Prediction, modeling, and refinement of protein structure

Abstract: Accurate predictions of protein structure are important for understanding many processes in cells. The interactions that govern protein folding and structure are complex, and still far from completely understood. However, progress is being made in many areas. Here, efforts to improve the overall quality of protein structure models are described. From a pure evolutionary perspective, in which proteins are viewed in the light of gradually accumulated mutations on the sequence level, it is shown how information from multiple sources helps to create more accurate models. A very simple but surprisingly accurate method for assigning confidence measures for protein structures is also tested. In contrast to models based on evolution, physics based methods view protein structures as the result of physical interactions between atoms. Newly implemented methods are described that both increase the time-scales accessible for molecular dynamics simulations almost 10-fold, and that to some extent might be able to refine protein structures. Finally, I compare the efficiency and properties of different techniques for protein structure refinement.