Developing statistical, topological and geometrical techniques for ab-initio protein structure prediction

开发用于从头算蛋白质结构预测的统计、拓扑和几何技术

• 批准号: 2671188
• 金额: --
• 依托单位: Durham University
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2671188
• 关键词: Developing; statistical; topological; geometrical; techniques

The project's aim is to develop techniques for reliably interpreting experimental small angle scattering data. This data can provide critical information regarding the varying structure of flexible proteins. The method will combine a parsimonious geometrical model of proteins tertiary structure to interpret the data, and monte-carlo based molecular dynamics simulations of the protein in solution to corroborate or rule out it predictions. One aspect of this development will focus on interpreting specific data sets: novel proteins whose structure and flexibility are as yet uncharacterised. The second aspect will focus on more fundamental issues, such as using the experimental data to asses the results of the molecular dynamics simulations and provide insight into both their successful characteristic as well as their limitations. In performing this second task it is hoped some fundamental insights into the nature protein dynamics can be revealed.

该项目的目的是开发可靠地解释实验小角度散射数据的技术。这些数据可以提供有关柔性蛋白质不同结构的关键信息。该方法将结合联合收割机蛋白质三级结构的简约几何模型来解释数据，并基于蒙特-卡罗的蛋白质溶液的分子动力学模拟来证实或排除它的预测。这一发展的一个方面将集中在解释特定的数据集：新的蛋白质，其结构和灵活性尚未确定。第二个方面将集中在更基本的问题，如使用实验数据来评估分子动力学模拟的结果，并提供洞察他们的成功特点以及他们的局限性。在执行第二项任务时，希望可以揭示一些对自然蛋白质动力学的基本见解。