Ab initio protein structure prediction using a combined hierarchical approach. Proteins

predict the three-dimensional structures for 13 pro-teins using a hierarchical approach. First, all pos-sible compact conformations of a protein sequence are enumerated using a highly simplified tetrahe-dral lattice model. We select a large subset of these conformations using a lattice-based scoring func-tion and build detailed all-atom models incorporat-ing predicted secondary structure. A combined all-atom knowledge-based scoring function is then used to select three smaller subsets from these all-atom models. Finally, a consensus-based distance geom-etry procedure is used to generate the best conforma-tions from each of the all-atom subsets. With this method, we are able to predict the global topology/ shape for all or a large part of the sequence for six out of the thirteen proteins. For two other proteins, the topology/shape for shorter fragments are pre-dicted. This represents a marked improvement in ab initio prediction since CASP was first instigated i