Prediction of β-turns and β-turn types by a novel bidirectional Elman-type recurrent neural network with multiple output layers (MOLEBRNN)

Gene

Volumn 422, Issue 1-2, 2008, Pages 22-29

  Kirschner, Andreas ^a   Frishman, Dmitrij ^a  

^a TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

Classification; Machine learning; Protein structure prediction; Structural bioinformatics

Indexed keywords

ACCURACY; AMINO ACID SEQUENCE; ARTICLE; ARTIFICIAL NEURAL NETWORK; CORRELATION COEFFICIENT; DATA ANALYSIS; MACHINE LEARNING; PREDICTION; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN SECONDARY STRUCTURE; PROTEIN STRUCTURE; STRUCTURAL BIOINFORMATICS; VALIDATION PROCESS;

ALGORITHMS; NEURAL NETWORKS (COMPUTER); PREDICTIVE VALUE OF TESTS; PROTEIN STRUCTURE, SECONDARY; PROTEINS; SEQUENCE ANALYSIS, PROTEIN;

EID: 49149096763     PISSN: 03781119     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.gene.2008.06.008     Document Type: Article

References (36)

1. Adamczak R.Ç., Porollo A., and Meller J.Ç. Combining prediction of secondary structure and solvent accessibility in proteins. Proteins 59 (2005) 467-475
2. Altschul S.F., et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25 (1997) 3389-3402
3. Bach A.C., et al. Type II′ to type I β-turn swap changes specificity for integrins. J. Am. Chem. Soc. 118 (1996) 293-294
4. Baldi P., Brunak S., Frasconi P., Soda G., and Pollastri G. Exploiting the past and the future in protein secondary structure prediction. Bioinformatics 15 (1999) 937-946
5. Berman H.M., et al. The protein data bank. Nucleic Acids Res. 28 (2000) 235-242
6. Chou P.Y., and Fasman G.D. Prediction of beta-turns. Biophys J. 26 (1979) 367-383
7. Elman J.L. Finding structure in time. Cogn. Sci. 14 (1990) 179-211
8. Fawcett T. ROC graphs: notes and practical considerations for researchers. Mach. Learn. 31 (2004)
9. Frishman D., and Argos P. Seventy-five percent accuracy in protein secondary structure prediction. Proteins 27 (1997) 329-335
10. Fuchs P.F.J., and Alix A.J.P. High accuracy prediction of beta-turns and their types using propensities and multiple alignments. Proteins 59 (2005) 828-839
11. Hinds M.G., et al. Synthesis, conformational properties, and antibody recognition of peptides containing beta-turn mimetics based on alpha-alkylproline derivatives. J. Med. Chem. 34 (1991) 1777-1789
12. Hutchinson E.G., and Thornton J.M. PROMOTIF - a program to identify and analyze structural motifs in proteins. Protein Sci. 5 (1996) 212-220
13. Jones D.T. Protein secondary structure prediction based on position-specific scoring matrices. J. Mol. Biol. 292 (1999) 195-202
14. Jones D.T., and Swindells M.B. Getting the most from PSI-BLAST. Trends Biochem. Sci. 27 (2002) 161-164
15. Kabsch W., and Sander C. Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers 22 (1983) 2577-2637
16. Kaur H., and Raghava G.P.S. A neural network method for prediction of beta-turn types in proteins using evolutionary information. Bioinformatics 20 (2004) 2751-2758
17. Kaur H., and Raghava G.P.S. Prediction of beta-turns in proteins from multiple alignment using neural network. Protein Sci. 12 (2003) 627-634
18. Kaur H., and Raghava G.P.S. An evaluation of beta-turn prediction methods. Bioinformatics 18 (2002) 1508-1514
19. Kim S. Protein beta-turn prediction using nearest-neighbor method. Bioinformatics 20 (2004) 40-44
20. Lawrence S., Burns I., Back A., Tsoi A.C., and Giles C.L. In: Orr G.B., and Müller K.-R. (Eds). Neural Networks: Tricks of the Trade vol. 1524 (1998), Springer, Berlin 545
21. Lewis T.J., Wedberg G.H., Peng J.C., Ricci J.L., Cheng C.M., and Maher J.V. Possible Recoil Effects in (16O, 15N) Transitions About 10 MeV above the Coulomb Barrier Phys. Rev. C vol. 8 (1973), American Physical Society 678-683
22. Li S.Z., Lee J.H., Lee W., Yoon C.J., Baik J.H., and Lim S.K. Type I beta-turn conformation is important for biological activity of the melanocyte-stimulating hormone analogues. Eur. J. Biochem. 265 (1999) 430-440
23. McGregor M.J., Flores T.P., and Sternberg M.J. Prediction of beta-turns in proteins using neural networks. Protein Eng. 2 (1989) 521-526
24. Qian N., and Sejnowski T.J. Predicting the secondary structure of globular proteins using neural network models. J. Mol. Biol. 202 (1988) 865-884
25. Richardson J.S. The anatomy and taxonomy of protein structure. Adv. Protein Chem. 34 (1981) 167-339
26. Rini J.M., Stanfield R.L., Stura E.A., Salinas P.A., Profy A.T., and Wilson I.A. Crystal structure of a human immunodeficiency virus type 1 neutralizing antibody, 50.1, in complex with its V3 loop peptide antigen. Proc. Natl. Acad. Sci. U S A 90 (1993) 6325-6329
27. Rose G.D., Gierasch L.M., and Smith J.A. Turns in peptides and proteins. Adv. Protein Chem. 37 (1985) 1-109
28. Rost B., and Sander C. Prediction of protein secondary structure at better than 70% accuracy. J. Mol. Biol. 232 (1993) 584-599
29. Shepherd A.J., Gorse D., and Thornton J.M. Prediction of the location and type of beta-turns in proteins using neural networks. Protein Sci. 8 (1999) 1045-1055
30. Venkatachalam C.M. Stereo chemical criteria for polypeptides and proteins. V. Conformation of a system of three linked peptide units. Biopolymers 6, 1425-1436. Domains of selectin family and its implications. FEBS Lett. 363 (1968) 123-126
31. Wheeler D.L., et al. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 35 (2007) D5-12
32. Wood M.J., and Hirst J.D. Protein secondary structure prediction with dihedral angles. Proteins 59 (2005) 476-481
33. Wootton J.C., and Federhen S. Statistics of local complexity in amino acid sequences and sequence databases. Comput. Chem. 17 (1993) 149-163
34. Zhang C., and Chou K. Prediction of beta-turns in proteins by 1-4 & 2-3 correlation model. Biopolymers 41 (1997) 673-702
35. Zhang Q., Yoon S., and Welsh W.J. Improved method for predicting beta-turn using support vector machine. Bioinformatics 21 (2005) 2370-2374
36. Zimmerman S.S., and Scheraga H.A. Local interactions in bends of proteins. Proc. Natl. Acad. Sci. U S A 74 (1977) 4126-4129