Prediction of Protein Loop Structures Using a Local Move Monte Carlo Approach and a Grid-Based Force Field Abstract: We have developed an improved local move Monte Carlo loop sampling approach for loop predictions. The method generates loop conformations based on simple moves for the torsion angles of side chains and local moves for backbone of loops. To reduce the computational costs for energy evaluations, we developed a grid-based force field to represent the protein environment and solvation effect. Simulated annealing has been used to enhance the efficiency of the local move MC loop sampling and identify low-energy loop conformations. The prediction quality is evaluated on a set of protein loops with known crystal structure that has been previously used by others to test different loop prediction methods. The results show a significant improvement of the accuracy for loop predictions comparing with other available methods on the same loop test set. The local move MC loop prediction approach developed here could be useful for improvement of the quality the loop regions in homology models, flexible protein-ligand and protein-protein docking studies.