Template-based C8-SCORPION: a protein 8-state secondary structure prediction method using structural information and context-based features

Ashraf Yaseen1, Yaohang Li1
1Department of Computer Science, Old Dominion University, Norfolk, VA, 23529, USA

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Rost B: Review:Protein secondary structure prediction continues to rise. J Struct Biol. 2001, 134 (2-3): 204-218. 10.1006/jsbi.2001.4336.

Garnier J, Gibrat JF, Robson B: GOR method for predicting protein secondary structure from amino acid sequence. Methods Enzymol. 1996, 266: 540-553.

Jones DT: Protein secondary structure prediction based on position-specific scoring matrices. J Mol Biol. 1999, 292 (2): 195-202. 10.1006/jmbi.1999.3091.

Rost B, Sander C: Combining evolutionary information and neural networks to predict protein secondary structure. Proteins. 1994, 19 (1): 55-72. 10.1002/prot.340190108.

Karplus K, Barrett C, Cline M, Diekhans M, Grate L, Hughey R: Predicting protein structure using only sequence information. Proteins-Structure Function and Genetics. 1999, Suppl 1: 121-125.

Pollastri G, McLysaght A: Porter: a new, accurate server for protein secondary structure prediction. Bioinformatics. 2005, 21 (8): 1719-1720. 10.1093/bioinformatics/bti203.

Cole C, Barber JD, Barton GJ: The Jpred 3 secondary structure prediction server. Nucleic Acids Res. 2008, 36: W197-W201. 10.1093/nar/gkn238.

Dor O, Zhou YQ: Achieving 80% ten-fold cross-validated accuracy for secondary structure prediction by large-scale training. Proteins. 2007, 66 (4): 838-845.

Pollastri G, Przybylski D, Rost B, Baldi P: Improving the prediction of protein secondary structure in three and eight classes using recurrent neural networks and profiles. Proteins-Structure Function and Genetics. 2002, 47 (2): 228-235. 10.1002/prot.10082.

Petersen B, Petersen TN, Andersen P, Nielsen M, Lundegaard C: A generic method for assignment of reliability scores applied to solvent accessibility predictions. Bmc Struct Biol. 2009, 9 (51): 10.1186/1472-6807-9-51.

Kabsch W, Sander C: Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers. 1983, 22 (12): 2577-2637. 10.1002/bip.360221211.

Ramachandran GN, Sasisekharan V: Conformation of polypeptides and proteins. Advances in protein chemistry. 1968, 23: 283-438.

Topf M, Baker ML, Marti-Renom MA, Chiu W, Sali A: Refinement of protein structures by iterative comparative modeling and CryoEM density fitting. J Mol Biol. 2006, 357 (5): 1655-1668. 10.1016/j.jmb.2006.01.062.

Wang ZY, Zhao F, Peng J, Xu JB: Protein 8-class secondary structure prediction using conditional neural fields. Proteomics. 2011, 11 (19): 3786-3792. 10.1002/pmic.201100196.

Montgomerie S, Sundararaj S, Gallin WJ, Wishart DS: Improving the accuracy of protein secondary structure prediction using structural alignment. Bmc Bioinformatics. 2006, 7:

Pollastri G, Martin AJM, Mooney C, Vullo A: Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure information. BMC Bioinformatics. 2007, 8:

Wang GL, Dunbrack RL: PISCES:a protein sequence culling server. Bioinformatics. 2003, 19 (12): 1589-1591. 10.1093/bioinformatics/btg224.

Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ: Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997, 25 (17): 3389-3402. 10.1093/nar/25.17.3389.

Cuff JA, Barton GJ: Application of multiple sequence alignment profiles to improve protein secondary structure prediction. Proteins-Structure Function and Genetics. 2000, 40 (3): 502-511. 10.1002/1097-0134(20000815)40:3<502::AID-PROT170>3.0.CO;2-Q.

Ahmad S, Gromiha MM, Sarai A: Real value prediction of solvent accessibility from amino acid sequence. Proteins-Structure Function and Genetics. 2003, 50 (4): 629-635. 10.1002/prot.10328.

Carugo O: Predicting residue solvent accessibility from protein sequence by considering the sequence environment. Protein Engineering. 2000, 13 (9): 607-609. 10.1093/protein/13.9.607.

Kinch LN, Shi S, Cheng H, Cong Q, Pei JM, Mariani V, Schwede T, Grishin NV: CASP9 target classification. Proteins. 2011, 79: 21-36. 10.1002/prot.23190.

Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE: The Protein Data Bank. Nucleic Acids Res. 2000, 28 (1): 235-242. 10.1093/nar/28.1.235.

Li Y, Liu H, Rata I, Jakobsson E: Building a Knowledge-Based Statistical Potential by Capturing High-Order Inter-residue Interactions and its Applications in Protein Secondary Structure Assessment. Journal of chemical information and modeling. 2013, 53 (2): 500-508. 10.1021/ci300207x.

Sippl MJ: Calculation of Conformational Ensembles from Potentials of Mean Force - an Approach to the Knowledge-Based Prediction of Local Structures in Globular-Proteins. J Mol Biol. 1990, 213 (4): 859-883. 10.1016/S0022-2836(05)80269-4.

Zemla A, Venclovas C, Fidelis K, Rost B: A modified definition of Sov, a segment-based measure for protein secondary structure prediction assessment. Proteins-Structure Function and Genetics. 1999, 34 (2): 220-223. 10.1002/(SICI)1097-0134(19990201)34:2<220::AID-PROT7>3.0.CO;2-K.

Rata I, Li Y, Jakobsson E: Backbone Statistical Potential from Local Sequence-Structure Interactions in Protein Loops. Journal of Physical Chemistry B. 2010, 114 (5): 1859-1869. 10.1021/jp909874g.

Samudrala R, Moult J: An all-atom distance-dependent conditional probability discriminatory function for protein structure prediction. Journal of Molecular Biology. 1998, 275: 895-916. 10.1006/jmbi.1997.1479.