Before revision: The protein structure reconstruction from Nuclear Magnetic Resonance (NMR) experiments heavily relies on computational algorithms , such as matrix completion (MC) . Recently, some effective low-rank matrix completion methods, like ASD and ScaledASD, have been successfully applied in image processing, which inspired us to apply them in protein structure reconstruction. Here we present an efficient method for determining protein structures from experimental NMR NOESY distances , by combining the ScaledASD algorithm with several afterwards procedures including chirality refinement, distance lower (upper) bound refinement, force field-based energy minimization (EM) and water refinement.
After revision: The protein structure reconstruction from Nuclear Magnetic Resonance (NMR) experiments heavily relies on computational algorithms , such as matrix completion (MC) . Recently, some effective low-rank matrix completion methods, like ASD and ScaledASD, have been successfully applied in image processing, which inspired us to apply the methods to reconstruct protein structures. In this paper, we present an efficient method for determining protein structures from experimental NMR NOESY distances , by combining the ScaledASD algorithm with several afterwards procedures including chirality refinement, distance lower (upper) bound refinement, force field-based energy minimization (EM) and water refinement.