Most protein model refinement protocols are based on a combination of conformational sampling from an initial model for refinement with a scheme for deriving an improved structure from the sampled conformations. Therefore, effective conformational sampling is one of the key parts for successful refinement. Some previously proposed protocols have used Monte Carlo minimization with structure perturbation operations and followed relaxation using MD simulations. Global optimization methods, such as genetic algorithm and conformational space annealing, have also been adopted in a few protocols. Most recently, MD simulations have become a popular choice for conformational sampling during refinement. MD simulations have had success by reaching the native state of smaller proteins via in silico protein folding simulations that started from extended states. Therefore, using such simulations to reach the native state from an initial model that is already close to the native state has been an obvious choice.