How Accurately Can We Model Protein Structures with Dihedral Angles?

Xuefeng Cui, Shuai Cheng Li, Dongbo Bu, Babak Alipanahi Ramandi, Ming Li

Abstract: Previous study shows that the same type of bond lengths and angles fit Gaussian distributions well with small standard deviations on high resolution protein structure data. The mean values of these Gaussian distributions have been widely used as ideal bond lengths and angles in bioinformatics. However, we are not aware of any research work done to evaluate how accurately we can model protein structures with dihedral angles and ideal bond lengths and angles. In this paper, we first introduce the protein structure idealization problem. Then, we develop a fast O(nm / ε) dynamic programming algorithm to find an approximately optimal idealized protein backbone structure according to our scoring function. Consequently, we demonstrate that idealized backbone structures always exist with small changes and significantly better free energy. We also apply our algorithm to refine protein pseudo-structures determined in NMR experiments.