WESTPA: A high-performance framework for simulating at the frontiers of biology

WESTPA：一个高性能的框架，用于模拟生物学的前沿（更新） 有一个“硅天花板”，最终限制了许多，如果不是大多数，类型的动态生物 模拟也就是说，即使是世界上最强大的计算机也无法产生足够长的时间。 模拟，无论是蛋白质的原子模型还是细胞行为的现实模型。在许多 在某些情况下，关键事件可能发生在模拟时间尺度之外-例如大的构象变化。 蛋白质的转变、药物膜渗透或细胞行为从健康到健康的转变， 病理状态。WESTPA软件包是一个强大的"元工具"-软件， 其他软件-它可以使可能的计算，否则将是不可能的， 给定计算预算，同时让研究人员继续使用模拟引擎和模型， 他们的选择WESTPA似乎是最常用的模拟“罕见事件”的平台， 不同的尺度。WESTPA通过协调多达数千个 轨迹由那些包以任何尺度原生地运行（例如，OpenMM、Amber、BioNetGen、MCell） 使用"加权集成"策略。WESTPA不仅自动并行使用 动力学引擎-但由于添加轨迹的统计过程， 除去这些，WESTPA可以在更短的时间内获得关键动力学和平衡观测值的估计。 计算时间比普通并行化所需的时间要长。该建议的目的是（i） 优化WESTPA的云计算和超级计算平台， 最先进的机器学习框架，并提高其易用性;（ii）使算法 使应用程序能够解决更具挑战性的问题;（iii）展示 WESTPA通过一系列从分子到细胞尺度的"展示"实例的有效性 使用各种动态引擎;以及（iv）继续提供个性化指导， 研究人员、用户支持、培训教程和研讨会。目标的完成将使 研究人员，他们的实验和计算合作者，以及世界各地的用户， 为多尺度生物模拟的新兴领域做出了广泛的贡献。

WESTPA: A high-performance framework for simulating at the frontiers of biology (Renewal) There is a ‘silicon ceiling’ that ultimately limits many, if not most, types of dynamical biological simulations. That is, even the world’s most powerful computers cannot generate sufficiently long simulations, whether for atomistic models of proteins or for realistic models of cell behavior. In many cases, the key events may occur beyond simulation timescales – such as large conformational transitions in proteins, drug membrane permeation, or transitions of cell behavior from healthy to pathological states. The WESTPA software package is a powerful ‘meta tool’—software that controls other software–which can make possible computations which otherwise would be impossible within a given computing budget, while letting researchers continue to use simulation engines and models of their choice. WESTPA appears to be the most commonly used platform for simulating ‘rare events’ at different scales. WESTPA controls existing dynamics engines by orchestrating up to thousands of trajectories run natively by those packages at any scale (e.g., OpenMM, Amber, BioNetGen, MCell) using a ‘weighted ensemble’ strategy. Not only does WESTPA automatically parallelize the use of dynamics engines – but because of the statistical process by which trajectories are added and removed, WESTPA can obtain estimates of key kinetic and equilibrium observables in significantly less computing time than would be required in ordinary parallelization. The aims of the proposal are (i) to optimize WESTPA for cloud computing and supercomputing platforms, engineering interoperability with state-of-the-art machine learning frameworks, and improving its ease of use; (ii) to make algorithmic advances to enable applications to ever more challenging problems; (iii) to demonstrate the effectiveness of WESTPA through a series of “showcase” examples from molecular to cellular scale using a variety of dynamics engines; and (iv) to continue offering individualized guidance to researchers, user support, training tutorials, and workshops. Completion of the aims will enable the investigators, their experimental and computational collaborators, and users throughout the world to make a wide range of contributions to the burgeoning field of biological simulation at multiple scales.