Elements: Enabling multi-resolution simulations at the interface of biology and nanotechnology with ARBD

在生物学和纳米技术的界面上，材料、物理定律和设计原理的陌生组合有望带来科学和技术的最根本性进步。将这一承诺转化为实际应用需要精确表征不熟悉的相互作用，这对现有的实验探针提出了重大挑战。该项目旨在通过为研究界提供一个强大而通用的计算框架来克服这些挑战，该框架能够准确描述中尺度生物纳米系统。该框架不是将此类系统建模为原子的集合，而是将分辨率与计算效率进行交易，从而允许将计算工作应用于需要的地方。该项目的成果将允许计算表征广泛的以前难以处理的系统，包括大型自组装DNA纳米结构，生物信息的单分子阅读系统，病毒，细胞器，甚至是小的细菌细胞。这个CSSI元素计划旨在通过将原子分辨率布朗动力学（ARBD）代码转换为通用的中尺度仿真引擎，支持多硬件平台、多节点和多GPU并行。在ARBD中实施先进的模拟方法有望大大简化专门从事纳米级传输，等离子体，DNA自组装和生物分子物理学的研究社区常见的建模和模拟任务。使用测试驱动的软件开发方法，该项目通过实现针对多种硬件类型的新并行数据结构并提供多级并行通信来转换ARBD。该项目通过支持集体变量和多副本模拟，为复杂流程的建模引入了额外的灵活性。该项目旨在通过与基于Python的力场库集成，创建详细的文档和教程，手，该奖项由NSF高级网络基础设施办公室颁发，并得到材料研究部的共同支持。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值进行评估，被认为值得支持和更广泛的影响审查标准。

At the interface of biology and nanotechnology, the unfamiliar combinations of materials, physical laws and design principles promise the most radical advancements in science and technology. Transforming this promise into practical applications requires precise characterization of the unfamiliar interactions, which presents major challenges to existing experimental probes. This project aims to overcome these challenges by providing the research community with a robust and versatile computational framework capable of accurate description of mesoscale bionano systems. Rather than modeling such systems as a collection of atoms, the framework trades resolution for computational efficiency, allowing the computational effort to be applied where it is needed. The project’s outcome will permit computational characterization of a wide range of previously intractable systems, including large self-assembled DNA nanostructures, systems for single molecule reading of biological information, viruses, organelles, and even small bacterial cells.This CSSI Elements program aims to provide a general framework for modeling systems at the interface of biology and nanotechnology by transforming the Atomic Resolution Brownian Dynamics (ARBD) code into a general-purpose mesoscale simulation engine supporting multiple hardware platforms, multi-node and multi-GPU parallelism. The implementation of advanced simulation methods in ARBD is expected to greatly simplify modeling and simulation tasks common to the research communities specializing in nanoscale transport, plasmonics, DNA self-assembly, and biomolecular physics. Using a test-driven software development approach, the project transforms ARBD by implementing new parallel data structures that target multiple hardware types and provide multiple levels of parallel communication. The project introduces additional flexibility into modelling of complex processes through its support for collective variables and multi-copy simulations. The project aims to make the ARBD framework widely accessibility through its integration with a python-based force-field library, creation of detailed documentation and tutorials, and hands-on workshops.This award by the NSF Office of Advanced Cyberinfrastructure is jointly supported by the Division of Materials 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.