Network for Computational Nanotechnology - Engineered nanoBIO Node

计算纳米技术网络 - 工程化 nanoBIO 节点

• 批准号: 1720625
• 负责人: James Glazier
• 金额: $ 400万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1720625&HistoricalAwards=false
• 关键词: Network; Computational; Nanotechnology; Engineered; nanoBIO

In its original formulation due to Feynman almost six decades back, nanotechnology began around a simple but powerful vision of a device engineered to write the entire Encyclopedia Britannica on the head of a pin. Nanotechnology now is a multidisciplinary field where devices are designed for applications in a diverse array of fields such as electronics, medicine, and energy using principles from engineering, physics, materials science, chemistry, computing, and biology. The safe and successful application of nanotechnology in the biological realm demands an advance in the original vision of Feynman due to the inherent multiscale nature of biology. Engineering of these nanoBIO devices must be based on the knowledge of how nanotechnology-based devices interact with biological systems at the protein, cell, tissue, and organ levels. The Engineered nanoBIO node at Indiana University (IU) will develop a powerful set of integrated computational nanotechnology tools that address this complex, multiscale problem and facilitate the discovery of customized, efficient, and safe nanoscale devices for biological applications. These computational tools will be tested and validated experimentally, and they will be integrated with IU's key cyberinfrastructure strengths in high-performance computing and scalable data-analysis platforms. They will meet critical national health needs as they find applications in nanomedicine by significantly enhancing the targeting and imaging capabilities of engineered nanoparticles, thus increasing our ability to generate new life-saving medicines for cancer treatment.  The node will engage several groups at IU, including: the Department of Intelligent Systems Engineering (ISE), the Biocomplexity Institute, the Department of Chemistry, the Pervasive Technology Institute (PTI), and the Digital Science Center. It will integrate advanced parallel computing middleware with the Network for Computational Nanotechnology Cyber Platform (nanoHUB). The node will be headquartered at the ISE, a department that is uniquely positioned to make nanoHUB the place for collaborative interactions of the interdisciplinary nanoBIO community and training of students in nanoengineering and bioengineering focused subjects. The node will interact with Science Gateways Community Institute in a broad outreach program targeting under-represented communities through workshops and workforce development forums. Nanomaterials-based devices offer unprecedented opportunities for the targeting, imaging, and manipulation of biological systems and have the potential to revolutionize the diagnosis and treatment of many diseases including cancer. However, this excitement about the potential of nanotechnology in the biomedical field is tempered by concerns about the outcomes of the interactions between engineered nanomaterials and biological systems, because we lack a sufficient fundamental understanding to link intrinsic nanoparticle features and incubation conditions to nanoparticle assembly and transport, single-cell and multicellular behavior, and ultimately therapeutic response. The Engineered nanoBIO node at Indiana University will address this complex problem by developing new nanoscience modeling and computational tools that span a wide range of biologically relevant length and time scales. The node aims to create computational tools designed for cutting-edge research to develop biocompatible, safe, and efficient nanoscale devices. The node plans to contribute tools that: 1) design functional nanoparticles and self-assembled nanostructures with user-selected physicochemical, mechanical, and biocompatible properties, 2) evaluate and control nanodevice-cell interactions and establish nanodevice-cell phenotype links, and 3) enable the engineering of multicellular systems using the nanoscale design elements and the nanodevice-cell phenotype links. The tools will be open-sourced, helping to attract a global community of users employing the node's tools and a global community of developers enhancing them. By introducing enhancements to cyberinfrastructure capabilities in the Network for Computational Nanotechnology, the Engineered nanoBIO node will provide an overarching framework of integrated nanoBIO tools that will empower researchers to investigate macroscale biotransport and cell phenotype response to tweaks in the design of nanodevices. This will enable the development of metrics for nanodevice safety, intracellular stability, and nanodevice-based detection, imaging, and drug-delivery capabilities.

在其最初的配方由于费曼近60年前，纳米技术开始围绕一个简单但强大的愿景设计的设备写在一个针头上的整个大英百科全书。纳米技术现在是一个多学科领域，其中设备被设计用于各种领域的应用，例如电子，医学和能源，使用工程，物理，材料科学，化学，计算和生物学的原理。纳米技术在生物学领域的安全和成功的应用需要在费曼的原始愿景的进步，由于生物学固有的多尺度性质。这些nanoBIO设备的工程必须基于纳米技术设备如何在蛋白质，细胞，组织和器官水平上与生物系统相互作用的知识。印第安纳州大学（IU）的工程nanoBIO节点将开发一套强大的集成计算纳米技术工具，以解决这一复杂的多尺度问题，并促进发现用于生物应用的定制，高效和安全的纳米级器件。这些计算工具将通过实验进行测试和验证，并将与IU在高性能计算和可扩展数据分析平台方面的关键网络基础设施优势相结合。它们将满足关键的国家健康需求，因为它们通过显着增强工程纳米粒子的靶向和成像能力而在纳米医学中找到应用，从而提高我们为癌症治疗生产新的救生药物的能力。 该节点将参与IU的几个小组，包括：智能系统工程系（伊势），生物复杂性研究所，化学系，普适技术研究所（PTI）和数字科学中心。它将把先进的并行计算中间件与计算纳米技术网络平台网络（nanoHUB）集成在一起。该节点将总部设在伊势，一个独特的定位，使nanoHUB的地方跨学科nanoBIO社区的协作互动和培训学生在纳米工程和生物工程为重点的科目部门。该节点将通过研讨会和劳动力发展论坛与科学门户社区研究所进行广泛的外展计划，针对代表性不足的社区进行互动。基于纳米材料的设备为生物系统的靶向，成像和操纵提供了前所未有的机会，并有可能彻底改变包括癌症在内的许多疾病的诊断和治疗。然而，这种兴奋的纳米技术在生物医学领域的潜力是缓和的工程纳米材料和生物系统之间的相互作用的结果的关注，因为我们缺乏足够的基本理解链接内在的纳米粒子的功能和孵育条件的纳米粒子组装和运输，单细胞和多细胞的行为，并最终治疗反应。印第安纳州大学的工程纳米生物学节点将通过开发新的纳米科学建模和计算工具来解决这个复杂的问题，这些工具涵盖了广泛的生物学相关长度和时间尺度。该节点旨在创建为尖端研究设计的计算工具，以开发生物相容性，安全和高效的纳米级设备。该节点计划贡献工具：1）设计功能性纳米颗粒和自组装纳米结构，具有用户选择的物理化学，机械和生物相容性特性，2）评估和控制纳米器件-细胞相互作用并建立纳米器件-细胞表型链接，以及3）使用纳米级设计元素和纳米器件-细胞表型链接实现多细胞系统的工程设计。这些工具将是开源的，有助于吸引全球用户社区使用节点的工具，并吸引全球开发人员社区加强这些工具。通过在计算纳米技术网络中引入网络基础设施能力的增强，工程nanoBIO节点将提供一个综合nanoBIO工具的总体框架，使研究人员能够研究宏观生物运输和细胞表型对纳米器件设计调整的反应。这将使纳米器件安全性，细胞内稳定性和基于纳米器件的检测，成像和药物输送能力的指标的发展。

项目成果

Machine Learning for Performance Enhancement of Molecular Dynamics Simulations

• DOI: 10.1007/978-3-030-22741-8_9
• 发表时间: 2019-06
• 作者: J. Kadupitiya;G. Fox;V. Jadhao

Addressing barriers in comprehensiveness, accessibility, reusability, interoperability and reproducibility of computational models in systems biology.

• DOI: 10.1093/bib/bbac212
• 发表时间: 2022-07-18
• 期刊: Briefings in bioinformatics
• 影响因子: 9.5

CompuCell3D Simulations Reproduce Mesenchymal Cell Migration on Flat Substrates.

CompuCell3D 模拟再现平坦基底上的间充质细胞迁移。

• DOI: 10.1016/j.bpj.2020.04.024
• 发表时间: 2020
• 期刊: Biophysical journal
• 影响因子: 3.4
• 作者: Fortuna,Ismael;Perrone,GabrielC;Krug,MoniqueS;Susin,Eduarda;Belmonte,JulioM;Thomas,GilbertoL;Glazier,JamesA;deAlmeida,RitaMC
• 通讯作者: deAlmeida,RitaMC

Machine learning for parameter auto-tuning in molecular dynamics simulations: Efficient dynamics of ions near polarizable nanoparticles

• DOI: 10.1177/1094342019899457
• 发表时间: 2019-10
• 期刊: The International Journal of High Performance Computing Applications
• 作者: J. Kadupitiya;G. Fox;V. Jadhao

Molecular Dynamics Simulations on Cloud Computing and Machine Learning Platforms

云计算和机器学习平台上的分子动力学模拟

• DOI: 10.1109/cloud53861.2021.00101
• 发表时间: 2021
• 期刊: 2021 IEEE 14th International Conference on Cloud Computing (CLOUD
• 作者: Sharma, Prateek;Jadhao, Vikram
• 通讯作者: Jadhao, Vikram