Background: A principal goal of structure prediction is the elucidation of function. We have studied the ability of computed models to preserve the microenvironments of functional sites. In particular, we analyzed 653 model structures (generated using an ab initio folding protocol) of a calcium binding protein, and assessed the degree to which calcium binding sites were recognizable. Results: While some model structures preserve the calcium binding microenvironments, many others, including some with low root-mean-squared deviation (RMSD), do not. There is very weak correlation between the overall RMSD of a structure and the preservation of calcium binding sites. Only when the quality of the model structure is high (local RMSD less than 2 Angstroms) does the modeling of the binding sites become reliable. Conclusions: Protein structure prediction methods need to be assessed in terms of their preservation of functional sites. High-resolution structures are necessary for identifying binding sites such as calcium binding sites.
