In silico maturation: Processing sequences to improve biopolymer functions based on genetic algorithms

Applications of Metaheuristics in Process Engineering

Volumn 9783319065083, Issue , 2014, Pages 271-288

  Savory, Nasa ^a   Abe, Koichi ^a   Yoshida, Wataru ^b   Ikebukuro, Kazunori ^a  

^a TOKYO UNIVERSITY OF AGRICULTURE AND TECHNOLOGY   (Japan)

^b TOKYO UNIVERSITY OF TECHNOLOGY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

LIGANDS; OLIGONUCLEOTIDES; PEPTIDES; RATIONAL FUNCTIONS;

APTAMERS; COMBINATORIAL LIBRARY; COMPLEX PROBLEMS; DIAGNOSTIC APPLICATIONS; FUNCTIONAL SEQUENCES; IN-SILICO; MULTIDIMENSIONAL PROBLEMS; PEPTIDE LIGAND; SEQUENCE SPACE; THERAPEUTIC APPLICATION;

GENETIC ALGORITHMS;

EID: 84930267903     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-3-319-06508-3_11     Document Type: Chapter

References (49)

1. Abe, K., Kobayashi, N., Sode, K., Ikebukuro, K.: Peptide ligand screening of alpha-synuclein aggregation modulators by in silico panning. BMC Bioinforma. 8, 451 (2007)
2. Asai, R., Nishimura, S.I., Aita, T., Takahashi, K.: In vitro selection of DNA aptamers on chips using a method for generating point mutations. Anal. Lett. 37, 645-656 (2005)
3. Belda, I., Madurga, S., Llorà, X., Martinell, M., Tarragó, T., Piqueras, M.G., Nicolás, E., Giralt, E.: ENPDA: an evolutionary structure-based de novo peptide design algorithm. J. Comput. Aided Mol. Des. 19, 585-601 (2005)
4. Bishop, G.R., Ren, J., Polander, B.C., Jeanfreau, B.D., Trent, J.O., Chaires, J.B.: Energetic basis of molecular recognition in a DNA aptamer. Biophys. Chem. 126, 165-175 (2007)
5. Bittker, J.A., Le, B.V., Liu, D.R.: Nucleic acid evolution and minimization by nonhomologous random recombination. Nat. Biotechnol. 20, 1024-1029 (2002)
6. Bock, L.C., Griffin, L.C., Latham, J.A., Vermaas, E.H., Toole, J.J.: Selection of single-stranded DNA molecules that bind and inhibit human thrombin. Nature 355, 564-566 (1992)
7. Boese, B.J., Breaker, R.R.: In vitro selection and characterization of cellulose-binding DNA aptamers. Nucleic Acids Res. 35, 6378-6388 (2007)
8. Brown, R.D., Martin, Y.C.: Designing combinatorial library mixtures using a genetic algorithm. J. Med. Chem. 40, 2304-2313 (1997)
9. Chushak, Y., Stone, M.O.: In silico selection of RNA aptamers. Nucleic Acids Res. 37, e87 (2009)
10. Crameri, A., Stemmer,W.P.: 10(20)-fold aptamer library amplification without gel purification. Nucleic Acids Res. 21, 4410 (1993)
11. Ellington, A.D., Szostak, J.W.: In vitro selection of RNA molecules that bind specific ligands. Nature 346, 818-822 (1990)
12. Ewing, T.J., Makino, S., Skillman, A.G., Kuntz, I.D.: DOCK 4.0: search strategies for automated molecular docking of flexible molecule databases. J. Comput. Aided Mol. Des. 15, 411-428 (2001)
13. FitzGerald, K.: In vitro display technologies -new tools for drug discovery. Drug Discov. Today 5, 253-258 (2000)
14. Goldberg, D.E.: Genetic algorithms in search, optimization and machine learning. Addison-Wesley, Boston (1989)
15. Holland, J.H.: Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. University of Michigan Press, Ann Arbor (1975)
16. Huey, R., Morris, G.M., Olson, A.J., Goodsell, D.S.: A semiempirical free energy force field with charge-based desolvation. J Comput. Chem. 28, 1145-1152 (2007)
17. Ikebukuro, K., Okumura, Y., Sumikura, K., Karube, I.: A novel method of screening thrombininhibiting DNA aptamers using an evolution-mimicking algorithm. Nucleic Acids Res. 33, e108 (2005)
18. Ikebukuro, K., Yoshida, W., Noma, T., Sode, K.: Analysis of the evolution of the thrombininhibiting DNA aptamers using a genetic algorithm. Biotechnol. Lett. 28, 1933-1937 (2006)
19. Kanagawa, T.: Bias and artifacts in multitemplate polymerase chain reactions (PCR). J. Biosci. Bioeng. 96, 317-323 (2003)
20. Katilius, E., Flores, C., Woodbury, N.W.: Exploring the sequence space of a DNA aptamer using microarrays. Nucleic Acids Res. 35, 7626-7635 (2007)
21. Klug, S.J., Famulok, M.: All you wanted to know about SELEX. Mol. Biol. Rep. 20, 97-107 (1994)
22. Knight, C.G., Platt, M., Rowe, W., Wedge, D.C., Khan, F., Day, P.J., McShea, A., Knowles, J., Kell, D.B.: Array-based evolution of DNA aptamers allows modelling of an explicit sequencefitness landscape. Nucleic Acids Res. 37:e6 (2009)
23. Laing, C., Schlick, T.: Computational approaches to RNA structure prediction, analysis, and design. Curr. Opin. Struct. Biol. 21, 306-318 (2011)
24. Lin, P.H., Tsai, C.W., Wu, J.W., Ruaan, R.C., Chen, W.Y.: Molecular dynamics simulation of the induced-fit binding process of DNA aptamer and L-argininamide. Biotechnol. J. 7, 1367-1375 (2012)
25. Macaya, R.F., Waldron, J.A., Beutel, B.A., Gao, H., Joesten, M.E., Yang, M., Patel, R., Bertelsen, A.H., Cook, A.F.: Structural and functional characterization of potent antithrombotic oligonucleotides possessing both quadruplex and duplex motifs. Biochemistry 34, 4478-4492 (1995)
26. Noma, T., Sode, K., Ikebukuro, K.: Characterization and application of aptamers for Taq DNA polymerase selected using an evolution-mimicking algorithm. Biotechnol. Lett. 28, 1939-1944 (2006)
27. Noma, T., Ikebukuro, K.: Aptamer selection based on inhibitory activity using an evolutionmimicking algorithm. Biochem. Biophys. Res. Commun. 347, 226-231 (2006)
28. Nonaka, Y., Sode, K., Ikebukuro, K.: Screening and improvement of an anti-VEGF DNA aptamer. Molecules 15, 215-225 (2010)
29. Nonaka, Y., Yoshida, W., Abe, K., Ferri, S., Schulze, H., Bachmann, T.T., Ikebukuro, K.: Affinity improvement of a VEGF aptamer by in silico maturation for a sensitive VEGFdetection system. Anal. Chem. 85, 1132-1137 (2013)
30. Pfeffer, P., Fober, T., Hullermeier, E., Klebe, G.: GARLig: a fully automated tool for subset selection of large fragment spaces via a self-adaptive genetic algorithm. J. Chem. Inf. Model 50, 1644-1659 (2010)
31. Pitt, J.N., Ferre-D0Amaré, A.R.: Rapid construction of empirical RNA fitness landscapes. Science 330, 376-379 (2010)
32. Platt, M., Rowe, W., Wedge, D.C., Kell, D.B., Knowles, J., Day, P.J.: Aptamer evolution for array-based diagnostics. Anal. Biochem. 390, 203-205 (2009)
33. Rockendorf, N., Borschbach,M., Frey, A.: Molecular evolution of peptide ligands with customtailored characteristics for targeting of glycostructures. PLoS Comput. Biol. 8, e1002800 (2012)
34. Rowe,W., Platt, M.,Wedge, D.C., Day, P.J., Kell, D.B., Knowles, J.D.: Convergent evolution to an aptamer observed in small populations on DNA microarrays. Phys. Biol. 7, 036007 (2010)
35. Rowe, W., Platt, M., Wedge, D.C., Day, P.J., Kell, D.B., Knowles, J.: Analysis of a complete DNA-protein affinity landscape. J. R. Soc. Interface 7, 397-408 (2010)
36. Savory, N., Abe, K., Sode, K., Ikebukuro, K.: Selection of DNA aptamer against prostate specific antigen using a genetic algorithm and application to sensing. Biosens. Bioelectron. 26, 1386-1391 (2010)
37. Savory, N., Lednor, D., Tsukakoshi, K., Abe, K., Yoshida,W., Ferri, S., Jones, B.V., Ikebukuro, K.: In silico Maturation of Binding-Specificity of DNA Aptamers Against Proteus mirabilis. Biotechnol. Bioeng. 110, 2573-2580 (2013)
38. Savory, N., Takahashi, Y., Tsukakoshi, K., Hasegawa, H., Takase, M., Abe, K., Yoshida, W., Ferri, S., Kumazawa, S., Sode, K., Ikebukuro, K.: Simultaneous improvement of specificity and affinity of aptamers against Streptococcus mutans by in silico maturation for biosensor development. Biotechnol. Bioeng. Epub ahead of print. doi:10.1002/bit.25111 (2013)
39. Scott, J.K., Smith, G.P.: Searching for peptide ligands with an epitope library. Science 249, 386-390 (1990)
40. Singh, J., Ator, M.A., Jaeger, E.P., Allen, M.P., Whipple, D.A., Soloweij, J.E., Chowdhary, S., Treasurywala, A.M.: Application of genetic algorithms to combinatorial synthesis: A computational approach to lead identification and lead optimization. J. Am. Chem. Soc. 118, 1669-1676 (1996)
41. Smirnov, I., Shafer, R.H.: Effect of loop sequence and size on DNA aptamer stability. Biochemistry 39, 1462-1468 (2000)
42. Teixidó, M., Belda, I., Roselló, X., González, S., Fabre, M., Llorà, X., Bacardit, J., Garrell, J.M., Vilaró, S., Albericio, F., Giralt, E.: Development of a genetic algorithm to design and identify peptides that can cross the blood-brain barrier. QSAR Comb. Sci. 22, 745-753 (2003)
43. Teixidó, M., Belda, I., Zurita, E., Llorà, X., Fabre, M., Vilaró, S., Albericio, F., Giralt, E.: Evolutionary combinatorial chemistry, a novel tool for SAR studies on peptide transport across the blood-brain barrier. Part 2. Design, synthesis and evaluation of a first generation of peptides. J. Pept. Sci. 11, 789-804 (2005)
44. Tuerk, C., Gold, L.: Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase. Science 249, 505-510 (1990)
45. Verdonk, M.L., Cole, J.C., Hartshorn, M.J., Murray, C.W., Taylor, R.D.: Improved proteinligand docking using GOLD. Proteins 52, 609-623 (2003)
46. Weber, L., Wallbaum, S., Broger, C., Gubernator, K.: Optimization of the biological-activity of combinatorial compound libraries by a genetic algorithm. Angew. Chem. Int. Ed. Engl. 34, 2280-2282 (1995)
47. Yagi, Y., Terada, K., Noma, T., Ikebukuro, K., Sode, K.: In silico panning for a non-competitive peptide inhibitor. BMC Bioinforma. 8, 11 (2007)
48. Yokobayashi, Y., Ikebukuro, K., McNiven, S., Karube, I.: Directed evolution of trypsin inhibiting peptides using a genetic algorithm. J. Chem. Soc. Perkin Trans. 1, 2435-2437 (1996)
49. Zhang, W., Loughran, M.G., Kanna, S., Yano, K., Ikebukuro, K., Yokobayashi, Y., Kuroda, R., Karube, I.: Exploration of structural features of monomeric helical peptides designed with a genetic algorithm. Proteins 53, 193-200 (2003)