Discovery of new therapeutics is a very challenging, expensive and time-consuming process. With the number of approved drugs declining steadily, combined with increasing costs, a rational approach is needed to facilitate, expedite and streamline the drug discovery process. In silico methods are playing key roles in the discovery of a growing number of marketed drugs. The use of computational approaches, particularly molecular dynamics, in drug design is rapidly gaining momentum and acceptance as an essential part of the toolkit for modern drug discovery. From analysing atomistic details for explaining experimentally observed phenomena, to designing drugs with increased efficacy and specificity, the insight that such simulations can provide is generating new ideas and applications that have previously been unexplored. Here we discuss physics-based simulation methodologies and applications in drug design: from locating pockets to designing novel lead compounds, from small molecules to peptides. With developments in hardware, software and theory, the improved predictive abilities of in silico efforts are becoming an essential part of efficient, economic and accurate drug development strategies.