Drug action is inherently multiscale: it connects molecular interactions to emergent properties at cellular and larger scales. Simulation techniques at each of these different scales are already central to drug design and development, but methods capable of connecting across these scales will extend our understanding of complex mechanisms and our ability to predict biological effects. Improved algorithms, ever-more-powerful computing architectures and the accelerating growth of rich data sets are driving advances in multiscale modelling methods capable of bridging chemical and biological complexity from the atom to the cell. Particularly exciting is the development of highly detailed, structure-based physical simulations of biochemical systems, which can now reach experimentally relevant timescales for large systems and, at the same time, achieve unprecedented accuracy. In this Perspective, we discuss how emerging data-rich, physics-based multiscale approaches are on the cusp of realizing their long-promised impact on the discovery, design and development of novel therapeutics. We highlight emerging methods and applications in this growing field and outline how different scales can be combined in practical modelling and simulation strategies.

药物作用本质上是多尺度的：它将分子相互作用与细胞和更大尺度上的新兴特性联系起来。每个不同尺度的模拟技术已经成为药物设计和开发的核心，但能够跨这些尺度连接的方法将扩展我们对复杂机制的理解和预测生物效应的能力。改进的算法、更强大的计算架构和丰富数据集的加速增长正在推动多尺度建模方法的进步，这些方法能够将化学和生物复杂性从原子连接到细胞。特别令人兴奋的是高度详细的、基于结构的生化系统物理模拟的发展，它现在可以达到大型系统的实验相关时间尺度，同时达到前所未有的精度。在本视角中，我们讨论了新兴的数据丰富、基于物理的多尺度方法如何即将实现其对新疗法的发现、设计和开发的长期承诺的影响。我们重点介绍这个不断发展的领域中的新兴方法和应用，并概述如何在实际建模和仿真策略中组合不同的尺度。