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In-Silico Bioprospecting: Finding Better Enzymes

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Abstract

Enzymes are essential biological macromolecules, which catalyse chemical reactions and have impacted the human civilization tremendously. The importance of enzymes as biocatalyst was realized more than a century ago by eminent scientists like Kuhne, Buchner, Payen, Sumner, and the last three decades has seen exponential growth in enzyme industry, mainly due to the revolution in tools and techniques in molecular biology, biochemistry and production. This has resulted in high demand of enzymes in various applications like food, agriculture, chemicals, pharmaceuticals, cosmetics, environment and research sector. The cut-throat competition also pushes the enzyme industry to constantly discover newer and better enzymes regularly. The conventional methods to discover enzymes are generally costly, time consuming and have low success rate. Exploring the exponentially growing biological databases with the help of various computational tools can increase the discovering process, with less resource consumption and higher success rate. Present review discusses this approach, known as in-silico bioprospecting, which broadly involves computational searching of gene/protein databases to find novel enzymes.

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References

  1. Coker, J. A. (2016). Extremophiles and biotechnology: Current uses and prospects. F1000Research, 5, 396.

    Article  CAS  Google Scholar 

  2. Anastas, P. T., & Warner, J. C. (1998). Green chemistry: Theory and practice. Oxford University Press: New York.

    Google Scholar 

  3. Savile, C. K., Janey, J. M., Mundorff, E. C., Moore, J. C., Tam, S., Jarvis, W. R., … Hughes, G. J. (2010). Biocatalytic asymmetric synthesis of chiral amines from ketones applied to sitagliptin manufacture. Science, 329(5989), 305–309.

    Article  CAS  PubMed  Google Scholar 

  4. Chamoli, M., & Pant, K. (2014). In-silico bioprospecting of the enzymes involved in the biosynthetic pathway of the alkaloid berberine and its distance study Through R. International Journal of Advanced Technology in Engineering and Science, 2(9), 165–178.

    Google Scholar 

  5. Musumeci, M. A., Lozada, M., Rial, D. V., Cormack, W. P. M., Jansson, J. K., Sjöling, S., … Dionisi, H. M. (2017). Prospecting biotechnologically-relevant monooxygenases from cold sediment metagenomes: An in silico approach. Marine Drugs, 15(4).

  6. Tan, H., Wu, X., Xie, L., Huang, Z., Peng, W., & Gan, B. (2016). Identification and characterization of a mesophilic phytase highly resilient to high-temperatures from a fungus-garden associated metagenome. Applied Microbiology and Biotechnology, 100(5), 2225–2241.

    Article  CAS  PubMed  Google Scholar 

  7. Berón, C. M., Curatti, L., & Salerno, G. L. (2005). New strategy for identification of novel cry-type genes from bacillus thuringiensis strains. Applied and Environmental Microbiology, 71(2), 761–765.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Tan, H., Wu, X., Xie, L., Huang, Z., Peng, W., & Gan, B. (2016). A novel phytase derived from an acidic peat-soil microbiome showing high stability under acidic plus pepsin conditions. Journal of Molecular Microbiology and Biotechnology, 26(4), 291–301.

    Article  CAS  PubMed  Google Scholar 

  9. Shakeel, T., Gupta, M., Fatma, Z., Kumar, R., Kumar, R., Singh, R., … Yazdani, S. S. (2018). A consensus-guided approach yields a heat-stable alkane-producing enzyme and identifies residues promoting thermostability. The Journal of Biological Chemistry, 1–30.

  10. Sharma, N., Thakur, N., Raj, T., Savitri, & Bhalla, T. C. (2017). Mining of microbial genomes for the novel sources of nitrilases. BioMed Research International, 2017.

  11. Gupta, S., Singh, Y., Kumar, H., Raj, U., Rao, A. R., & Varadwaj, P. K. (2018). Identification of novel abiotic stress proteins in triticum aestivum through functional annotation of hypothetical proteins. Interdisciplinary Sciences: Computational Life Sciences, 10(1), 205–220.

    CAS  Google Scholar 

  12. Thornbury, M., Sicheri, J., Guinard, C., Mahoney, D., Routledge, F., Curry, M., … Getz, L. (2018). Discovery and Characterization of Novel Lignocellulose-Degrading Enzymes from the Porcupine Microbiome. bioRxiv, (February).

  13. Toyama, D., de Morais, M. A. B., Ramos, F. C., Zanphorlin, L. M., Tonoli, C. C. C., Balula, A. F., et al. (2018). A novel β-glucosidase isolated from the microbial metagenome of Lake Poraquê (Amazon, Brazil). Biochimica et Biophysica Acta, 1866(4), 569–579.

    Article  CAS  PubMed  Google Scholar 

  14. Qu, Y., Egelund, J., Gilson, P. R., Houghton, F., Gleeson, P. A., Schultz, C. J., & Bacic, A. (2008). Identification of a novel group of putative Arabidopsis thaliana β-(1,3)-galactosyltransferases. Plant Molecular Biology, 68(1–2), 43–59.

    Article  CAS  PubMed  Google Scholar 

  15. Foong, C. P., Lakshmanan, M., Abe, H., Taylor, T. D., Foong, S. Y., & Sudesh, K. (2018). A novel and wide substrate specific polyhydroxyalkanoate (PHA) synthase from unculturable bacteria found in mangrove soil. Journal of Polymer Research, 25(1), 23.

    Article  CAS  Google Scholar 

  16. Vaquero, M. E., De Eugenio, L. I., Martínez, M. J., & Barriuso, J. (2015). A novel CalB-type lipase discovered by fungal genomes mining. PLoS ONE, 10(4), 1–11.

    Article  CAS  Google Scholar 

  17. Adam, N., & Perner, M. (2018). Novel hydrogenases from deep-sea hydrothermal vent metagenomes identified by a recently developed activity-based screen. ISME Journal, 12(5), 1225–1236.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Ferrer, M., Martínez-Martínez, M., Bargiela, R., Streit, W. R., Golyshina, O. V., & Golyshin, P. N. (2016). Estimating the success of enzyme bioprospecting through metagenomics: Current status and future trends. Microbial Biotechnology, 9(1), 22–34.

    Article  CAS  PubMed  Google Scholar 

  19. Uria, A. R., & Zilda, D. S. (2016). Metagenomics-guided mining of commercially useful biocatalysts from marine microorganisms. In Advances in Food and nutrition research.

  20. Gasteiger, E., Hoogland, C., Gattiker, A., Duvaud, S., Wilkins, M. R., Appel, R. D., & Bairoch, A. (2005). Protein identification and analysis tools on the ExPASy server. The Proteomics Protocols Handbook, 571–607.

  21. Roumpeka, D. D., Wallace, R. J., Escalettes, F., Fotheringham, I., & Watson, M. (2017). A review of bioinformatics tools for bio-prospecting from metagenomic sequence data. Frontiers in Genetics.

  22. Machielsen, R., Leferink, N. G. H., Hendriks, A., Brouns, S. J. J., Hennemann, H. G., Daußmann, T., & Van Der Oost, J. (2008). Laboratory evolution of Pyrococcus furiosus alcohol dehydrogenase to improve the production of (2S,5S)-hexanediol at moderate temperatures. Extremophiles, 12(4), 587–594.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Wang, N. Q., Sun, J., Huang, J., & Wang, P. (2014). Cloning, expression, and directed evolution of carbonyl reductase from Leifsonia xyli HS0904 with enhanced catalytic efficiency. Applied Microbiology and Biotechnology, 98(20), 8591–8601.

    Article  CAS  PubMed  Google Scholar 

  24. Jakoblinnert, A., Wachtmeister, J., Schukur, L., Shivange, A. V., Bocola, M., Ansorge-Schumacher, M. B., & Schwaneberg, U. (2013). Reengineered carbonyl reductase for reducing methyl-substituted cyclohexanones. Protein Engineering, Design and Selection, 26(4), 291–298.

    Article  CAS  PubMed  Google Scholar 

  25. Hoelsch, K., Sührer, I., Heusel, M., & Weuster-Botz, D. (2013). Engineering of formate dehydrogenase: Synergistic effect of mutations affecting cofactor specificity and chemical stability. Applied Microbiology and Biotechnology, 97(6), 2473–2481.

    Article  CAS  PubMed  Google Scholar 

  26. Koudelakova, T., Chaloupkova, R., Brezovsky, J., Prokop, Z., Sebestova, E., Hesseler, M., … Damborsky, J. (2013). Engineering enzyme stability and resistance to an organic cosolvent by modification of residues in the access tunnel. Angewandte Chemie - International Edition, 52(7), 1959–1963.

    Article  CAS  PubMed  Google Scholar 

  27. Buller, A. R., Brinkmann-Chen, S., Romney, D. K., Herger, M., Murciano-Calles, J., & Arnold, F. H. (2015). Directed evolution of the tryptophan synthase β-subunit for stand-alone function recapitulates allosteric activation. Proceedings of the National Academy of Sciences, 112(47), 14599–14604.

  28. Brinkmann-Chen, S., Flock, T., Cahn, J. K. B., Snow, C. D., Brustad, E. M., McIntosh, J. A., … Arnold, F. H. (2013). General approach to reversing ketol-acid reductoisomerase cofactor dependence from NADPH to NADH. Proceedings of the National Academy of Sciences, 110(27), 10946–10951.

  29. Fox, R. J., & Huisman, G. W. (2008). Enzyme optimization: moving from blind evolution to statistical exploration of sequence-function space. Trends in Biotechnology, 26(3), 132–138.

    Article  CAS  PubMed  Google Scholar 

  30. Reetz, M. T., Rentzsch, M., Pletsch, A., Maywald, M., Maiwald, P., Peyralans, J. J. P., … Taglieber, A. (2007). Directed evolution of enantioselective hybrid catalysts: a novel concept in asymmetric catalysis. Tetrahedron, 63(28), 6404–6414.

    Article  CAS  Google Scholar 

  31. Rubin-Pitel, S. B., Cho, C. M. H., Chen, W., & Zhao, H. (2007). Directed evolution tools in bioproduct and bioprocess development. Bioprocessing for Value-Added Products from Renewable Resources, 49–72.

  32. Li, Y., & Cirino, P. C. (2014). Recent advances in engineering proteins for biocatalysis. Biotechnology and Bioengineering, 111(7), 1273–1287.

    Article  CAS  PubMed  Google Scholar 

  33. Wang, M., Si, T., & Zhao, H. (2012). Biocatalyst development by directed evolution, Bioresource Technology, 40(6), 1301–1315.

    CAS  Google Scholar 

  34. Woodley, J. M. (2013). Protein engineering of enzymes for process applications. Current Opinion in Chemical Biology, 17(2), 310–316.

    Article  CAS  PubMed  Google Scholar 

  35. Zheng, G. W., & Xu, J. H. (2011). New opportunities for biocatalysis: Driving the synthesis of chiral chemicals. Current Opinion in Biotechnology, 22(6), 784–792.

    Article  CAS  PubMed  Google Scholar 

  36. Lane, M. D., & Seelig, B. (2014). Advances in the directed evolution of proteins. Current Opinion in Chemical Biology, 22, 129–136.

    Article  CAS  PubMed  Google Scholar 

  37. Kaur, J., Kumar, A., & Kaur, J. (2018). Strategies for optimization of heterologous protein expression in E. coli: Roadblocks and reinforcements. International Journal of Biological Macromolecules, 106, 803–822.

    Article  CAS  PubMed  Google Scholar 

  38. Rosano, G. L., & Ceccarelli, E. A. (2014). Recombinant protein expression in Escherichia coli: Advances and challenges. Frontiers in Microbiology.

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The manuscript is a review article and was not supported by any funding agency.

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Authors and Affiliations

  1. Department of Biological Sciences, Sunandan Divatia School of Science, NMIMS Deemed to be University, Vile Parle (W), Mumbai, 400056, India

    Asmita Kamble & Harinder Singh

  2. Biosystems Engineering Lab, Department of Chemical Engineering, IIT Bombay, Powai, Mumbai, 400076, India

    Sumana Srinivasan

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  1. Asmita Kamble
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  2. Sumana Srinivasan
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Correspondence to Harinder Singh.

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Kamble, A., Srinivasan, S. & Singh, H. In-Silico Bioprospecting: Finding Better Enzymes. Mol Biotechnol 61, 53–59 (2019). https://doi.org/10.1007/s12033-018-0132-1

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