Molecular dynamics (MD) simulations enable the study of molecular-scale behavior that is often challenging or impossible to observe experimentally. While all-atom simulations can accurately describe the microscopic features of molecular interactions, they are often unable to access the time and length scales needed to model many phenomena of fundamental and technological interest, particularly for macromolecular systems commonly encountered in biology and materials science. A solution to this problem is to use coarse-grained (CG) molecular simulations, in which groups of atoms are mapped onto a smaller set of CG particles, which can speed up simulations by orders of magnitude. CG simulations using isotropic (spherical) particles have been used to study large biomolecular and synthetic polymer systems with reasonable accuracy. Isotropic-particle CG models predominate due to their simplicity and widely developed CG parametrization methods. However, isotropic CG models may not always provide the most accurate, efficient, or physically transparent CG description of system properties. For molecules consisting of large, rigid, anisotropic fragments, which includes important classes of molecules such as nucleic acids, liquid crystals, and organic semiconductors (due to their extended π-conjugation), anisotropic-particle CG models can more accurately represent the shape and interaction anisotropy using a smaller number of CG particles. This potentially increases simulation speed compared with the use of isotropic CG particles for a given level of accuracy. The speedup benefits from anisotropic coarse-graining are expected to be most evident as molecular size and anisotropy increases, enabling an increased relative degree of coarse-graining while accurately capturing molecular anisotropy compared with coarsegraining using isotropic particles, which can compensate for the greater computational demands per particle of simulating anisotropic particles compared with isotropic ones. The smaller number of CG variables for an anisotropic CG model compared with an isotropic CG model of equivalent accuracy or fidelity can also enable more straightforward interpretation or prediction of system properties, particularly those related to the orientation of anisotropic molecules. This is the case for organic semiconductors, for which molecular ordering and alignment at the material interfaces play crucial roles in determining the performance of organic electronic devices such as solar cells, light-emitting diodes and transistors. . Implementation of MD simulations of anisotropic CG models is facili-tated by well-established analytical non-bonded pair potentials, with the most commonly used being the Gay-Berne and RE-squared potentials for ellipsoidal particles. Advantages of using anisotropic CG models have been demonstrated in recent approaches to simulate organic material systems, in which both large-scale conformational properties and small-scale anisotropic molecular arrangements were obtained.