title: Quality Assessment of Predicted Protein Models Using Energies Calculated by the Fragment Molecular Orbital Method.
abstract: Protein structure prediction directly from sequences is a very challenging problem in computational biology. One of the most successful approaches employs stochastic conformational sampling to search an empirically derived energy function landscape for the global energy minimum state. Due to the errors in the empirically derived energy function, the lowest energy conformation may not be the best model. We have evaluated the use of energy calculated by the fragment molecular orbital method (FMO energy) to assess the quality of predicted models and its ability to identify the best model among an ensemble of predicted models. The fragment molecular orbital method implemented in GAMESS was used to calculate the FMO energy of predicted models. When tested on eight protein targets, we found that the model ranking based on FMO energies is better than that based on empirically derived energies when there is sufficient diversity among these models. This model diversity can be estimated prior to the FMO energy calculations. Our result demonstrates that the FMO energy calculated by the fragment molecular orbital method is a practical and promising measure for the assessment of protein model quality and the selection of the best protein model among many generated.
authors.affiliation: Structural Bioinformatics Team, Division of Structural and Synthetic Biology, Center for Life Science Technologies, RIKEN, 1-7-22 Suehiro, Yokohama, Kanagawa 230-0045, Japan phone: +81(0)45-503-9560/fax: +81(0)45-503-9559.|Present address: Mathématiques et Informatique Appliquées de Toulouse, Unité de Recherche 875, Institut National de la Recherche Agronomique, F-31320 Castanet-Tolosan, France.
authors.forename: David
authors.initials: D
authors.lastname: Simoncini
authors.affiliation: RIKEN Research Cluster for Innovation, 2-1 Hirosawa, Wako, Saitama 351-0198 Japan phone/fax: +81(0)48-467-9477/+81(0)48-467-8503.|Department of Biomolecular Engineering, Tokyo Institute of Technology, 4259 Nagatsutacho, Midori-ku, Yokohama, Kanagawa 226-8501, Japan.|Japan Society for the Promotion of Science, Kojimachi Business Center Building, 5-3-1 Kojimachi, Chiyoda-ku, Tokyo 102-0083, Japan.
authors.forename: Hiroya
authors.initials: H
authors.lastname: Nakata
authors.affiliation: RIKEN Research Cluster for Innovation, 2-1 Hirosawa, Wako, Saitama 351-0198 Japan phone/fax: +81(0)48-467-9477/+81(0)48-467-8503.
authors.forename: Koji
authors.initials: K
authors.lastname: Ogata
authors.affiliation: RIKEN Research Cluster for Innovation, 2-1 Hirosawa, Wako, Saitama 351-0198 Japan phone/fax: +81(0)48-467-9477/+81(0)48-467-8503. snakamura@riken.jp.
authors.forename: Shinichiro
authors.initials: S
authors.lastname: Nakamura
authors.affiliation: Structural Bioinformatics Team, Division of Structural and Synthetic Biology, Center for Life Science Technologies, RIKEN, 1-7-22 Suehiro, Yokohama, Kanagawa 230-0045, Japan phone: +81(0)45-503-9560/fax: +81(0)45-503-9559. kamzhang@riken.jp.
authors.forename: Kam Yj
authors.initials: KY
authors.lastname: Zhang
mesh_terms: D008958:Models, Molecular; D011506:Proteins / Q000737:chemistry*; D013816:Thermodynamics
chemical_list: D011506:Proteins
keywords: Fragment molecular orbital; Model selection; Pair interaction energy; Quality assessment; Structure prediction