The intrinsic dynamics of macromolecules is an essential property to relate the structure of biomolecular systems with their function in the cell. In the field of ligand-receptor recognition, numerous evidences have revealed the limitations of the lock-and-key theory, and the need to elaborate models that take into account the inherent plasticity of biomolecules, such as the induced-fit model or the existence of an ensemble of pre-equilibrated conformations. Depending on the nature of the target system, ligand binding can be associated with small local adjustments in side chains or even the backbone to large-scale motions of structural fragments, domains or even subunits. Reproducing the inherent flexibility of biomolecules has thus become one of the most challenging issues in molecular modeling and simulation studies, as it has direct implications in our understanding of the structure-function relationships, but even in areas such as virtual screening and structure-based drug discovery. Given the intrinsic limitation of conventional simulation tools, only events occurring in short time scales can be reproduced at a high accuracy level through all-atom techniques such as Molecular Dynamics simulations. However, larger structural rearrangements demand the use of enhanced sampling methods relying on modified descriptions of the biomolecular system or the potential surface. This review illustrates the crucial role that structural plasticity plays in mediating ligand recognition through representative examples. In addition, it discusses some of the most powerful computational tools developed to characterize the conformational flexibility in ligand-receptor complexes.
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