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

在生物学和纳米技术的交界处，材料、物理定律和设计原则的陌生组合预示着科学和技术的最根本进步。要将这一前景转化为实际应用，需要精确描述不熟悉的相互作用，这对现有的实验探测器提出了重大挑战。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，该框架能够准确地描述中尺度生物纳米系统。该框架不是将这样的系统建模为原子的集合，而是以分辨率换取计算效率，允许在需要的地方应用计算努力。该项目的成果将允许对一系列以前难以处理的系统进行计算表征，包括大型自组装DNA纳米结构、用于读取生物信息的单分子系统、病毒、细胞器，甚至是小型细菌细胞。该CSSI Elements程序旨在通过将原子分辨率布朗动力学(ARBD)代码转换为支持多硬件平台、多节点和多GPU并行的通用中尺度模拟引擎，为生物和纳米技术接口的系统建模提供通用框架。ARBD中先进模拟方法的实施有望极大地简化纳米尺度传输、等离子体、DNA自组装和生物分子物理等研究领域常见的建模和模拟任务。使用测试驱动的软件开发方法，该项目通过实现新的并行数据结构来转换ARBD，这些结构针对多种硬件类型并提供多个级别的并行通信。该项目通过支持集合变量和多副本模拟，为复杂过程的建模带来了额外的灵活性。该项目旨在通过与基于蟒蛇的力场库的集成，创建详细的文档和教程，以及动手工作室，使ARBD框架变得广泛可用。该奖项由NSF高级网络基础设施办公室联合支持材料研究部。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。

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.