SPSSM8: an accurate approach for predicting eight-state secondary structures of proteins.
Protein eight-state secondary structure prediction is challenging, but is necessary to determine protein structure and function. Here, we report the development of a novel approach, SPSSM8, to predict eight-state secondary structures of proteins accurately from sequences based on the structural position-specific scoring matrix (SPSSM). The SPSSM has been successfully utilized to predict three-state secondary structures. Now we employ an eight-state SPSSM as a feature that is obtained from sequence structure alignment against a large database of 9 million sequences with putative structural information. The SPSSM8 uses a low sequence identity dataset (9062 entries) as a training set and conditional random field for the classification algorithm. The SPSSM8 achieved an average eight-state secondary structure accuracy (Q8) of 71.7% (Q3, 81.6%) for an independent testing set (463 entries), which had an improved accuracy of 10.1% and 4.6% compared with SSPro8 and CNF, respectively, and significantly improved the accuracy of eight-state secondary structure prediction. For CASP 9 dataset (92 entries) the SPSSM8 achieved a Q8 accuracy of 80.1% (Q3, 83.0%). The SPSSM8 was confirmed as an outstanding predictor for eight-state secondary structures of proteins. SPSSM8 is freely available at http://cal.tongji.edu.cn/SPSSM8.
Department of Chemistry, Tongji University, Shanghai, PR China. Electronic address: pshcong@tongji.edu.cn.
Peisheng
P
Cong
Dapeng
D
Li
Zhiheng
Z
Wang
Shengnan
S
Tang
Tonghua
T
Li
D000595:Amino Acid Sequence; D030562:Databases, Protein; D056510:Position-Specific Scoring Matrices; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*; D016415:Sequence Alignment
D011506:Proteins
8-State secondary structure; 9M-BLAST; CRF; PSI-BLAST; SPSSM