Learning and characterizing DNA sequences in DNA-nanotube hybrid structures for high-affinity binding and recognition of molecular targets
学习和表征 DNA-纳米管混合结构中的 DNA 序列,以实现分子靶标的高亲和力结合和识别
基本信息
- 批准号:2106587
- 负责人:
- 金额:$ 48.22万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-06-01 至 2025-05-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Nanomaterials with unique and powerful optical properties have emerged as promising tools for imaging and sensing small biological molecules present in cells, tissues, and live organisms. Imaging these important molecules is hampered by the lack of sensing tools, limiting our ability to understand how certain biological molecules allow the brain to communicate with the body. This project will develop new experimental and theoretical tools to detect the presence of brain-relevant molecules, with a focus on two molecules called serotonin and oxytocin, which are involved in human mood, emotions, social behavior, and their dysregulation in disorders like depression and autism. The new tools are based on DNA molecules, long molecules composed of repeating subunits, wrapped around long and rigid carbon nanotubes, which will detect serotonin and oxytocin in the sample by emitting light. The key objective is to discover special DNA molecules that will bind strongly to serotonin and oxytocin, bring them close to the nanotube surface, and change the optical signal that the nanotube emits. This objective will be addressed by combining the information obtained in experimental screening of DNA-nanotube systems with the artificial intelligence computer methods and computer simulations. The project will lead to new methods for discovery of useful DNA molecules, which could be applied towards developing tools to detect other biological molecules of interest that currently remain ‘invisible’. The efforts in this project will enrich the training and research experiences of underrepresented students at the University of Texas at El Paso and the University of California, Berkeley and provide the basis for demonstrations on science behind serotonin and oxytocin to middle school student groups. Sensing and imaging of small molecular analytes within complex biological samples is of high interest but remains a challenge due to the lack of suitable imaging tools. This project will establish methods to systematically develop conjugates of single-walled carbon nanotubes and single stranded DNA for optical sensing of selected analytes. The methods will be established for two analytes, serotonin, and oxytocin brain neuromodulators. To develop new DNA-nanotube optical sensors, unique DNA sequences, which simultaneously bind with high affinity to the analytes on nanotube surfaces and lead to strong optical response of the nanotubes, need to be identified. Yet, discovering these useful DNA sequences has been a challenge, with most research efforts relying on screening-based serendipity. In this project, the research team will combine the high throughput datasets of experimental DNA sequence screening methods, lower throughput spectroscopic measurements, and the artificial intelligence-based methodology to learn and predict DNA sequences that bind with high affinity to analytes on nanotube surfaces and induce high nanotube optical activity. First, the team will develop and validate new methods to: 1) determine short DNA sequences that bind with high affinity to serotonin and oxytocin molecules on nanotube surfaces; and 2) learn and predict DNA sequences that provide high optical response to DNA-nanotube conjugates in the presence of the analytes. Then, the molecular basis of analyte recognition by DNA sequences on nanotube surfaces will be explored with simulations. This project should have a significant impact on many individuals from underrepresented groups at the University of Texas at El Paso and the University of California, Berkeley through several activities that will be organized. The computational chemistry modules will be introduced into physical chemistry laboratory classes, a student-coordinated research event will be organized, and demonstrations on the science behind serotonin and oxytocin will be developed for middle school student groups. Undergraduate students from underrepresented groups will be recruited and trained in the above research.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.
具有独特而强大的光学特性的纳米材料已经成为成像和传感存在于细胞、组织和活生物体中的小生物分子的有前途的工具。由于缺乏传感工具,对这些重要分子进行成像受到了阻碍,限制了我们了解某些生物分子如何使大脑与身体进行交流的能力。该项目将开发新的实验和理论工具,以检测与大脑相关的分子的存在,重点关注两种称为血清素和催产素的分子,这两种分子与人类的情绪、情感、社会行为以及抑郁症和自闭症等疾病的失调有关。新的工具是基于DNA分子,由重复的亚基组成的长分子,包裹在长而坚硬的碳纳米管上,它将通过发光来检测样品中的血清素和催产素。关键目标是发现一种特殊的DNA分子,这种分子能与血清素和催产素紧密结合,使它们靠近纳米管表面,并改变纳米管发出的光信号。这一目标将通过将dna -纳米管系统实验筛选获得的信息与人工智能计算机方法和计算机模拟相结合来解决。该项目将带来发现有用DNA分子的新方法,这可以应用于开发工具来检测目前仍然“看不见”的其他感兴趣的生物分子。该项目的努力将丰富德克萨斯大学埃尔帕索分校和加州大学伯克利分校代表性不足的学生的培训和研究经验,并为向中学生群体展示血清素和催产素背后的科学提供基础。复杂生物样品中小分子分析物的传感和成像具有很高的兴趣,但由于缺乏合适的成像工具,仍然是一个挑战。该项目将建立方法,系统地开发单壁碳纳米管和单链DNA的共轭物,用于选定分析物的光学传感。该方法将建立两种分析物,血清素和催产素脑神经调节剂。为了开发新的DNA-纳米管光学传感器,需要鉴定出独特的DNA序列,这些DNA序列可以同时与纳米管表面的分析物高亲和力结合,并导致纳米管的强光学响应。然而,发现这些有用的DNA序列一直是一个挑战,因为大多数研究工作都依赖于基于筛选的意外发现。在这个项目中,研究团队将结合实验DNA序列筛选方法的高通量数据集,低通量光谱测量和基于人工智能的方法来学习和预测与纳米管表面分析物高亲和力结合并诱导高纳米管光学活性的DNA序列。首先,该团队将开发并验证新方法:1)确定纳米管表面与血清素和催产素分子高亲和力结合的短DNA序列;2)学习和预测在分析物存在下对DNA-纳米管偶联物提供高光学响应的DNA序列。然后,将通过模拟来探索纳米管表面DNA序列识别分析物的分子基础。该项目将通过组织的几项活动,对德克萨斯大学埃尔帕索分校和加州大学伯克利分校中代表性不足的群体的许多个人产生重大影响。将计算化学模块引入物理化学实验课,并组织学生参与的研究活动,以中学生为对象开展5 -羟色胺和催产素的科学演示。上述研究将招募和培训来自代表性不足群体的本科生。该奖项反映了美国国家科学基金会的法定使命,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。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Lela Vukovic其他文献
Highly Pegylated Sterically Stabilized Micelles in Aqueous Media: Structure, Dynamics, and Storage of Therapeutic Agents
- DOI:
10.1016/j.bpj.2011.11.2724 - 发表时间:
2012-01-31 - 期刊:
- 影响因子:
- 作者:
Lela Vukovic;Fatima A. Khatib;Stephanie P. Drake;Antonett Madriaga;Kenneth S. Brandenburg;Alan T. Tang;Neil Shah;Petr Kral;Hayat Onyuksel - 通讯作者:
Hayat Onyuksel
Computational Modeling of DNA-Nanotube Hybrid Conjugates for Biosensor Applications
- DOI:
10.1016/j.bpj.2020.11.2256 - 发表时间:
2021-02-12 - 期刊:
- 影响因子:
- 作者:
Lela Vukovic - 通讯作者:
Lela Vukovic
Lela Vukovic的其他文献
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