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RUI: Extraction, Purification and Characterization of the Interaction Between Cyclotide and Cyclotide Aggregates with Lipid Bilayers

RUI: Extraction, Purification and Characterization of the Interaction Between Cyclotide and Cyclotide Aggregates with Lipid Bilayers
RUI:环肽和环肽聚集体与脂质双层之间相互作用的提取、纯化和表征
批准号:
2107567
负责人:
Neville Forlemu
金额:
$24.91万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-09-15 至 2025-08-31

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中文摘要
翻译
在化学系大分子、超分子和纳米化学(MSN)项目的支持下,格鲁吉亚格温内特学院科学技术学院的Neville Forlemu、Ajay Mallia、Simon Mwongela和Sairam Tangirala提议研究环肽的化学、结构和聚集特性。环肽是一种具有独特结构和特殊稳定性的微型蛋白质,用于植物保护免受害虫侵害。修饰环肽的能力可以增强它们在抗生素、诊断剂和生态友好农药设计中的潜在应用。为了指导具有不同应用的环肽的有效设计,研究人员提出了提取和纯化环肽的方法,以了解它们的化学和结构特性,自组装以及它们与脂质的相互作用。预计通过提高对科学,技术,工程和数学(STEM)教育的兴趣,并通过获得使用合成过程,分析仪器和计算技术的技能和专业知识,所涉及的学生的竞争力将提高技术和生命科学公司的生态系统,这些公司依赖于创新和研究在格鲁吉亚州蓬勃发展。本项目的目标是建立一个多元化的科研人才库,以满足不断增长的经济和社会需求。本项目旨在阐明涉及环肽及其与脂质双层相互作用的超分子结构的分子细节。采用混合分子动力学和蒙特-卡罗模拟研究了环肽聚集体的热力学性质。还将实施基于机器学习的算法来提高模拟速度。本研究旨在提高不同的cyclotides渗透或调节不同磷脂组成的脂质双层膜的理解。此外,膜结合,形态和自组装的环肽将探讨使用原子力显微镜,毛细管电泳测量。本研究的主要目的是:(i)利用绿色溶剂有效地提取和纯化环肽类化合物;(ii)确定环肽类化合物聚集体的形态、分子间和分子内的相互作用;(iii)确定环肽类化合物与脂双层的相互作用模式;(iv)研究环肽类化合物作为绿色农药的软材料、释放剂和支架的应用;(iv)研究环肽类化合物在农药中的应用。以及(v)展示了机器学习辅助计算在预测基于环肽的组装中的分子水平相互作用方面的应用。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
With the support of the Macromolecular, Supramolecular and Nanochemistry (MSN) Program in the Division of Chemistry, Neville Forlemu, Ajay Mallia, Simon Mwongela, and Sairam Tangirala at the School of Science and Technology, Georgia Gwinnett College, propose to investigate the chemical, structural, and aggregation properties of cyclotides. Cyclotides are mini-proteins with a unique structure and exceptional stability used by plants for protection against pests. The ability to modify cyclotides can enhance their potential applications in the design of antibiotics, diagnostic agents, and eco-friendly pesticides. To guide the efficient design of cyclotides with diverse applications, the investigators propose ways to extract and purify cyclotides, to understand their chemical and structural properties, self-assembly, and their interactions with lipids. It is anticipated that by enhancing interest in science, technology, engineering, and mathematics (STEM) education, and by gaining skills and expertise in using synthetic processes, analytical instruments, and computational techniques, the competitiveness of the students involved will be enhanced for the ecosystem of technology and life science companies that depend on innovation and research to thrive in the state of Georgia. It is a goal of the proposed research to generate a diverse pool of scientific researchers capable of meeting ever-growing economical and societal needs.This project aims to elucidate the molecular details of supramolecular structures involving cyclotides and their interactions with lipid bilayers. The thermodynamic properties of cyclotide aggregates will be investigated using hybrid molecular-dynamics and Monte-Carlo simulations. Machine learning-based algorithms to improve simulation speeds will also be implemented. This research seeks to enhance understanding of how diverse cyclotides permeate or modulate lipid bilayer membranes with varying phospholipid composition. In addition, the membrane binding, morphology, and self-assembly of cyclotides will be explored using atomic force microscopy, and capillary electrophoretic measurements. The goals of this research include: (i) utilizing green solvents to efficiently extract and purify cyclotides; (ii) determining of the morphology, inter- and intra-molecular interactions that give rise to self-assembly in cyclotide aggregates; (iii) ascertaining the mode of interactions between cyclotides and lipid bilayers; (iv) examining applications of cyclotides as soft materials, delivery agents, and scaffolds for green pesticides; and (v) demonstrating the application of machine learning-assisted computation to predict the molecular-level interactions in cyclotide-based assemblies.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.
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