Element: Computational Toolkit to Discover Peptides that Self-assemble into User-selected Structures

肽是自然产生的氨基酸的短链(序列)。它们存在于所有活的细胞和组织中，在那里它们发挥着重要的生物学功能。多肽现在正被考虑用于纳米技术，因为它们能够组装成各种纳米结构-纳米纤维、纳米片材和纳米颗粒。这种结构在医学、电子学、酶催化和药物释放等领域具有潜在的应用前景。该项目的目标是开发一种开放的软件工具包，能够识别能够组装成用户选择的纤维状结构的多肽序列。用户将能够筛选可能数以千计的肽序列，这些序列组装成他们选择的纳米结构，并根据它们的稳定性进行排序。将开发一种名为PepAD(多肽组装设计)的算法，该算法搜索组装成用户指定结构的序列。随附的软件包将允许进一步分析大量这些肽序列形成所需结构的相对速度。为了确定有效性和未来改进计算工具的基础，选定的设计将使用先进的生物物理表征技术和固态核磁共振光谱进行实验验证。PepAD将是开源的，易于运行。开发者以及科学界和工程界成员对它的使用应该会导致设计下一代复杂纳米结构的能力。该工具包将是第一个用于此类组装的工具包，将在GitHub和NSF赞助的分子模拟和设计框架(MoSDeF)上提供。众所周知，许多多肽采用β链构象并自发组装成各种纳米结构--纳米纤维、纳米片材、纳米颗粒等--在包括纳米医学、电子学、药物释放和水凝胶在内的广泛领域中应用。该项目的目标是开发一种开放的软件工具包，能够识别能够组装成用户选择的基于测试片的结构的多肽序列。将开发一种名为PepAD(多肽组装设计)的算法，该算法搜索组装成用户指定的结构的序列。PepAD将允许用户筛选可能数以千计的肽序列，这些序列自发组装成他们选择的结构，并根据它们的稳定性进行排序。非连续分子动力学(DMD)模拟软件以及PRIME20力场也将可用于分析所设计的结构？装配动力学。为了确定有效性和未来改进计算工具的基础，选定的设计将使用生物物理表征技术和固态核磁共振(ss核磁共振)光谱进行实验验证。该项目有四个目标：(1)开发算法PepAD，确定能够自组装成用户确定的淀粉样结构的短肽序列；(2)执行DMD/PRIME20模拟以检查组装动力学，(3)使用生物物理表征实验和ss核磁共振合成和测试肽设计，以及(4)社区测试和优化PepAD软件，然后将其作为插件安装在GitHub和MoSDeF上。该工具包将是第一个用于测试表程序集的工具包，它将是开源的，易于使用。该软件的成功实施将为自组装纳米结构的计算设计铺平道路：(A)响应触发，如温度、pH或特定离子的变化，以及(B)当多肽与小分子、识别元件、荧光团或酶等功能结合时。推广活动包括为普通观众制作一段视频，描述如何将分子水平的计算机模拟用于新材料的设计，以及一款iPad应用程序，允许用户通过计算设计蛋白质模型，然后观看蛋白质折叠时的电影。该项目将利用自我组装的概念和相关想法来设计针对本科生的STEM教育活动。该项目将致力于扩大妇女和少数民族的机会，并提高K-12学生的科学意识。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Peptides are short chains (sequences) of naturally-occurring amino acids. They are found in all living cells and tissues, where they perform vital biological functions. Peptides are now being considered for use in nanotechnology as they are able to assemble to form a variety of nanostructures - nanofibers, nanosheets, and nanoparticles. Such structures have potential applications in a wide variety of fields including medicine, electronics, enzyme catalysis and drug release. The goal of this project is to develop an open software toolkit that enables the identification of peptide sequences that are capable of assembling into user-selected fiber-like structures. Users will be able to screen potentially thousands of peptide sequences that assemble into the nanostructure of their choosing, and rank order them according to their stability. An algorithm, PepAD (Peptide Assembly Design) will be developed that searches for sequences that assemble into structures specified by the user. An accompanying software package will allow further analysis of the relative speed at which a large number of these peptide sequences form the desired structure. To establish efficacy and a basis for future improvement of computational tools, selected designs will be validated experimentally using advanced biophysical characterization techniques and solid-state nuclear magnetic resonance spectroscopy. PepAD will be open source and easy to run. Its use by the developers and by members of the scientific and engineering communities should lead to the ability to design the next generation of complex nanostructures. The toolkit, which will be the first of its kind for these types of assemblies, will be available on GitHub and on the NSF-sponsored Molecular Simulation and Design Framework (MoSDeF).Many peptides are known to adopt beta strand conformations and assemble spontaneously into a variety of nanostructures--- nanofibers, nanosheets, nanoparticles, etc. - with applications in a wide variety of fields including nanomedicine, electronics, drug release, and hydrogels. The goal of this project is to develop an open software toolkit that enables the identification of peptide sequences that are capable of assembling into user-selected beta-sheet-based structures. An algorithm, PepAD (Peptide Assembly Design) will be developed that searches for sequences that assemble into structurers specified by the user. PepAD will allow users to screen potentially thousands of peptide sequences that assemble spontaneously into the structure of their choosing, and rank order them according to their stability. Discontinuous molecular dynamics (DMD) simulation software along with the PRIME20 force field will also be made available to enable analysis of the designed structures? assembly kinetics. To establish efficacy and a basis for future improvement of computational tools, selected designs will be validated experimentally using biophysical characterization techniques and solid-state nuclear magnetic resonance (ssNMR) spectroscopy. There are four objectives: (1) develop an algorithm, PepAD, that identifies short peptide sequences that are capable of self-assembling into user-determined amyloid structures; (2) perform DMD/PRIME20 simulations to examine assembly kinetics, (3) synthesize and test the peptide designs using biophysical characterization experiments and ssNMR, and (4) community test and refine the PepAD software and then install it on GitHub and on MoSDeF as a plugin. The toolkit, which will be the first of its kind for beta-sheet assemblies, will be open source and easy to use. Successful implementation of this software will pave the way for the computational design of nanostructures that self-assemble: (a) in response to a trigger such as a change in temperature, pH, or specific ions, and (b) when the peptides are conjugated to functionalities like small molecules, recognition elements, fluorophores or enzymes. Outreach activities include the creation of a video for general audiences that describes how molecular-level computer simulations can be used in the design of new materials and an iPad app that allows users to computationally design model proteins and then watch movies of them as they fold. The project will use the concept of harnessing self-assembly and related ideas to design educational activities for undergraduate STEM students. The project will work to broaden opportunities for women and minorities, and to increase science awareness in K-12 students.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.