Accelerated Discovery of Functional Tetramine-based Metal-Organic Cages using High-throughput Computational Screening Methods
Accelerated Discovery of Functional Tetramine-based Metal-Organic Cages using High-throughput Computational Screening Methods
批准号:
2751538
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --
中文摘要
金属有机笼(MOC)是由有机连接剂和金属离子构建的多面体形状的微小人工容器。它们在其空腔内结合较小分子(客体)的能力使其在催化,分离,传感,药物输送和生物技术等领域具有潜在的应用性。这项工作的目的是发展新的功能MOCs,通过子组件自组装从四胺接头制备。这种MOC的常规发现过程涉及试错过程,这可能导致时间和资源的浪费。该项目旨在通过采用基于开源python库stk56的虚拟筛选方法来加速这一过程。这种方法将导致选择一组被建议自组装成新MOC的构建块,例如具有逐渐增大的腔尺寸或具有各向异性腔。这些积木将在实验室制备,并研究它们的自组装和功能。该项目预计将提供深入了解MOC的基本设计原则,并导致发现具有新功能的MOC。由于跨学科的性质,该项目预计将促进来自超分子化学,计算机科学,计算化学和数学等各个领域的研究人员之间的合作。
英文摘要
Metal-organic cages (MOCs) are tiny artificial containers in the shape of polyhedra built from organic linkers and metal-ions. Their ability to bind smaller molecules (guests) within their cavities gives them potential applicability in fields such as catalysis, separations, sensing, drug delivery and biotechnology. This work aims towards the development of new functional MOCs, prepared from tetramine linkers through subcomponent self-assembly. The conventional discovery process of such MOCs involves trial-and-error processes which can lead to a waste of time and resources. This project aims to accelerate this process by employing virtual screening methods based on the open-sourced python library stk56. This approach will lead to the selection of a set of building blocks that are suggested to self-assemble into new MOCs, for example with progressively larger cavity sizes or with anisotropic cavities. These building blocks will be prepared in the lab and their self- assembly and functionality will be investigated. This project is expected to provide insight into the fundamental design principles of MOCs and to lead to the discovery of MOCs with new functionality. Due to the interdisciplinary character, this project is expected to foster collaborations between researchers from a variety of fields such as supramolecular chemistry, computer science, computational chemistry, and mathematics.
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