title: 3dRNAscore: a distance and torsion angle dependent evaluation function of 3D RNA structures.
abstract: Model evaluation is a necessary step for better prediction and design of 3D RNA structures. For proteins, this has been widely studied and the knowledge-based statistical potential has been proved to be one of effective ways to solve this problem. Currently, a few knowledge-based statistical potentials have also been proposed to evaluate predicted models of RNA tertiary structures. The benchmark tests showed that they can identify the native structures effectively but further improvements are needed to identify near-native structures and those with non-canonical base pairs. Here, we present a novel knowledge-based potential, 3dRNAscore, which combines distance-dependent and dihedral-dependent energies. The benchmarks on different testing datasets all show that 3dRNAscore are more efficient than existing evaluation methods in recognizing native state from a pool of near-native states of RNAs as well as in ranking near-native states of RNA models.
authors.affiliation: Biomolecular Physics and Modeling Group, Department of Physics and Key Laboratory of Molecular Biophysics of the Ministry of Education, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China.
authors.forename: Jian
authors.initials: J
authors.lastname: Wang
authors.affiliation: Biomolecular Physics and Modeling Group, Department of Physics and Key Laboratory of Molecular Biophysics of the Ministry of Education, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China.
authors.forename: Yunjie
authors.initials: Y
authors.lastname: Zhao
authors.affiliation: Biomolecular Physics and Modeling Group, Department of Physics and Key Laboratory of Molecular Biophysics of the Ministry of Education, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China.
authors.forename: Chunyan
authors.initials: C
authors.lastname: Zhu
authors.affiliation: Biomolecular Physics and Modeling Group, Department of Physics and Key Laboratory of Molecular Biophysics of the Ministry of Education, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China yxiao@mail.hust.edu.cn.
authors.forename: Yi
authors.initials: Y
authors.lastname: Xiao
mesh_terms: D003627:Data Interpretation, Statistical; D008958:Models, Molecular; D009690:Nucleic Acid Conformation; D012313:RNA / Q000737:chemistry*; D054159:Torsion, Mechanical
chemical_list: D012313:RNA