Hierarchical energy-based approach to protein-structure prediction: Blind-test evaluation with CASP3 targets

A hierarchical approach based exclusively on finding the global minimum of an appropriate potential energy function, without the aid of secondary structure prediction, multiple-sequence alignment, or threading, is proposed. The procedure starts from an extensive search of the conformational space of a protein, using our recently developed united-residue off-lattice UNRES force field and the conformational space annealing (CSA) method. The structures obtained in the search are clustered into families and ranked according to their UNRES energy. Structures within a preassigned energy cutoff are gradually converted into an all-atom representation, followed by a limited conformational search at the all-atom level, using the electrostatically driven Monte Carlo (EDMC) method and the ECEPP/3 force field including hydration. The approach was tested (in the CASP3 experiment) in blind predictions on seven targets, five of which were globular proteins with sizes ranging from 89 to 140 amino acid residues. Comparison of the computed lowest-energy structures, with the experimental structures, made available after the predictions were submitted, shows that large fragments (∼60 residues, representing 45–80% of the proteins) of those five globular proteins were predicted with the root mean square deviations (RMSDs) ranging from 4 to 7 Å for the Cα atoms, with correct secondary structure and topology. These results constitute an important step toward the prediction of protein structure based solely on global optimization of a potential energy function for a given amino acid sequence.