Unleashing the power of meta-threading for evolution/structure-based function inference of proteins

Frontiers in Genetics

Volumn 4, Issue JUN, 2013, Pages

  Brylinski, Michal ^a  

^a LOUISIANA STATE UNIVERSITY   (United States)

Author keywords

Iron sulfur binding; Ligand binding; Metal binding; Protein function inference; Protein meta threading; Protein DNA interactions; Protein protein interactions; Template based modeling

Indexed keywords

EID: 84883528654     PISSN: None     EISSN: 16648021     Source Type: Journal    
DOI: 10.3389/fgene.2013.00118     Document Type: Article

References (36)

1. Berman, H. M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T. N., Weissig, H., et al. (2000). The Protein Data Bank. Nucleic Acids Res. 28, 235-242. doi: 10.1093/nar/28.1.235
2. Biegert, A., and Soding, J. (2009). Sequence context-specific profiles for homology searching. Proc. Natl. Acad. Sci. U.S.A. 106, 3770-3775. doi: 10.1073/pnas.0810767106
3. Brylinski, M., and Feinstein, W. P. (2012). Setting up a meta-threading pipeline for high-throughput structural bioinformatics: eThread software distribution, walkthrough and resource profiling. J. Comput. Sci. Syst. Biol. 6, 001-010. doi: 10.4172/jcsb.1000094
4. Brylinski, M., and Lingam, D. (2012). eThread: a highly optimized machine learning-based approach to meta-threading and the modeling of protein tertiary structures. PLoS ONE 7:e50200. doi: 10.1371/journal.pone.0050200
5. Brylinski, M., and Skolnick, J. (2008). A threading-based method (FINDSITE) for ligand-binding site prediction and functional annotation. Proc. Natl. Acad. Sci. U.S.A. 105, 129-134. doi: 10.1073/pnas.0707684105
6. Brylinski, M., and Skolnick, J. (2010). Comparison of structure-based and threading-based approaches to protein functional annotation. Proteins 78, 118-134. doi: 10.1002/prot.22566
7. Brylinski, M., and Skolnick, J. (2011). FINDSITE-metal: integrating evolutionary information and machine learning for structure-based metal-binding site prediction at the proteome level. Proteins 79, 735-751. doi: 10.1002/prot.22913
8. Bucher, P., Karplus, K., Moeri, N., and Hofmann, K. (1996). A flexible motif search technique based on generalized profiles. Comput. Chem. 20, 3-23. doi: 10.1016/S0097-8485(96)80003-9
9. Chikhi, R., Sael, L., and Kihara, D. (2010). Real-time ligand binding pocket database search using local surface descriptors. Proteins 78, 2007-2028. doi: 10.1002/prot.22715
10. Eddy, S. R. (1998). Profile hidden Markov models. Bioinformatics 14, 755-763. doi: 10.1093/bioinformatics/14.9.755
11. Gao, M., and Skolnick, J. (2010). iAlign: a method for the structural comparison of protein-protein interfaces. Bioinformatics 26, 2259-2265. doi: 10.1093/bioinformatics/btq404
12. Halford, S. E., and Marko, J. F. (2004). How do site-specific DNA-binding proteins find their targets?. Nucleic Acids Res. 32, 3040-3052. doi: 10.1093/nar/gkh624
13. Hughey, R., and Krogh, A. (1996). Hidden Markov models for sequence analysis: extension and analysis of the basic method. Comput. Appl. Biosci. 12, 95-107. doi: 10.1093/bioinformatics/12.2.95
14. Jones, D. T., Taylor, W. R., and Thornton, J. M. (1992). A new approach to protein fold recognition. Nature 358, 86-89. doi: 10.1038/358086a0
15. Kestler, H. A. (2001). ROC with confidence - a Perl program for receiver operator characteristic curves. Comput. Methods Programs Biomed. 64, 133-136. doi: 10.1016/S0169-2607 (00)00098-5
16. Krissinel, E., and Henrick, K. (2007). Inference of macromolecular assemblies from crystalline state. J. Mol. Biol. 372, 774-797. doi: 10.1016/j.jmb.2007.05.022
17. Lobley, A., Sadowski, M. I., and Jones, D. T. (2009). pGenTHREADER and pDomTHREADER: new methods for improved protein fold recognition and superfamily discrimination. Bioinformatics 25, 1761-1767. doi: 10.1093/bioinformatics/btp302
18. Moult, J., Fidelis, K., Kryshtafovych, A., Rost, B., and Tramontano, A. (2009). Critical assessment of methods of protein structure prediction - Round VIII. Proteins 77(Suppl. 9), 1-4. doi: 10.1002/prot.22589
19. Pandit, S. B., and Skolnick, J. (2008). Fr-TM-align: a new protein structural alignment method based on fragment alignments and the TM-score. BMC Bioinformatics 9:531. doi: 10.1186/1471-2105-9-531
20. Pons, J. L., and Labesse, G. (2009). @TOME-2: a new pipeline for comparative modeling of protein-ligand complexes. Nucleic Acids Res. 37, W485-W491. doi: 10.1093/nar/gkp368
21. Rost, B. (1999). Twilight zone of protein sequence alignments. Protein Eng. 12, 85-94. doi: 10.1093/protein/12.2.85
22. Rost, B. (2002). Enzyme function less conserved than anticipated. J. Mol. Biol. 318, 595-608. doi: 10.1016/S0022-2836(02)00016-5
23. Roy, A., Kucukural, A., and Zhang, Y. (2010). I-TASSER: a unified platform for automated protein structure and function prediction. Nat. Protoc.5, 725-738. doi: 10.1038/nprot.2010.5
24. Sadreyev, R., and Grishin, N. (2003). COMPASS: a tool for comparison of multiple protein alignments with assessment of statistical significance. J. Mol. Biol. 326, 317-336. doi: 10.1016/S0022-2836(02)01371-2
25. Sael, L., and Kihara, D. (2010). Binding ligand prediction for proteins using partial matching of local surface patches. Int. J. Mol. Sci. 11, 5009-5026. doi: 10.3390/ijms11125009
26. Sael, L., and Kihara, D. (2012). Detecting local ligand-binding site similarity in non homologous proteins by surface patch comparison. Proteins 80, 1177-1195. doi: 10.1002/prot.24018
27. Sinha, R., Kundrotas, P. J., and Vakser, I. A. (2010). Docking by structural similarity at protein-protein interfaces. Proteins 78, 3235-3241. doi: 10.1002/prot.22812
28. Soding, J. (2005). Protein homology detection by HMM-HMM comparison. Bioinformatics 21, 951-960. doi: 10.1093/bioinformatics/bti125
29. Tanimoto, T. T. (1958). An Elementary Mathematical Theory of Classification and Prediction. IBM Internal Report. New York, IBM.
30. Truchon, J. F., and Bayly, C. I. (2007). Evaluating virtual screening methods: good and bad metrics for the "early recognition" problem. J. Chem. Inf. Model. 47, 488-508. doi: 10.1021/ci600426e
31. Wallach, I., and Lilien, R. (2009). The protein-small-molecule database, a non-redundant structural resource for the analysis of protein-ligand binding. Bioinformatics 25, 615-620. doi: 10.1093/bioinformatics/btp035
32. Wang, G., and Dunbrack, R. L. Jr. (2003). PISCES: a protein sequence culling server. Bioinformatics 19, 1589-1591. doi: 10.1093/bioinformatics/btg224
33. Wass, M. N., Kelley, L. A., and Sternberg, M. J. (2010). 3DLigandSite: predicting ligand-binding sites using similar structures. Nucleic Acids Res. 38, W469-W473. doi: 10.1093/nar/gkq406
34. Zhang, Y., and Skolnick, J. (2004a). Scoring function for automated assessment of protein structure template quality. Proteins 57, 702-710. doi: 10.1002/prot.20264
35. Zhang, Y., and Skolnick, J. (2004b). Tertiary structure predictions on a comprehensive benchmark of medium to large size proteins. Biophys. J. 87, 2647-2655. doi: 10.1529/biophysj.104.045385
36. Zhou, H., and Zhou, Y. (2005). SPARKS 2 and SP3 servers in CASP6. Proteins 61(Suppl. 7), 152-156. doi: 10.1002/prot.20732