18-BBSRC-NSF/BIO - Structural modeling of interactome to assess phenotypic effects of genetic variation

18-BBSRC-NSF/BIO - 相互作用组的结构建模以评估遗传变异的表型效应

• 批准号: BB/T010487/1
• 负责人: Michael Sternberg
• 金额: $ 63.69万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FT010487%2F1
• 关键词: 18; BBSRC; NSF; BIO; Structural

This grant supports further collaboration between the groups of Prof Sternberg at Imperial College London and Prof Vakser at the University of Kansas, US. Today the sequences of genomes can be determined rapidly and from the gene sequences one obtains the sequence of proteins, which are central to biological function. Accordingly, a grand challenge for biology is to maximize the fundamental biological insights that can be obtained from determination of these protein sequences. In addition, genetic mutation often leads to minor differences in the gene sequence which result in the change of a single part of the protein sequence. These are known as single amino acid variants (SAVs). A vast amount of information on SAVs is available from a wide-range of organisms ranging from human through to bacteria. SAVs can either result in altered biological activity or may have no discernible effect. Understanding and predicting the effect of SAVs is central to many areas of biological research. Knowledge of the three-dimensional structure of proteins and their interactions with partner proteins (known as complexes) is therefore essential for understanding the mode of action of proteins and the interpretation of the effects of genetic variation. Under our previous collaboration the two groups developed the first version of a web-based resource called GWYRE (www.gwyre.org). This is a database of predicted 3D structures and complexes for biologically important organisms.The aim of the proposed research is to enhance the development of the GWYRE resource. To do this we will:(i) develop advanced methodology for high-throughput modelling of individual proteins(ii) develop high-throughput structure-based methods to predict interactions of experimentally determined and modelled proteins(iii) integrate (i) and (ii) to generate models for complexes(iv) develop enhanced computer algorithms to assess the effect of SAVs on structures and complexes(v) disseminate the GWYRE portal via publications, conference presentations, and the provision of training workshops(vi) engage in public outreach.

这笔赠款支持伦敦帝国理工学院的斯滕贝格教授和美国堪萨斯大学的Vakser教授之间的进一步合作。今天，基因组的序列可以迅速确定，从基因序列中可以获得蛋白质的序列，这对生物功能至关重要。因此，生物学的一个重大挑战是最大限度地提高从确定这些蛋白质序列中获得的基本生物学见解。此外，基因突变往往导致基因序列的微小差异，从而导致蛋白质序列的单个部分发生变化。这些被称为单氨基酸变体（SAV）。大量关于SAV的信息可从从从人类到细菌的广泛生物体获得。SAV可导致生物活性改变或可能无明显影响。了解和预测SAV的影响是生物学研究许多领域的核心。因此，了解蛋白质的三维结构及其与伴侣蛋白（称为复合物）的相互作用对于理解蛋白质的作用模式和解释遗传变异的影响至关重要。在我们之前的合作下，这两个小组开发了第一个版本的基于网络的资源，称为GWYRE（www.gwyre.org）。这是一个预测生物重要有机体的三维结构和复合体的数据库。拟议研究的目的是加强GWYRE资源的开发。为此，我们将：（i）开发用于单个蛋白质的高通量建模的先进方法（ii）开发基于高通量结构的方法来预测实验确定和建模的蛋白质的相互作用（iii）整合（i）和（ii）以生成复合物的模型（iv）开发增强的计算机算法来评估SAV对结构和复合物的影响（v）通过出版物、会议演示和提供培训讲习班传播GWYRE门户网站（vi）参与公共宣传。

项目成果

Computational Resources for Molecular Biology 2023

分子生物学计算资源 2023

• DOI: 10.1016/j.jmb.2023.168160
• 发表时间: 2023
• 期刊: Journal of Molecular Biology
• 影响因子: 5.6
• 作者: Mathews D