Collaborative Research: Branching in RNA Secondary Structures

合作研究：RNA二级结构的分支

基本信息

批准号：
1815832
负责人：
Svetlana Poznanovikj
金额：
$ 11.62万
依托单位：
Clemson University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-01 至 2023-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1815832&HistoricalAwards=false
关键词：
Collaborative Research Branching RNA Secondary

项目摘要

This project will develop mathematical tools to better understand the structure of biomolecules with important cellular functions. RNA, a single-strand molecule derived from DNA, is essential in various biological roles. Besides converting the information stored in DNA into proteins, some RNAs control vital cell processes. RNA chains must fold into specific shapes to serve these roles. However, despite the series of refinements to the commonly-used energy model for predicting RNA structure, the accuracy of folding predictions for longer RNA sequences is not satisfying. This project will use geometric combinatorics to gain insights into the stability and accuracy of predictions from the current energy model. Addressing these biologically relevant questions leads to important mathematical problems which intersect with active research areas in polyhedral geometry and discrete optimization. Results from this project will be used to improve software predicting RNA folding and assist molecular biologists studying RNA function. Additionally, as part of the project, the investigators will train graduate and undergraduate students in research at the interface of mathematics and biology.This research will advance biological understanding and mathematical knowledge within the developing field of discrete mathematical biology at the juncture between geometric combinatorics and molecular biology. The affine energy function which governs the entropic cost of branching is a known shortcoming of the current nearest neighbor thermodynamic model. However, this coarse approximation to biochemical reality, which is highly constrained by computational efficiency, is well-suited to mathematical modeling and analysis. Methods from geometric combinatorics (polytopes and their normal fans) will be used to give the first parametric analysis of the branching of biological RNA sequences. Biologically relevant questions, including the accuracy and stability of the current branching parameters in thermodynamic optimization methods for RNA secondary structure prediction, will be addressed using methods from geometric combinatorics. The similarities and differences of these RNA branching polytopes will then be delineated by addressing the challenges of characterization, comparison, and approximation. This will provide new insight into the inability of current prediction methods to distinguish native branching characteristics from the large number of suboptimal structures.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目将开发数学工具，以更好地了解具有重要细胞功能的生物分子的结构。 RNA是源自DNA的单链分子，在各种生物学作用中都是必不可少的。除了将存储在DNA中的信息转换为蛋白质外，RNA还控制了重要的细胞过程。 RNA链必须折叠成特定的形状才能发挥这些作用。但是，尽管对预测RNA结构的常用能量模型进行了一系列的改进，但较长的RNA序列的折叠预测的准确性并不令人满意。该项目将使用几何组合物来洞悉当前能量模型的预测的稳定性和准确性。解决这些与生物学相关的问题会导致重要的数学问题，这些问题与多面体几何学和离散优化的主动研究领域相交。该项目的结果将用于改善预测RNA折叠的软件，并帮助研究RNA功能的分子生物学家。此外，作为该项目的一部分，研究人员将在数学和生物学界面进行研究培训研究生和本科生。这项研究将在几何学组合和分子生物学之间的连接期在开发的离散数学生物学领域中提高生物学理解和数学知识。控制分支的熵成本的仿射能函数是当前最近的邻居热力学模型的已知缺点。但是，这种对生化现实的粗略近似受到计算效率的高度限制，非常适合数学建模和分析。几何组合物（多型及其正常风扇）的方法将用于对生物RNA序列的分支进行第一个参数分析。生物学相关的问题，包括用于RNA二级结构预测的热力学优化方法中当前分支参数的准确性和稳定性，将使用几何组合学中的方法来解决。然后，将通过解决表征，比较和近似的挑战来描述这些RNA分支多面体的相似性和差异。这将为当前的预测方法提供新的见解，即将本地分支特征与大量次优结构区分开来。该奖项反映了NSF的法定任务，并被认为是通过基金会的智力优点和更广泛影响的审查标准通过评估来通过评估来获得支持的。