title: NMRDSP: an accurate prediction of protein shape strings from NMR chemical shifts and sequence data.
abstract: Shape string is structural sequence and is an extremely important structure representation of protein backbone conformations. Nuclear magnetic resonance chemical shifts give a strong correlation with the local protein structure, and are exploited to predict protein structures in conjunction with computational approaches. Here we demonstrate a novel approach, NMRDSP, which can accurately predict the protein shape string based on nuclear magnetic resonance chemical shifts and structural profiles obtained from sequence data. The NMRDSP uses six chemical shifts (HA, H, N, CA, CB and C) and eight elements of structure profiles as features, a non-redundant set (1,003 entries) as the training set, and a conditional random field as a classification algorithm. For an independent testing set (203 entries), we achieved an accuracy of 75.8% for S8 (the eight states accuracy) and 87.8% for S3 (the three states accuracy). This is higher than only using chemical shifts or sequence data, and confirms that the chemical shift and the structure profile are significant features for shape string prediction and their combination prominently improves the accuracy of the predictor. We have constructed the NMRDSP web server and believe it could be employed to provide a solid platform to predict other protein structures and functions. The NMRDSP web server is freely available at http://cal.tongji.edu.cn/NMRDSP/index.jsp.
authors.affiliation: Department of Chemistry, Tongji University, Shanghai, China.
authors.forename: Wusong
authors.initials: W
authors.lastname: Mao
authors.affiliation: Department of Chemistry, Tongji University, Shanghai, China.
authors.forename: Peisheng
authors.initials: P
authors.lastname: Cong
authors.affiliation: Department of Chemistry, Tongji University, Shanghai, China.
authors.forename: Zhiheng
authors.initials: Z
authors.lastname: Wang
authors.affiliation: Department of Chemistry, Tongji University, Shanghai, China.
authors.forename: Longjian
authors.initials: L
authors.lastname: Lu
authors.affiliation: Department of Chemistry, Tongji University, Shanghai, China.
authors.forename: Zhongliang
authors.initials: Z
authors.lastname: Zhu
authors.affiliation: Department of Chemistry, Tongji University, Shanghai, China.
authors.forename: Tonghua
authors.initials: T
authors.lastname: Li
mesh_terms: D000595:Amino Acid Sequence; D019295:Computational Biology / Q000379:methods*; D020407:Internet; D009682:Magnetic Resonance Spectroscopy; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*
chemical_list: D011506:Proteins