Amaro Rommie E, Mulholland Adrian J
Department of Chemistry and Biochemistry, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093-0304.
Centre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol BS8 1TS, UK.
Nat Rev Chem. 2018 Apr;2(4). doi: 10.1038/s41570-018-0148. Epub 2018 Apr 11.
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 understanding of complex mechanisms and the ability to predict biological effects. Improved algorithms, ever-more-powerful computing architectures and the accelerating growth of rich datasets are driving advances in multiscale modeling 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 are now able to access 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 of the cusp of realizing long-promised impact in 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.
它将分子相互作用与细胞及更大尺度上的涌现特性联系起来。这些不同尺度上的模拟技术已经是药物设计和开发的核心，但能够跨尺度连接的方法将扩展对复杂机制的理解以及预测生物学效应的能力。改进的算法、功能越来越强大的计算架构以及丰富数据集的加速增长，正在推动多尺度建模方法的进步，这些方法能够跨越从原子到细胞的化学和生物学复杂性。特别令人兴奋的是生物化学系统高度详细的、基于结构的物理模拟的发展，现在这些模拟能够在实验相关的时间尺度上处理大型系统，同时实现前所未有的准确性。在这篇观点文章中，我们讨论新兴的、基于数据和物理的多尺度方法如何正处于在新型治疗药物的发现、设计和开发中实现长期承诺的影响的关键节点。我们强调这个不断发展的领域中的新兴方法和应用，并概述在实际建模和模拟策略中如何将不同尺度结合起来。
