Model quality assessment for membrane proteins is an important problem in biological field. There are some successful experimental methods for discriminating between high- and low- quality protein structure, such as X-ray crystallography, NMR spectroscopy and 3D EM etc.. In this paper, we would like to deal with this problem from a mathematical point-of-view. In recent years, a variety of nonlinear dimension reduction methods have been proposed to deal with high-dimensional data. The data set we are going to use in this paper is a high-dimensional data, which is very complex with nonlinear properties. We try to assess the local model quality using these nonlinear algorithms. The performances of the nonlinear techniques on this problem are investigated. The paper also analyzed the experimental results and suggests how the performance of nonlinear dimension reduction algorithms may be improved.