Multiscale methods in drug design bridge chemical and biological complexity in the search for cures

Abstract

| 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.