Accurate simulation of protein–ligand interactions remains a central challenge in drug discovery. Coarse-grained (CG) molecular dynamics offers a route to broader system coverage and efficient sampling by reducing molecular resolution. Here, we examine the potential of Martini 3 for drug discovery, reviewing methodological advances in simulation setup and addressing persistent challenges in sampling, model parameterization, and the reliable estimation of binding thermodynamics. Finally, we discuss priorities for translating CG simulations into robust, scalable drug discovery workflows.
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Grazzi et al. (2026) studied this question.
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