The Martini model is a coarse-grained force field used for biomolecular simulations, developed by the Marrink and Tieleman groups. It combines speed and versatility while maintaining chemical specificity. The model uses a four-to-one mapping, representing four heavy atoms as a single interaction center. It has been applied to a wide range of biomolecules, including lipids, peptides, proteins, and carbohydrates. The model's non-bonded interactions are described by the Lennard-Jones potential, with parameters derived from experimental data. Bonded interactions include harmonic bond and angle potentials, and multimodal dihedral potentials. The model has been validated against experimental data and atomistic simulations, showing good agreement in many cases. The Martini model has been used to study various applications, including lipid membrane characterization, lipid polymorphism, membrane protein interactions, and drug delivery systems. It has also been used to simulate membrane fusion, lipid monolayers, and surfactant self-assembly. The model has been extended to include nanoparticles, such as graphene and carbon nanotubes, and has been used to study their interactions with biological materials. Despite its successes, the Martini model has limitations, such as the inability to accurately model certain lipid-lined membrane pores and the need for further optimization in some cases. Overall, the Martini model is a powerful tool for biomolecular simulations, offering a balance between computational efficiency and chemical accuracy.The Martini model is a coarse-grained force field used for biomolecular simulations, developed by the Marrink and Tieleman groups. It combines speed and versatility while maintaining chemical specificity. The model uses a four-to-one mapping, representing four heavy atoms as a single interaction center. It has been applied to a wide range of biomolecules, including lipids, peptides, proteins, and carbohydrates. The model's non-bonded interactions are described by the Lennard-Jones potential, with parameters derived from experimental data. Bonded interactions include harmonic bond and angle potentials, and multimodal dihedral potentials. The model has been validated against experimental data and atomistic simulations, showing good agreement in many cases. The Martini model has been used to study various applications, including lipid membrane characterization, lipid polymorphism, membrane protein interactions, and drug delivery systems. It has also been used to simulate membrane fusion, lipid monolayers, and surfactant self-assembly. The model has been extended to include nanoparticles, such as graphene and carbon nanotubes, and has been used to study their interactions with biological materials. Despite its successes, the Martini model has limitations, such as the inability to accurately model certain lipid-lined membrane pores and the need for further optimization in some cases. Overall, the Martini model is a powerful tool for biomolecular simulations, offering a balance between computational efficiency and chemical accuracy.