Coarse grained modeling

Coarse-grained modeling, coarse-grained models, aim at simulating the behaviour of complex systems using their coarse-grained (simplified) representation. Coarse-grained models are widely used for molecular modeling of biomolecules at various granularity levels. A wide range of coarse-grained models have been proposed. They are usually dedicated to computational modeling of specific molecules: proteins, nucleic acids, lipid membranes, carbohydrates or water. In these models, molecules are represented by individual atoms and pseudo-atoms (that replace the group of atoms), or pseudo-atoms only. By decreasing the degrees of freedom much longer simulation times can be studied than using classical atomistic models. Coarse-grained models have found practical applications in: protein structure prediction, prediction of protein interactions and molecular dynamics simulations of protein folding.

In 2013, the Nobel Prize in Chemistry has been awarded “for the development of multiscale models for complex chemical systems” to Michael Levitt, Ariel Warshel, and Martin Karplus. Their early works on coarse-grained protein modeling have been recognized by the Nobel Prize Committee as an important step in studies of large macromolecular systems. Coarse-grained models are presently often used as components of multiscale modeling protocols in combination with atomistic resolution models. Atomistic resolution models alone are presently not efficient enough to handle large system sizes and simulation timescales.