title: Effective protein conformational sampling based on predicted torsion angles.
abstract: Protein structure prediction is a long-standing problem in molecular biology. Due to lack of an accurate energy function, it is often difficult to know whether the sampling algorithm or the energy function is the most important factor for failure of locating near-native conformations of proteins. This article examines the size dependence of sampling effectiveness by using a perfect "energy function": the root-mean-squared distance from the target native structure. Using protein targets up to 460 residues from critical assessment of structure prediction techniques (CASP11, 2014), we show that the accuracy of near native structures sampled is relatively independent of protein sizes but strongly depends on the errors of predicted torsion angles. Even with 40% out-of-range angle prediction, 2 Å or less near-native conformation can be sampled. The result supports that the poor energy function is one of the bottlenecks of structure prediction and predicted torsion angles are useful for overcoming the bottleneck by restricting the sampling space in the absence of a perfect energy function.
authors.affiliation: Institute for Glycomics and School of Information and Communication Technology, Griffith University, Queensland, 4222, Australia.
authors.forename: Yuedong
authors.initials: Y
authors.lastname: Yang
authors.affiliation: Institute for Glycomics and School of Information and Communication Technology, Griffith University, Queensland, 4222, Australia.
authors.forename: Yaoqi
authors.initials: Y
authors.lastname: Zhou
mesh_terms: D056004:Molecular Dynamics Simulation; D009010:Monte Carlo Method; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*
chemical_list: D011506:Proteins
keywords: conformational sampling; energy function; protein structure prediction; torsion angle prediction