Collaborative Research: Geometric Elucidation of Supramolecular Assembly and Allostery with Experimental Validation

合作研究：超分子组装和变构的几何阐明与实验验证

基本信息

批准号：
1563291
负责人：
Maria Kurnikova
金额：
$ 33.2万
依托单位：
Carnegie-Mellon University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2016
资助国家：
美国
起止时间：
2016-09-01 至 2021-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1563291&HistoricalAwards=false
关键词：
Collaborative Research Geometric Elucidation Supramolecular

项目摘要

A wide variety of supramolecular structures in nature and engineering--from viruses to protein crystals to nanomaterials--assemble rapidly and spontaneously at room temperature with remarkable efficacy. Many assembly processes incorporate the phenomenon of allostery, where intermolecular interaction is controlled by binding events at a remote site of one of the interacting molecules. Despite increasingly sophisticated in vivo, in vitro and in silico experimental efforts, assembly processes are poorly understood. A more mathematically rigorous, and mechanistically intuitive theory is crucial not only to predict and engineer assembly and allostery but also to guide further time-consuming experimentation. Deeper understanding of assembly, allostery, and the role of the latter in the former will help control infectious diseases, assemble viral vectors for gene therapy, design drugs and engineer materials at the nanoscale.It is natural to expect that geometry and algorithmic complexity would play a key role in understanding the mechanisms underlying assembly, since the assembly process must crucially depend on the intricate shape and volume of the so-called assembly configuration space in which the molecules move relative to each other as they assemble. Conversely, it is also natural to expect that new mathematics, algorithms and software will result from the quest to understand intricate molecular configuration spaces and perform computations over them. The project's goals include new theorems and algorithms, their hybridization with prevailing methods, and opensource software. Progress is expected on long open problems in rigidity, configuration spaces, distance geometry; algorithms for efficient atlasing, search, sampling, and volume computation for high dimensional and topologically intricate configuration spaces; hybrid methods that combine the new algorithms with prevailing energy-based Monte Carlo simulation; and most significantly, concrete experimental validation of predictions. The project combines expertise in geometry and algorithms, experimental structural biology, and computational chemistry, and is well-suited for bringing the three communities together, for providing interdisciplinary training for research students as well as for outreach to schools and the public.

自然界和工程中的各种超分子结构——从病毒到蛋白质晶体再到纳米材料——在室温下快速自发地组装，具有显着的功效。许多组装过程都包含变构现象，其中分子间相互作用由相互作用分子之一的远程位点的结合事件控制。尽管体内、体外和计算机实验工作日益复杂，但人们对组装过程却知之甚少。数学上更严格、机械上更直观的理论不仅对于预测和设计组装和变构至关重要，而且对于指导进一步耗时的实验也至关重要。更深入地了解组装、变构以及后者在前者中的作用将有助于控制传染病、组装用于基因治疗的病毒载体、在纳米尺度上设计药物和工程材料。很自然地期望几何和算法复杂性将发挥作用在理解组装的机制方面发挥着关键作用，因为组装过程必须关键取决于所谓的组装构型空间的复杂形状和体积，在该空间中，分子在组装时相对于彼此移动。相反，人们也很自然地期望通过探索复杂的分子构型空间并对其进行计算来产生新的数学、算法和软件。该项目的目标包括新的定理和算法、它们与流行方法的混合以及开源软件。刚性、配置空间、距离几何等长期悬而未决的问题有望取得进展；用于高维和拓扑复杂配置空间的高效图集、搜索、采样和体积计算的算法；将新算法与流行的基于能量的蒙特卡罗模拟相结合的混合方法；最重要的是，预测的具体实验验证。该项目结合了几何和算法、实验结构生物学和计算化学方面的专业知识，非常适合将三个社区聚集在一起，为研究生提供跨学科培训以及向学校和公众进行推广。