Computational approaches have found great utility in areas including drug discovery and environmental contamination by investigating protein dynamics, binding and interaction patterns. For drug discovery, in silico biophysical methods serve an important role in reducing the cost of and accelerating the discovery process, as such methods aid in facilitating the identification, optimization and screening of potential drug candidates and in providing important understanding of drug mechanisms of actions and structure activity relationships at the atomic level. For computational drug discovery and protein modelling strategies, probable binding conformations of the ligand to its target can be predicted, and these conformations can be further evaluated by using scoring functions, molecular dynamics and free energy calculations to determine binding affinities and understand how a ligand recognizes its host. Despite the utility of computational approaches in areas such as drug design and the study of protein functioning, the choice of methods is not straightforward. Because of this, a series of international blinded host-guest binding prediction challenges are available to identify the most effective approaches to predict a variety of properties. Some of the methods available for calculating free energies include free energy perturbation, replica exchange free energy perturbation and thermodynamic integration approaches, and end-state methods. The later are most promising due to their reduced computational cost and because there is no need for intermediate state simulation.
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