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Statistical torsion angle potential energy functions for protein structure modeling: A bicubic interpolation approach
Authors:Tae‐Rae Kim  Joshua SungWoo Yang  Seokmin Shin  Jinhyuk Lee
Institution:1. Department of Chemistry, Seoul National University, , Seoul 151‐747, Republic of Korea;2. Korean Bioinformation Center (KOBIC), Korea Research Institute of Bioscience and Biotechnology, , Yuseong‐gu, Daejeon 305‐806, Republic of Korea;3. Department of Bioinformatics, University of Science and Technology, , Yuseong‐Gu, Daejeon 305‐350, Republic of Korea
Abstract:A set of grid type knowledge‐based energy functions is introduced for ?χ1, ψχ1, ?ψ, and χ1χ2 torsion angle combinations. Boltzmann distribution is assumed for the torsion angle populations from protein X‐ray structures, and the functions are named as statistical torsion angle potential energy functions. The grid points around periodic boundaries are duplicated to force periodicity, and the remedy relieves the derivative discontinuity problem. The devised functions rapidly improve the quality of model structures. The potential bias in the functions and the usefulness of additional secondary structure information are also investigated. The proposed guiding functions are expected to facilitate protein structure modeling, such as protein structure prediction, protein design, and structure refinement. Proteins 2013. Proteins 2013; 81:1156–1165. © 2013 Wiley Periodicals, Inc.
Keywords:torsion angle  statistical potential  structure modeling  bicubic interpolation
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