期刊
JOURNAL OF COMPUTATIONAL BIOLOGY
卷 16, 期 1, 页码 85-103出版社
MARY ANN LIEBERT, INC
DOI: 10.1089/cmb.2008.0082
关键词
protein structure prediction; novel low resolution model; genetic algorithm
类别
资金
- Australian Research Council [DP0557303]
This paper describes a detailed investigation of a lattice-based HP (hydrophobic-hydrophilic) model for ab initio protein structure prediction (PSP). The outcome of the simplified HP lattice model has high degeneracy, which could mislead the prediction. The HPNX model was proposed to address the degeneracy problem as well as to avoid the conformational deformity with the hydrophilic (P) residues. We have experimentally shown that it is necessary to further improve the existing HPNX model. We have found and solved the critical error of another existing YhHX model. By extracting the significant features from the YhHX for the HPNX model, we have proposed a novel hHPNX model. Hybrid Genetic Algorithm (HGA) has been used to compare the predictability of these models and hHPNX outperformed other models. We preferred 3D face-centered-cube (FCC) lattice configuration to have closest resemblance to the real folded 3D protein.
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