Vital: Viterbi algorithm for de novo peptide design

PLoS ONE

Volumn 5, Issue 6, 2010, Pages

  Besray Unal, E ^a   Gursoy, Attila ^a   Erman, Burak ^a  

^a KOÇ UNIVERSITY   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

HEPTAPEPTIDE; PEPTIDE; PROTEIN; PROTEIN INHIBITOR;

ALGORITHM; ARTICLE; BINDING AFFINITY; BINDING SITE; CONTROLLED STUDY; DRUG DESIGN; ENERGY; HIDDEN MARKOV MODEL; MOLECULAR DOCKING; PREDICTION; PROTEIN BINDING; PROTEIN CONFORMATION; PROTEIN TARGETING; STATISTICAL MODEL;

ALGORITHMS; MARKOV CHAINS; MODELS, MOLECULAR; PEPTIDES; PROBABILITY;

EID: 77955234902     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0010926     Document Type: Article

References (66)

1. Petsalaki E, Stark A, Garcia-Urdiales E, Russell RB (2009) Accurate Prediction of Peptide Binding Sites on Protein Surfaces. Plos Computational Biology 5: -.
2. Frenkel D, Clark DE, Li J, Murray CW, Robson B, et al. (1995) Pro-Ligand - an Approach to De-Novo Molecular Design.4. Application to the Design of Peptides. Journal of Computer-Aided Molecular Design 9: 213-225.
3. Hetenyi C, van der Spoel D (2002) Efficient docking of peptides to proteins without prior knowledge of the binding site. Protein Science 11: 1729-1737.
4. Juretic D, Vukicevic D, Ilic N, Antcheva N, Tossi A (2009) Computational Design of Highly Selective Antimicrobial Peptides. Journal of Chemical Information and Modeling 49: 2873-2882.
5. Mayrose I, Penn O, Erez E, Rubinstein ND, Shlomi T, et al. (2007) Pepitope: epitope mapping from affinity-selected peptides. Bioinformatics 23: 3244-3246.
6. Moreau V, Fleury C, Piquer D, Nguyen C, Novali N, et al.(2008) PEPOP: Computational design of immunogenic peptides. Bmc Bioinformatics 9: -.
7. Stein A, Aloy P (2008) A molecular interpretation of genetic interactions in yeast. Febs Letters 582: 1245-1250.
8. Brusic V, Rudy G, Honeyman M, Hammer J, Harrison L (1998) Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network. Bioinformatics 14: 121-130.
9. Hammer J, Bono E, Gallazzi F, Belunis C, Nagy Z, et al. (1994) Precise Prediction of Major Histocompatibility Complex Class-Ii Peptide Interaction Based on Peptide Side-Chain Scanning. Journal of Experimental Medicine 180: 2353-2358.
10. Hammer J, Gallazzi F, Bono E, Karr RW, Guenot J, et al. (1995) Peptide Binding-Specificity of Hla-Dr4 Molecules - Correlation with Rheumatoid- Arthritis Association. Journal of Experimental Medicine 181: 1847-1855.
11. Hanai T, Noguchi H, Matsubara Y, Takeda K, Honda H, et al. (2000) Computational Design of Proteinous Drug Employing Hidden Markov Model. Genome Informatics 11: 394-395.
12. Harrison LC, Tait BD, Honeyman MC, Brusic V (1993) Major Histocompatibility Complex (Mhc) Molecules in Insulin-Dependent Diabetes. Journal of Leukocyte Biology. pp 105-105.
13. Honeyman MC, Brusic V, Stone NL, Harrison LC (1998) Neural networkbased prediction of candidate T-cell epitopes. Nature Biotechnology 16: 966-969.
14. Kato R, Noguchi H, Honda H, Kobayashi T (2003) Hidden Markov modelbased approach as the first screening of binding peptides that interact with MHC class II molecules. Enzyme and Microbial Technology 33: 472-481.
15. Noguchi H, Hanai T, Honda H, Harrison LC, Kobayashi T (2001) Fuzzy neural network-based prediction of the motif for MHC class II binding peptides. Journal of Bioscience and Bioengineering 92: 227-231.
16. Noguchi H, Kato R, Hanai T, Matsubara Y, Honda H, et al. (2002) Hidden Markov Model-Based Prediction of Antigenic Peptides That Interact with MHC Class II Molecules. Journal of Bioscience and Bioengineering 94: 264-270.
17. Ajay A, Walters WP, Murcko MA (1998) Can we learn to distinguish between ''drug-like'' and ''nondrug-like'' molecules? Journal of Medicinal Chemistry 41: 3314-3324.
18. Abe K, Kobayashi N, Sode K, Ikebukuro K (2007) Peptide ligand screening of asynuclein aggregation modulators by in silico panning. BMC Bioinformatics 8: 451.
19. Kamphausen S, Holtge N, Wirsching F, Morys-Wortmann C, Riester D, et al. (2002) Genetic algorithm for the design of molecules with desired properties. Journal of Computer-Aided Molecular Design 16: 551-567.
20. Riester D, Wirsching F, Salinas G, Keller M, Gebinoga M, et al. (2005) Thrombin inhibitors identified by computer-assisted multiparameter design. Proceedings of the National Academy of Sciences of the United States of America 102: 8597-8602.
21. Belda I, Madurga S, Llora X, Martinell M, Tarrago T, et al. (2005) ENPDA: an evolutionary structure-based de novo peptide design algorithm. Journal of Computer-Aided Molecular Design 19: 585-601.
22. Klepeis JL, Floudas CA, Morikis D, Tsokos CG, Lambris JD (2004) Design of peptide analogues with improves activity using a novel de novo protein design approach. Industrial & Engineering Chemistry Research 43: 3817-3826.
23. Singh J, Ator MA, Jaeger EP, Allen MP, Whipple DA, et al. (1996) Application of Genetic Algorithms to Combinatorial Synthesis: A Computational Approach to Lead Identification and Lead Optimization. J Am Chem Soc 118: 1669-1676.
24. Budin N, Ahmed S, Majeux N, Caflisch A (2001) An evolutionary approach for structure-based design of natural and nonnatural peptidic ligands. Combinatorial Chemistry & High Throughput Screening 4: 661-673.
25. Budin N, Majeux N, Caflisch A (2001) Fragment-based flexible ligand docking by evolutionary optimization. Biological Chemistry 382: 1365-1372.
26. Budin N, Majeux N, Tenette-Souaille C, Caflisch A (2001) Structure-based ligand design by a build-up approach and genetic algorithm search in conformational space. Journal of Computational Chemistry 22: 1956-1970.
27. Unal EB, Gursoy A, Erman B (2010) Inhibitor Peptide Design for NF-kappaB: Markov Model and Genetic Algorithm Approaches. 5th International Symposium on Health Informatics and Bioinformatics (HIBIT'10). Antalya, Turkey: IEEE Xplore
28. London N, Movshovitz-Attias D, Schueler-Furman O (2010) TheStructural Basis of Peptide-Protein Binding Strategies. Structure 18: 188-199.
29. Pegg SCH, Haresco JJ, Kuntz ID (2001) A genetic algorithm for structure-based de novo design. Journal of Computer-Aided Molecular Design 15: 911-933.
30. Haliloglu T, Erman B (2009) Analysis of Correlations between Energy and Residue Fluctuations in Native Proteins and Determnation of Specific Sites for Binding. Physical Review Letters 102: 088103.
31. Haliloglu T, Gul A, Erman B (2010) Predicting the Important Residues and Interaction Pathways in Proteins Using the Gaussian Network Model. Application to Binding and Stability of HLA Proteins. Submitted to PLOS computational Biology
32. Haliloglu T, Seyrek E, Erman B (2008) Prediction of Binding Sites in Receptor- Ligand Complexes with the Gaussian Network Model. Physical Review Letters 100: 228102.
33. Morris GM, Goodsell DS, Halliday RS, Huey R, Hart WE, et al. (1998) Automated Docking Using a Lamarckian Genetic Algorithm and and Empirical Binding Free Energy Function. Journal of Computational Chemistry 19: 1639-1662.
34. Flory PJ (1969) Statistical Mechanics of Chain Molecules. New York: Wiley.
35. Rabiner LR (1989) A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition. Proceedings of The IEEE 77: 257-286.
36. Ramachandran GN, Ramakrishnan C, Sasisekharan V (1963) Stereochemistry of polypeptide chain configurations. J Mol Biol 7: 95-99.
37. Forney GDJ (1973) The Viterbi Algorithm. Proceedings of IEEE 61: 268-278.
38. Viterbi AJ (1967) Error Bounds for Convolutional Codes and an Asymptotically Optimum Decoding Algorithm. IEEE Transactions on Information Theory 13: 260-269.
39. Ewens WJ, Grant GR (2001) Statistical methods in bioinformatics: an introduction. New York: Springer
40. Bystroff C, Krogh A (2008) Hidden Markov Models for Prediction of Protein Features. Methods in Molecular Biology 413: 173-198.
41. Sramek R, Brejova B, Vinar T (2009) On-line Viterbi Algorithm for Analysis of Long Biological Sequences. In: Giancarlo R, Hannenhalli S, eds. Lecture Notes in Computer Science. Philadelphia, PA, USA: Springer.
42. Fariselli P, Martelli PL, Casadio R (2005) A new decoding algorithm for hidden Markov models improves the prediction of the topology of all-beta membrane proteins. BMC Bioinformatics 6.
43. Mirabeau O, Perlas E, Severini C, Audero E, Gascuel O, et al. (2007) Identification of novel peptide hormones in the human proteome by Hidden Markov model screening. Genome Resarch 17: 320-327.
44. Sonmez K, Zaveri NT, Kerman IA, Burke S, Neal CR, et al. (2009) Evolutionary Sequence Modeling for Discovery of Peptide Hormones. Plos Computational Biology 5: -
45. Fitzkee NC, Fleming PJ, Rose GD (2005) The Protein Coil Library: a structural database of nonhelix, nonstrand fragments derived from the PDB. Proteins 58: 852-854.
46. Tuncbag N, Kar G, Gursoy A, Keskin O, Nussinov R (2009) Towards inferring time dimensionality in protein-protein interaction networks by integrating structures: the p53 example. Molecular Biosystems 5: 1770-1778.
47. Vanhee P, Stricher F, Baeten L, Verschueren E, Lenaerts T, et al. (2009) Protein-Peptide Interactions Adopt the Same Structural Motifs as Monomeric Protein Folds. Structure 17: 1128-1136.
48. Tuncbag N, Gursoy A, Keskin O (2009) Identification of Computational Hot Spots in Protein Interfaces: Combining Solvent Accessibility and Inter-Residue Potentials Improves the Accuracy. Bioinformatics 25: 1513-1520.
49. HyperChem(TM) Professional 7.51, Hypercube, Inc., 1115 NW 4th Street, Gainesville, Florida 32601, USA
50. Keskin O, Yuret D, Gursoy A, Turkay M, Erman B (2004) Relationships between amino acid sequence and backbone torsion angle preferences in proteins. Proteins-Structure Function and Bioinformatics 55: 992-998.
51. Unal EB, Gursoy A, Erman B (2009) Conformational energies and entropies of peptides, and the peptide-protein binding problem. Phys Biol 6: 36014.
52. Karplus PA (1996) Experimentally observed conformation-dependent geometry and hidden strain in proteins. Protein Science. pp 1406-1420.
53. DS Modeling 2.5, Accelrys Inc.
54. Louis JM, Dyda FD, Nashed NT, Kimmel AR, Davies DR (1998) Hydrophilic Peptides Derived from the Transframe Region of Gag-Pol Inhibit the HIV-1 Protease. Biochemistry 37: 2105-2110.
55. Fujinaga M, Cherney MM, Oyama H, Oda K, James MNG (2004) The molecular structure and catalytic mechanism of a novel carboxyl peptidase from Scytalidium lignicolum. PNAS 101: 3364-3369.
56. Kumar J, Ethayathulla AS, Srivastava DB, Singh N, Sharma S, et al (2009) Crystal structure of the complex formed between signalling protein from goat mammary gland (SPG-40) and a tripeptide Trp-Pro-Trp at 2.8A resolution
57. Nam KH, Kim K, Kim EEK, Hwang KY (2009) Crystal structure of an EfPDF complex with Met-Ala-Ser based on crystallographic packing. Biochemical and Biophysical Research Communications 381: 630-633.
58. Oldenburg KR, Loganathan D, Goldstein IJ, Schultz PG, Gallop MA (1992) Peptide ligands for a sugar-binding protein isolated from a random peptide library. PNAS 89: 5393-5397.
59. Zhang Z, Qian M, Huang Q, Jia Y, Tang Y, et al. (2001) Crystal Structure of the Complex of Concanavalin A and Tripeptide. Journal of Protein Chemistry 20: 59-65.
60. Hulsmeyer M, Fiorillo M, Bettosini F, Sorrentino R, Saenger W, et al. (2004) Dual, HLA-B27 Subtype-dependent Conformation of a Self-peptide. J Exp Med 199: 271-281.
61. Fiorillo M, Ruckert C, Hulsmeyer M, Sorrentino R, Saenger W, et al. (2005) Allele-dependent Similarity between Viral and Self-peptide Presentation by HLA-B27 Subtypes. J Biol Chem 280: 2962-2971.
62. Rucker C, Fiorillo M, Loll B, Moretti R, Biesiadka J, et al. (2006) Conformational Dimorphism of Self-peptides and Molecular Mimicry in a Disease-associated HLA-B27 Subtype. J Biol Chem 281: 2306-2316.
63. Lin-Su K, Wajnrajch M (2002) Growth Hormone Releasing Hormone (GHRH) and the GHRH Receptor. Reviews in Endocrine & Metabolic Disorders 3: 313-323.
64. Chantalat L, Jones N, Korber F, Navaza J, Pavlovsky A (1995) The Crystal-Structure of Wild-Type Growth-Hormone at 2.5 Angstrom Resolution. Protein Pept Lett 2: 333.
65. Haack T, Gonzalez MJ, Sanchez Y, Giralt E (1997) D-amino acids in protein de novo design. II. Protein-diastereomerism versus protein-enantiomerism. Letters in Peptide Science 4: 377-386.
66. Humphrey W, Dalke A, Schulten F (1996) VMD - Visual Molecular Dynamics. J Molec Graphics 14: 33-38.