulating further research into structure quality.Whereas crystal structures are typically represented by a single set of coordinates at the average position (together with 'B factors' that represent the uncertainty in each coordinate), NMR structures are always represented as an ensemble of (typically 20) structures. There is a valid reason for this, that NMR structures are inherently less well defined than crystal structures. Nevertheless, it is confusing and unnecesary. We aim to apply our method to define more closely how many structures in an ensemble are really necessary, and whether some are simply wrong. In order to assist the process, we will improve current methods for calculating chemical shifts from structures, by modifying them to work on ensembles. Finally, we shall use our methods to look at an important class of protein structures called Intrinsically Disordered Proteins, to test whether current methods provide a correct representation of the true conformational ensemble. These represent roughly one third of human proteins (including many responsible for signalling), so are an important topic.

蛋白质结构对于理解蛋白质功能和药物设计至关重要。为了使用结构，用户了解结构的好坏是至关重要的。这些结构主要是由x射线晶体学和核磁共振生成的。对于晶体结构，有可靠的方法知道结构有多好。这些都是基于这样一个事实，即一个结构可以用来精确地计算输入数据应该是什么样子：因此，与实际衍射数据的比较提供了可靠的质量定量测量。对于核磁共振，没有这样的测量，这意味着到目前为止很难知道核磁共振结构有多好。这不仅是结构信息使用者的问题，也是计算结构的科学家的问题，因为他们也没有办法判断他们的结构有多好。在这个建议中，我们描述了一种计算核磁共振结构质量（即验证）的方法，基于比较两种局部刚度的测量，一种来自结构，另一种来自原始输入数据。第一个测量是使用一种基于图论的确定刚性簇的既定方法来计算的，该方法被称为first，由我们的合作者Sljoka博士开发。第二种方法使用随机线圈指数（RCI），这是一个基于简单想法的程序，即当蛋白质局部无序时，蛋白质主链原子的核磁共振频率（“化学位移”）具有非常典型的“随机线圈”位移，因此实验测量的蛋白质位移可用于量化给定氨基酸残基的无序程度。因此，对这两种局部刚度测量的比较提供了一种对结构刚度与实验确定的“真实”刚度相比有多好的残差测试。虽然这不是结构和输入之间的直接比较，但它可能是核磁共振结构所能得到的最接近的比较，是核磁共振结构确定过程中的重大改进。该提案描述了我们将如何实现比较并检查它是否如预期的那样工作，然后我们将如何将其提供给社区并使用它来检查NMR结构，例如通过报告所有现有蛋白质NMR结构的质量（目标1）。开发了验证工具后，我们建议将其应用于一些有用的目的。第一个（目标2）是识别“好的”和“坏的”核磁共振结构。到目前为止，还没有很好的方法来知道结构有多好：通过识别这样的结构，我们希望通过制定质量标准为结构生物学社区提供重要的资源，从而刺激对结构质量的进一步研究。晶体结构通常由平均位置的一组坐标表示（加上代表每个坐标不确定性的“B因子”），而核磁共振结构总是被表示为（通常是20个）结构的集合。有一个合理的理由，核磁共振结构本质上比晶体结构更不明确。然而，这是令人困惑和不必要的。我们的目标是应用我们的方法来更紧密地定义一个集合中有多少结构是真正必要的，以及是否有一些结构是完全错误的。为了辅助这一过程，我们将改进现有的计算结构化学位移的方法，通过修改它们来计算整体。最后，我们将使用我们的方法来研究一类重要的蛋白质结构，称为内在无序蛋白质，以测试当前的方法是否提供了真正的构象集合的正确表示。这些蛋白质约占人类蛋白质的三分之一（包括许多负责信号传导的蛋白质），因此是一个重要的话题。

项目成果

Improved methodology for protein NMR structure calculation using hydrogen bond restraints and ANSURR validation: The SH2 domain of SH2B1

• DOI: 10.1016/j.str.2023.05.012
• 发表时间: 2023-08-03
• 期刊: STRUCTURE
• 影响因子: 5.7
• 作者: Fowler，Nicholas J.;Albalwi，Marym F.;Williamson，Mike P.
• 通讯作者: Williamson，Mike P.

A method for validating the accuracy of NMR protein structures

验证 NMR 蛋白质结构准确性的方法

• DOI: 10.1101/2020.04.20.048777
• 发表时间: 2020
• 作者: Fowler N

A method for validating the accuracy of NMR protein structures.

• DOI: 10.1038/s41467-020-20177-1
• 发表时间: 2020-12-18
• 期刊: Nature communications
• 影响因子: 16.6
• 作者: Fowler NJ;Sljoka A;Williamson MP
• 通讯作者: Williamson MP

The accuracy of protein structures in solution determined by AlphaFold and NMR

通过 AlphaFold 和 NMR 测定溶液中蛋白质结构的准确性

• DOI: 10.1101/2022.01.18.476751
• 发表时间: 2022
• 作者: Fowler N