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Tailoring Proteins to Re-Evolve Nature: A Short Review

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Abstract

Proteins are key biomolecules for most biological processes, their function is related to their conformation that is also dictated by their sequence of amino acids. Through evolution, nature has produced an immense variety of enzymatic tools of high efficiency and selectivity, and thanks to the understanding of the molecular basis of life and the technological advances, scientists have learned to introduce mutations and select mutant enzymes, to optimize and control their molecular fitness characteristics mainly for industrial, medical and environmental applications. The relationship between protein structure and enzymatic functionality is essential, and there are various experimental and instrumental techniques for unravelling the molecular changes, activities and specificities. Protein engineering applies computational tools, in hand with experimental tools for mutations, like directed evolution and rational design, along with screening methods to obtain protein variations with the desired properties under a short time frame. With innovations in technology, it is possible to fine tune properties in proteins and reach new frontiers in their applications. The present review will briefly discuss these points and methods, with a glimpse on their strengths and pitfalls, while giving an overview of the versatility of synthetic proteins and their huge potential for biotechnological and biomedical fields.

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References

  1. Bugg, T. D. (2001). Enzymes: General properties. In John Wiley & Sons, Ltd (Ed.), Encyclopedia of Life Sciences. Chichester: Wiley. https://doi.org/10.1038/npg.els.0000709.

    Chapter  Google Scholar 

  2. Baier, F., Copp, J. N., & Tokuriki, N. (2016). Evolution of enzyme superfamilies: Comprehensive exploration of sequence–function relationships. Biochemistry, 55(46), 6375–6388. https://doi.org/10.1021/acs.biochem.6b00723.

    Article  PubMed  CAS  Google Scholar 

  3. Pabis, A., Risso, V. A., Sanchez-Ruiz, J. M., & Kamerlin, S. C. (2017). Cooperativity and flexibility in enzyme evolution. Current Opinion in Structural Biology, 48, 83–92. https://doi.org/10.1016/j.sbi.2017.10.020.

    Article  PubMed  CAS  Google Scholar 

  4. Cobb, R. E., Chao, R., & Zhao, H. (2013). Directed evolution: past, present and future. AIChE Journal American Institute of Chemical Engineers, 59(5), 1432–1440. https://doi.org/10.1002/aic.13995.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. Lane, M. D., & Seelig, B. (2014). Advances in the directed evolution of proteins. Current Opinion in Chemical Biology, 22, 129–136. https://doi.org/10.1016/j.cbpa.2014.09.013.

    Article  PubMed  CAS  Google Scholar 

  6. Magliery, T. J. (2015). Protein stability: computation, sequence statistics, and new experimental methods. Current Opinion in Structural Biology, 33, 161–168. https://doi.org/10.1016/j.sbi.2015.09.002.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  7. Kulshreshtha, S., Chaudhary, V., Goswami, G. K., & Mathur, N. (2016). Computational approaches for predicting mutant protein stability. Journal of Computer-Aided Molecular Design, 30(5), 401–412. https://doi.org/10.1007/s10822-016-9914-3.

    Article  PubMed  CAS  Google Scholar 

  8. Baweja, M., Nain, L., Kawarabayasi, Y., & Shukla, P. (2016). Current technological improvements in enzymes toward their biotechnological applications. Frontiers in Microbiology, 7, 965. https://doi.org/10.3389/fmicb.2016.00965.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Anbar, M., Gul, O., Lamed, R., Sezerman, U. O., & Bayer, E. A. (2012). Improved thermostability of Clostridium thermocellum endoglucanase Cel8A by using consensus-guided mutagenesis. Applied and Environmental Microbiology, 78(9), 3458–3464. https://doi.org/10.1128/AEM.07985-11.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Ragauskas, A. J., Williams, C. K., Davison, B. H., Britovsek, G., Cairney, J., Eckert, C. A., Frederick, W. J., Hallett, J. P., Leak, D. J., Liotta, C. L., Mielenz, J. R., & Tschaplinski, T. (2006). The path forward for biofuels and biomaterials. Science, 311(5760), 484–489. https://doi.org/10.1126/science.1114736.

    Article  PubMed  CAS  Google Scholar 

  11. Brophy, J. A. N., & Voigt, C. A. (2014). Principles of genetic circuit design. Nature Methods, 11(5), 508–520. https://doi.org/10.1038/nmeth.2926.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Zheng, X., Xing, X.-H., & Zhang, C. (2017). Targeted mutagenesis: A sniper-like diversity generator in microbial engineering. Synthetic and Systems Biotechnology, 2(2), 75–86. https://doi.org/10.1016/j.synbio.2017.07.001.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Kingsley, L. J., & Lill, M. A. (2015). Substrate tunnels in enzymes: structure–function relationships and computational methodology. Proteins, 83(4), 599–611. https://doi.org/10.1002/prot.24772.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  14. Kuo, Y.-M., Henry, R. A., & Andrews, A. J. (2016). Measuring specificity in multi-substrate/product systems as a simple tool to investigate selectivity in vivo. Biochimica et Biophysica Acta, 1864(1), 70–76. https://doi.org/10.1016/j.bbapap.2015.08.011.

    Article  PubMed  CAS  Google Scholar 

  15. Samanta, S., & Mukherjee, S. (2017). Co-operative intra-protein structural response due to protein–protein complexation revealed through thermodynamic quantification: study of MDM2-p53 binding. Journal of Computer-Aided Molecular Design, 31(10), 891–903. https://doi.org/10.1007/s10822-017-0057-y.

    Article  PubMed  CAS  Google Scholar 

  16. Unterlass, J. E., Wood, R. J., Baslé, A., Tucker, J., Cano, C., Noble, M. M. E., & Curtin, N. J. (2017). Structural insights into the enzymatic activity and potential substrate promiscuity of human 3-phosphoglycerate dehydrogenase (PHGDH). Oncotarget, 8(61), 104478–104491. https://doi.org/10.18632/oncotarget.22327.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Jala, V. R., Appaji Rao, N., & Savithri, H. S. (2003). Identification of amino acid residues, essential for maintaining the tetrameric structure of sheep liver cytosolic serine hydroxymethyltransferase, by targeted mutagenesis. Biochemical Journal, 369(Pt 3), 469–476. https://doi.org/10.1042/BJ20021160.

    Article  PubMed Central  CAS  Google Scholar 

  18. Chatterjee, R., & Yuan, L. (2006). Directed evolution of metabolic pathways. Trends in Biotechnology, 24(1), 28–38. https://doi.org/10.1016/j.tibtech.2005.11.002.

    Article  PubMed  CAS  Google Scholar 

  19. Socha, R. D., & Tokuriki, N. (2013). Modulating protein stability—directed evolution strategies for improved protein function. FEBS Journal, 280(22), 5582–5595. https://doi.org/10.1111/febs.12354.

    Article  CAS  Google Scholar 

  20. Taylor, J. L., Price, J. E., & Toney, M. D. (2015). Directed evolution of the substrate specificity of dialkylglycine decarboxylase. Biochimica et Biophysica Acta, 1854(2), 146–155. https://doi.org/10.1016/j.bbapap.2014.12.003.

    Article  PubMed  CAS  Google Scholar 

  21. Ratananikom, K., Choengpanya, K., Tongtubtim, N., Charoenrat, T., Withers, S. G., & Kongsaeree, P. T. (2013). Mutational analysis in the glycone binding pocket of Dalbergia cochinchinensis β-glucosidase to increase catalytic efficiency toward mannosides. Carbohydrate Research, 373, 35–41. https://doi.org/10.1016/j.carres.2012.10.018.

    Article  PubMed  CAS  Google Scholar 

  22. Suarez, S. C., Beardslee, R. A., Toffton, S. M., & McCulloch, S. D. (2013). Biochemical analysis of active site mutations of human polymerase η. Mutation Research, 745–746, 46–54. https://doi.org/10.1016/j.mrfmmm.2013.03.001.

    Article  PubMed  CAS  Google Scholar 

  23. Khan, S., Pozzo, T., Megyeri, M., Lindahl, S., Sundin, A., Turner, C., & Karlsson, E. N. (2011). Aglycone specificity of Thermotoga neapolitana β-glucosidase 1A modified by mutagenesis, leading to increased catalytic efficiency in quercetin-3-glucoside hydrolysis. BMC Biochemistry, 12, 11. https://doi.org/10.1186/1471-2091-12-11.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. Weng, M., Zheng, Z., Bao, W., Cai, Y., Yin, Y., & Zou, G. (2009). Enhancement of oxidative stability of the subtilisin nattokinase by site-directed mutagenesis expressed in Escherichia coli. Biochimica et Biophysica Acta (BBA)-Proteins and Proteomics, 1794(11), 1566–1572. https://doi.org/10.1016/j.bbapap.2009.07.007.

    Article  CAS  Google Scholar 

  25. Kobayashi, J., Furukawa, M., Ohshiro, T., & Suzuki, H. (2015). Thermoadaptation-directed evolution of chloramphenicol acetyltransferase in an error-prone thermophile using improved procedures. Applied Microbiology and Biotechnology, 99(13), 5563–5572. https://doi.org/10.1007/s00253-015-6522-4.

    Article  PubMed  CAS  Google Scholar 

  26. Seo, J.-H., Kim, H.-H., Jeon, E.-Y., Song, Y.-H., Shin, C.-S., & Park, J.-B. (2016). Engineering of Baeyer–Villiger monooxygenase-based Escherichia coli biocatalyst for large scale biotransformation of ricinoleic acid into (Z)-11-(heptanoyloxy)undec-9-enoic acid. Scientific Reports. https://doi.org/10.1038/srep28223.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Capone, S., Ćorajević, L., Bonifert, G., Murth, P., Maresch, D., Altmann, F., Herwig, C., & Spadiut, O. (2015). Combining protein and strain engineering for the production of glyco-engineered horseradish peroxidase C1A in Pichia pastoris. International Journal of Molecular Sciences, 16(10), 23127–23142. https://doi.org/10.3390/ijms161023127.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Larue, K., Melgar, M., & Martin, V. J. J. (2016). Directed evolution of a fungal β-glucosidase in Saccharomyces cerevisiae. Biotechnology for Biofuels, 9. https://doi.org/10.1186/s13068-016-0470-9.

  29. Lian, J., Li, Y., HamediRad, M., & Zhao, H. (2014). Directed evolution of a cellodextrin transporter for improved biofuel production under anaerobic conditions in Saccharomyces cerevisiae. Biotechnology and Bioengineering, 111(8), 1521–1531. https://doi.org/10.1002/bit.25214.

    Article  PubMed  CAS  Google Scholar 

  30. Glenn, W. S., Nims, E., & O’Connor, S. E. (2011). Reengineering a tryptophan halogenase to preferentially chlorinate a direct alkaloid precursor. Journal of the American Chemical Society, 133(48), 19346–19349. https://doi.org/10.1021/ja2089348.

    Article  PubMed  CAS  Google Scholar 

  31. Jain, K., Warmack, R. A., Debler, E. W., Hadjikyriacou, A., Stavropoulos, P., & Clarke, S. G. (2016). Protein arginine methyltransferase product specificity is mediated by distinct active-site architectures. The Journal of Biological Chemistry, 291(35), 18299–18308. https://doi.org/10.1074/jbc.M116.740399.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Chiang, C.-H., Grauffel, C., Wu, L.-S., Kuo, P.-H., Doudeva, L. G., Lim, C., Shen, C. K., & Yuan, H. S. (2016). Structural analysis of disease-related TDP-43 D169G mutation: linking enhanced stability and caspase cleavage efficiency to protein accumulation. Scientific Reports, 6, 21581. https://doi.org/10.1038/srep21581.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  33. Cohen, I., Kayode, O., Hockla, A., Sankaran, B., Radisky, D. C., Radisky, E. S., & Papo, N. (2016). Combinatorial protein engineering of proteolytically resistant mesotrypsin inhibitors as candidates for cancer therapy. The Biochemical Journal, 473(10), 1329–1341. https://doi.org/10.1042/BJ20151410.

    Article  PubMed  CAS  Google Scholar 

  34. Clark, D. P., & Pazdernik, N. J. (2016). Chapter 11: Protein engineering. Boston: Academic Cell. (pp. 365–392)

    Google Scholar 

  35. Lv, B., Sun, H., Huang, S., Feng, X., Jiang, T., & Li, C. (2017). Structure-guided engineering of the substrate specificity of a fungal β-glucuronidase toward triterpenoid saponins. The Journal of Biological Chemistry, 293(2), 433–443. https://doi.org/10.1074/jbc.M117.801910.

    Article  PubMed  PubMed Central  Google Scholar 

  36. He, R., Reyes, A. C., Amyes, T. L., & Richard, J. P. (2018). Enzyme architecture: the role of a flexible loop in activation of glycerol-3-phosphate dehydrogenase for catalysis of hydride transfer. Biochemistry. https://doi.org/10.1021/acs.biochem.7b01282.

    Article  PubMed  Google Scholar 

  37. Reyes, A. C., Amyes, T. L., & Richard, J. P. (2016). Enzyme architecture: a startling role for Asn270 in glycerol 3-phosphate dehydrogenase-catalyzed hydride transfer. Biochemistry, 55(10), 1429–1432. https://doi.org/10.1021/acs.biochem.6b00116.

    Article  PubMed  CAS  Google Scholar 

  38. Gromiha, M. M. (2010). Chapter 6—protein stability. In Protein Bioinformatics (pp. 209–245). Singapore: Academic Press. https://doi.org/10.1016/B978-8-1312-2297-3.50006-0.

    Chapter  Google Scholar 

  39. Martínez Cuesta, S., Rahman, S. A., Furnham, N., & Thornton, J. M. (2015). The classification and evolution of enzyme function. Biophysical Journal, 109(6), 1082–1086. https://doi.org/10.1016/j.bpj.2015.04.020.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  40. Tsien, R. Y. (1998). The green fluorescent protein. Annual Review of Biochemistry, 67(1), 509–544. https://doi.org/10.1146/annurev.biochem.67.1.509.

    Article  PubMed  CAS  Google Scholar 

  41. Heim, R., & Tsien, R. Y. (1996). Engineering green fluorescent protein for improved brightness, longer wavelengths and fluorescence resonance energy transfer. Current Biology: CB, 6(2), 178–182.

    Article  CAS  PubMed  Google Scholar 

  42. Savile, C. K., Janey, J. M., Mundorff, E. C., Moore, J. C., Tam, S., Jarvis, W. R., Colbeck, J. C., Krebber, A., Fleitz, F. J., Brands, J., Devine, P. N., & Hughes, G. J. (2010). Biocatalytic asymmetric synthesis of chiral amines from ketones applied to sitagliptin manufacture. Science, 329(5989), 305–309. https://doi.org/10.1126/science.1188934.

    Article  PubMed  CAS  Google Scholar 

  43. Butterfield, G. L., Lajoie, M. J., Gustafson, H. H., Sellers, D. L., Nattermann, U., Ellis, D., Bale, J. B., Ke, S., Lenz, G. H., Yehdego, A., Ravichandran, R., & Baker, D. (2017). Evolution of a designed protein assembly encapsulating its own RNA genome. Nature, 552(7685), 415–420. https://doi.org/10.1038/nature25157.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  44. Kwong, P. D., & Mascola, J. R. (2018). HIV-1 vaccines based on antibody identification, B cell ontogeny, and epitope structure. Immunity, 48(5), 855–871. https://doi.org/10.1016/j.immuni.2018.04.029.

    Article  PubMed  CAS  Google Scholar 

  45. Olivera-Nappa, A., Andrews, B. A., & Asenjo, J. A. (2011). Mutagenesis Objective Search and Selection Tool (MOSST): an algorithm to predict structure-function related mutations in proteins. BMC Bioinformatics, 12(1), 122. https://doi.org/10.1186/1471-2105-12-122.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  46. Currin, A., Swainston, N., Day, P. J., & Kell, D. B. (2015). Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently. Chemical Society Reviews, 44(5), 1172–1239. https://doi.org/10.1039/C4CS00351A.

    Article  PubMed  CAS  Google Scholar 

  47. Tiwari, V. (2016). In vitro engineering of novel bioactivity in the natural enzymes. Frontiers in Chemistry, 4(39). https://doi.org/10.3389/fchem.2016.00039.

  48. Taylor, A. I., & Holliger, P. (2015). Directed evolution of artificial enzymes (XNAzymes) from diverse repertoires of synthetic genetic polymers. Nature Protocols, 10(10), 1625–1642. https://doi.org/10.1038/nprot.2015.104.

    Article  PubMed  CAS  Google Scholar 

  49. Dalby, P. A. (2011). Strategy and success for the directed evolution of enzymes. Current Opinion in Structural Biology, 21(4), 473–480. https://doi.org/10.1016/j.sbi.2011.05.003.

    Article  PubMed  CAS  Google Scholar 

  50. Tee, K. L., & Wong, T. S. (2013). Polishing the craft of genetic diversity creation in directed evolution. Biotechnology Advances, 31(8), 1707–1721. https://doi.org/10.1016/j.biotechadv.2013.08.021.

    Article  PubMed  CAS  Google Scholar 

  51. Bunzel, H. A., Garrabou, X., Pott, M., & Hilvert, D. (2018). Speeding up enzyme discovery and engineering with ultrahigh-throughput methods. Current Opinion in Structural Biology, 48, 149–156. https://doi.org/10.1016/j.sbi.2017.12.010.

    Article  PubMed  CAS  Google Scholar 

  52. Acevedo-Rocha, C. G., Hoebenreich, S., & Reetz, M. T. (2014). Iterative saturation mutagenesis: a powerful approach to engineer proteins by systematically simulating Darwinian evolution. Methods in Molecular Biology, 1179, 103–128. https://doi.org/10.1007/978-1-4939-1053-3_7.

    Article  PubMed  Google Scholar 

  53. Parra, L. P., Agudo, R., & Reetz, M. T. (2013). Directed evolution by using iterative saturation mutagenesis based on multiresidue sites. Chembiochem: A European Journal of Chemical Biology, 14(17), 2301–2309. https://doi.org/10.1002/cbic.201300486.

    Article  PubMed  CAS  Google Scholar 

  54. Cai, Y., Bhuiya, M.-W., Shanklin, J., & Liu, C.-J. (2015). Engineering a monolignol 4-O-methyltransferase with high selectivity for the condensed lignin precursor coniferyl alcohol. The Journal of Biological Chemistry, 290(44), 26715–26724. https://doi.org/10.1074/jbc.M115.684217.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  55. Chaparro-Riggers, J. F., Polizzi, K. M., & Bommarius, A. S. (2007). Better library design: data-driven protein engineering. Biotechnology Journal, 2(2), 180–191. https://doi.org/10.1002/biot.200600170.

    Article  PubMed  Google Scholar 

  56. What is Rosetta@home? (2018). Rosetta@home. Retrieved April 28, 2018 from https://boinc.bakerlab.org/rosetta/rah/rah_about.php.

  57. Niu, R.-J., Zheng, Q.-C., Zhang, J.-L., & Zhang, H.-X. (2013). Molecular dynamics simulations studies and free energy analysis on inhibitors of MDM2-p53 interaction. Journal of Molecular Graphics & Modelling, 46, 132–139. https://doi.org/10.1016/j.jmgm.2013.10.005.

    Article  CAS  Google Scholar 

  58. Chen, J., Wang, J., Zhang, Q., Chen, K., & Zhu, W. (2015). Probing origin of binding difference of inhibitors to MDM2 and MDMX by polarizable molecular dynamics simulation and QM/MM-GBSA calculation. Scientific Reports, 5, 17421. https://doi.org/10.1038/srep17421.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  59. Radchenko, T., Brink, A., Siegrist, Y., Kochansky, C., Bateman, A., Fontaine, F., Morettoni, L., & Zamora, I. (2017). Software-aided approach to investigate peptide structure and metabolic susceptibility of amide bonds in peptide drugs based on high resolution mass spectrometry. PLoS ONE, 12(11), e0186461. https://doi.org/10.1371/journal.pone.0186461.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  60. Zhang, L., Ai, H.-X., Li, S.-M., Qi, M.-Y., Zhao, J., Zhao, Q., & Liu, H.-S. (2017). Virtual screening approach to identifying influenza virus neuraminidase inhibitors using molecular docking combined with machine-learning-based scoring function. Oncotarget, 8(47), 83142–83154. https://doi.org/10.18632/oncotarget.20915.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Studer, R. A., Dessailly, B. H., & Orengo, C. A. (2013). Residue mutations and their impact on protein structure and function: detecting beneficial and pathogenic changes. Biochemical Journal, 449(3), 581–594. https://doi.org/10.1042/BJ20121221.

    Article  CAS  Google Scholar 

  62. Wójcikowski, M., Ballester, P. J., & Siedlecki, P. (2017). Performance of machine-learning scoring functions in structure-based virtual screening. Scientific Reports, 7, 46710. https://doi.org/10.1038/srep46710.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Alcalde, M. (2016). When directed evolution met ancestral enzyme resurrection. Microbial Biotechnology, 10(1), 22–24. https://doi.org/10.1111/1751-7915.12452.

    Article  PubMed  PubMed Central  Google Scholar 

  64. Wheeler, L. C., Lim, S. A., Marqusee, S., & Harms, M. J. (2016). The thermostability and specificity of ancient proteins. Current opinion in structural biology, 38, 37–43. https://doi.org/10.1016/j.sbi.2016.05.015.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  65. Gilis, D., & Rooman, M. (2000). PoPMuSiC, an algorithm for predicting protein mutant stability changes: application to prion proteins. Protein Engineering, 13(12), 849–856.

    Article  CAS  PubMed  Google Scholar 

  66. Dehouck, Y., Kwasigroch, J. M., Gilis, D., & Rooman, M. (2011). PoPMuSiC 2.1: a web server for the estimation of protein stability changes upon mutation and sequence optimality. BMC Bioinformatics, 12, 151. https://doi.org/10.1186/1471-2105-12-151.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Cabrita, L. D., Gilis, D., Robertson, A. L., Dehouck, Y., Rooman, M., & Bottomley, S. P. (2007). Enhancing the stability and solubility of TEV protease using in silico design. Protein Science, 16(11), 2360–2367. https://doi.org/10.1110/ps.072822507.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  68. Olivera-Nappa, A., Reyes, F., Andrews, B. A., & Asenjo, J. A. (2013). Cold adaptation, Ca2+ dependency and autolytic stability are related features in a highly active cold-adapted trypsin resistant to autoproteolysis engineered for biotechnological applications. PLoS ONE, 8(8). https://doi.org/10.1371/journal.pone.0072355.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Bedbrook, C. N., Rice, A. J., Yang, K. K., Ding, X., Chen, S., LeProust, E. M., Gradinaru, V., & Arnold, F. H. (2017). Structure-guided SCHEMA recombination generates diverse chimeric channelrhodopsins. Proceedings of the National Academy of Sciences of the United States of America, 114(13), E2624–E2633. https://doi.org/10.1073/pnas.1700269114.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  70. Bedbrook, C. N., Yang, K. K., Rice, A. J., Gradinaru, V., & Arnold, F. H. (2017). Machine learning to design integral membrane channel rhodopsins for efficient eukaryotic expression and plasma membrane localization. PLoS Computational Biology, 13(10), e1005786. https://doi.org/10.1371/journal.pcbi.1005786.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  71. Heinzelman, P., Snow, C. D., Smith, M. A., Yu, X., Kannan, A., Boulware, K., Villalobos, A., Govindarajan, S., Minshull, J., & Arnold, F. H. (2009). SCHEMA recombination of a fungal cellulase uncovers a single mutation that contributes markedly to stability. The Journal of Biological Chemistry, 284(39), 26229–26233. https://doi.org/10.1074/jbc.C109.034058.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  72. Pai, P. P., Ranjani, S. S. S., & Mondal, S. (2015). PINGU: PredIction of eNzyme catalytic residues usinG seqUence information. PLoS ONE, 10(8), e0135122. https://doi.org/10.1371/journal.pone.0135122.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  73. Ko, J., Murga, L. F., André, P., Yang, H., Ondrechen, M. J., Williams, R. J., Agunwamba, A., & Budil, D. E. (2005). Statistical criteria for the identification of protein active sites using theoretical microscopic titration curves. Proteins, 59(2), 183–195. https://doi.org/10.1002/prot.20418.

    Article  PubMed  CAS  Google Scholar 

  74. Tong, W., Williams, R. J., Wei, Y., Murga, L. F., Ko, J., & Ondrechen, M. J. (2008). Enhanced performance in prediction of protein active sites with THEMATICS and support vector machines. Protein Science: A Publication of the Protein Society, 17(2), 333–341. https://doi.org/10.1110/ps.073213608.

    Article  CAS  Google Scholar 

  75. Folding@home Fighting disease with a world wide distributed super computer. (n.d.). Retrieved from https://foldingathome.org/.

  76. Craveur, P., Joseph, A. P., Esque, J., Narwani, T. J., Noël, F., Shinada, N., Goguet, M., Sylvain, L., Poulain, P., & de Brevern, A. G. (2015). Protein flexibility in the light of structural alphabets. Frontiers in Molecular Biosciences. https://doi.org/10.3389/fmolb.2015.00020.

    Article  PubMed  PubMed Central  Google Scholar 

  77. Baneyx, F., & Mujacic, M. (2004). Recombinant protein folding and misfolding in Escherichia coli. Nature Biotechnology, 22(11), 1399–1408. https://doi.org/10.1038/nbt1029.

    Article  PubMed  CAS  Google Scholar 

  78. Collinet, B., Hervé, M., Pecorari, F., Minard, P., Eder, O., & Desmadril, M. (2000). Functionally accepted insertions of proteins within protein domains. Journal of Biological Chemistry, 275(23), 17428–17433. https://doi.org/10.1074/jbc.M000666200.

    Article  CAS  Google Scholar 

  79. Giri Rao, V. V. H., & Gosavi, S. (2018). On the folding of a structurally complex protein to its metastable active state. Proceedings of the National Academy of Sciences of the United States of America. https://doi.org/10.1073/pnas.1708173115.

    Article  PubMed  PubMed Central  Google Scholar 

  80. Alberts, B., Johnson, A., Lewis, J., Raff, M., Roberts, K., & Walter, P. (2002). Isolating, cloning, and sequencing DNA. In Molecular Biology of the Cell (4th ed.). New York: Garland Science.

    Google Scholar 

  81. Celie, P. H., Parret, A. H., & Perrakis, A. (2016). Recombinant cloning strategies for protein expression. Current Opinion in Structural Biology, 38, 145–154. https://doi.org/10.1016/j.sbi.2016.06.010.

    Article  PubMed  CAS  Google Scholar 

  82. Gilis, D., McLennan, H. R., Dehouck, Y., Cabrita, L. D., Rooman, M., & Bottomley, S. P. (2003). In vitro and in silico design of α1-antitrypsin mutants with different conformational stabilities. Journal of Molecular Biology, 325(3), 581–589. https://doi.org/10.1016/S0022-2836(02)01221-4.

    Article  PubMed  CAS  Google Scholar 

  83. Addgene: Choosing a molecular cloning technique. (n.d.). Retrieved October 10, 2017, from https://www.addgene.org/plasmid-reference/cloning-choice/.

  84. Applications|NEB. (n.d.). Retrieved October 13, 2017, from https://www.neb.com/applications.

  85. Protein Expression and Purification Core Facility—Cloning—Cloning Methods—EMBL. (n.d.). Retrieved October 10, 2017, from https://www.embl.de/pepcore/pepcore_services/cloning/cloning_methods/index.html.

  86. Gibson, D. G. (2009). Synthesis of DNA fragments in yeast by one-step assembly of overlapping oligonucleotides. Nucleic Acids Research, 37(20), 6984–6990. https://doi.org/10.1093/nar/gkp687.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  87. Poluri, K. M., & Gulati, K. (2017). Protein engineering techniques: Gateways to synthetic protein universe. Springer, Singapore. Retrieved from http://www.springer.com/gp/book/9789811027314.

  88. Arnold, F. H., & Georgiou, G. (Eds.)., (2003). Directed evolution library creation: methods and protocols. Humana Press, New York. Retrieved from http://www.springer.com/gp/book/9781588292858.

  89. Stemmer, W. P. (1994). DNA shuffling by random fragmentation and reassembly: in vitro recombination for molecular evolution. Proceedings of the National Academy of Sciences of the United States of America, 91(22), 10747–10751.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Moore, G. L., & Maranas, C. D. (2002). eCodonOpt: a systematic computational framework for optimizing codon usage in directed evolution experiments. Nucleic Acids Research, 30(11), 2407–2416.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Packer, M. S., & Liu, D. R. (2015). Methods for the directed evolution of proteins. Nature Reviews Genetics, 16(7), 379. https://doi.org/10.1038/nrg3927.

    Article  PubMed  CAS  Google Scholar 

  92. Müller, K. M., Stebel, S. C., Knall, S., Zipf, G., Bernauer, H. S., & Arndt, K. M. (2005). Nucleotide exchange and excision technology (NExT) DNA shuffling: a robust method for DNA fragmentation and directed evolution. Nucleic Acids Research, 33(13), e117. https://doi.org/10.1093/nar/gni116.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  93. Sieber, V., Martinez, C. A., & Arnold, F. H. (2001). Libraries of hybrid proteins from distantly related sequences. Nature Biotechnology, 19(5), 456–460. https://doi.org/10.1038/88129.

    Article  PubMed  CAS  Google Scholar 

  94. Gonzalez-Perez, D., Garcia-Ruiz, E., & Alcalde, M. (2012). Saccharomyces cerevisiae in directed evolution. Bioengineered Bugs, 3(3), 172–177. https://doi.org/10.4161/bbug.19544.

    Article  PubMed  PubMed Central  Google Scholar 

  95. Böttcher, D., & Bornscheuer, U. T. (2010). Protein engineering of microbial enzymes. Current Opinion in Microbiology, 13(3), 274–282. https://doi.org/10.1016/j.mib.2010.01.010.

    Article  PubMed  CAS  Google Scholar 

  96. Lutz, S., Ostermeier, M., Moore, G. L., Maranas, C. D., & Benkovic, S. J. (2001). Creating multiple-crossover DNA libraries independent of sequence identity. Proceedings of the National Academy of Sciences, 98(20), 11248–11253. https://doi.org/10.1073/pnas.201413698.

    Article  CAS  Google Scholar 

  97. Murakami, H., Hohsaka, T., & Sisido, M. (2002). Random insertion and deletion of arbitrary number of bases for codon-based random mutation of DNAs. Nature Biotechnology, 20(1), 76–81. https://doi.org/10.1038/nbt0102-76.

    Article  PubMed  CAS  Google Scholar 

  98. Tseng, W.-C., Lin, J.-W., Wei, T.-Y., & Fang, T.-Y. (2008). A novel megaprimed and ligase-free, PCR-based, site-directed mutagenesis method. Analytical Biochemistry, 375(2), 376–378. https://doi.org/10.1016/j.ab.2007.12.013.

    Article  PubMed  CAS  Google Scholar 

  99. Lee, S. H., Ryu, E. J., Kang, M. J., Wang, E.-S., Piao, Z., Choi, Y. J., Jung, K. H., Jeon, J. Y., & Shin, Y. C. (2003). A new approach to directed gene evolution by recombined extension on truncated templates (RETT). Journal of Molecular Catalysis B: Enzymatic, 26(3), 119–129. https://doi.org/10.1016/j.molcatb.2003.05.001.

    Article  CAS  Google Scholar 

  100. Frauenkron-Machedjou, V. J., Fulton, A., Zhu, L., Anker, C., Bocola, M., Jaeger, K.-E., & Schwaneberg, U. (2015). Towards understanding directed evolution: more than half of all amino acid positions contribute to ionic liquid resistance of Bacillus subtilis lipase A. ChemBioChem, 16(6), 937–945. https://doi.org/10.1002/cbic.201402682.

    Article  PubMed  CAS  Google Scholar 

  101. Johnston, C. A., Whitney, D. S., Volkman, B. F., Doe, C. Q., & Prehoda, K. E. (2011). Conversion of the enzyme guanylate kinase into a mitotic-spindle orienting protein by a single mutation that inhibits GMP-induced closing. Proceedings of the National Academy of Sciences of the United States of America, 108(44), E973–E978. https://doi.org/10.1073/pnas.1104365108.

    Article  PubMed  PubMed Central  Google Scholar 

  102. Woods, D. F., & Bryant, P. J. (1993). ZO-1, DlgA and PSD-95/SAP90: homologous proteins in tight, septate and synaptic cell junctions. Mechanisms of Development, 44(2), 85–89. https://doi.org/10.1016/0925-4773(93)90059-7.

    Article  PubMed  CAS  Google Scholar 

  103. Wyganowski, K. T., Kaltenbach, M., & Tokuriki, N. (2013). GroEL/ES buffering and compensatory mutations promote protein evolution by stabilizing folding intermediates. Journal of Molecular Biology, 425(18), 3403–3414. https://doi.org/10.1016/j.jmb.2013.06.028.

    Article  PubMed  CAS  Google Scholar 

  104. Rehm, F. B. H., Chen, S., & Rehm, B. H. A. (2016). Enzyme engineering for in situ immobilization. Molecules, 21(10). https://doi.org/10.3390/molecules21101370.

    Article  CAS  PubMed Central  Google Scholar 

  105. Singh, R. K., Tiwari, M. K., Singh, R., & Lee, J.-K. (2013). From protein engineering to immobilization: promising strategies for the upgrade of industrial enzymes. International Journal of Molecular Sciences, 14(1), 1232–1277. https://doi.org/10.3390/ijms14011232.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  106. Greenfield, N. J. (2006). Using circular dichroism spectra to estimate protein secondary structure. Nature protocols, 1(6), 2876–2890. https://doi.org/10.1038/nprot.2006.202.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  107. Na, Y.-R., & Park, C. (2009). Investigating protein unfolding kinetics by pulse proteolysis. Protein Science: A Publication of the Protein Society, 18(2), 268–276. https://doi.org/10.1002/pro.29.

    Article  CAS  Google Scholar 

  108. Dutta, A. K., Rösgen, J., & Rajarathnam, K. (2015). Using isothermal titration calorimetry to determine thermodynamic parameters of protein–glycosaminoglycan interactions. Methods in Molecular Biology. (Clifton, N.J.), 1229, 315–324. https://doi.org/10.1007/978-1-4939-1714-3_25.

    Article  CAS  Google Scholar 

  109. Penner, M. H. (2010). Ultraviolet, visible, and fluorescence spectroscopy. In Food Analysis (pp. 387–405). Boston: Springer. https://doi.org/10.1007/978-1-4419-1478-1_22.

    Chapter  Google Scholar 

  110. Concepts and Principles of High Performance Liquid Chromatography. (2006). In HPLC in Enzymatic Analysis (pp. 13–40). Wiley, New York. https://doi.org/10.1002/9780470110591.ch2.

    Book  Google Scholar 

  111. Uribe, S., & Sampedro, J. G. (2003). Measuring solution viscosity and its effect on enzyme activity. Biological Procedures Online, 5, 108–115. https://doi.org/10.1251/bpo52.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  112. de Boer, A. R., Lingeman, H., Niessen, W. M. A., & Irth, H. (2007). Mass spectrometry-based biochemical assays for enzyme-inhibitor screening. TrAC Trends in Analytical Chemistry, 26(9), 867–883. https://doi.org/10.1016/j.trac.2007.08.004.

    Article  CAS  Google Scholar 

  113. Lisi, G. P., & Loria, J. P. (2016). Solution NMR spectroscopy for the study of enzyme allostery. Chemical Reviews, 116(11), 6323–6369. https://doi.org/10.1021/acs.chemrev.5b00541.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  114. Lorber, B., Fischer, F., Bailly, M., Roy, H., & Kern, D. (2012). Protein analysis by dynamic light scattering: methods and techniques for students. Biochemistry and Molecular Biology Education: A Bimonthly Publication of the International Union of Biochemistry and Molecular Biology, 40(6), 372–382. https://doi.org/10.1002/bmb.20644.

    Article  CAS  Google Scholar 

  115. Gast, K., & Fiedler, C. (2012). Dynamic and static light scattering of intrinsically disordered proteins. Methods in Molecular Biology (Clifton, N.J.), 896, 137–161. https://doi.org/10.1007/978-1-4614-3704-8_9.

    Article  CAS  Google Scholar 

  116. Kuznetsova, E., Proudfoot, M., Sanders, S. A., Reinking, J., Savchenko, A., Arrowsmith, C. H., Edwards, A. M., & Yakunin, A. F. (2005). Enzyme genomics: Application of general enzymatic screens to discover new enzymes. FEMS Microbiology Reviews, 29(2), 263–279. https://doi.org/10.1016/j.fmrre.2004.12.006.

    Article  PubMed  CAS  Google Scholar 

  117. Acker, M. G., & Auld, D. S. (2014). Considerations for the design and reporting of enzyme assays in high-throughput screening applications. Perspectives in Science, 1(1), 56–73. https://doi.org/10.1016/j.pisc.2013.12.001.

    Article  Google Scholar 

  118. Gasymov, O. K., Abduragimov, A. R., & Glasgow, B. J. (2014). Probing tertiary structure of proteins using single trp mutations with circular dichroism at low temperature. The Journal of Physical Chemistry. B, 118(4), 986–995. https://doi.org/10.1021/jp4120145.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  119. Holthauzen, L. M. F., Auton, M., Sinev, M., & Rösgen, J. (2011). Protein stability in the presence of cosolutes. Methods in Enzymology, 492, 61–125. https://doi.org/10.1016/B978-0-12-381268-1.00015-X.

    Article  PubMed  CAS  Google Scholar 

  120. Monera, O. D., Kay, C. M., & Hodges, R. S. (1994). Protein denaturation with guanidine hydrochloride or urea provides a different estimate of stability depending on the contributions of electrostatic interactions. Protein Science: A Publication of the Protein Society, 3(11), 1984–1991.

    Article  CAS  Google Scholar 

  121. Li Li, A. Kantor, & Nicholas Warne. (2013). Application of a PEG precipitation method for solubility screening: A tool for developing high protein concentration formulations. Protein Science, 22(8), 1118–1123.

    Article  CAS  PubMed  Google Scholar 

  122. Roodveldt, C., & Tawfik, D. S. (2005). Directed evolution of phosphotriesterase from Pseudomonas diminuta for heterologous expression in Escherichia coli results in stabilization of the metal-free state. Protein Engineering Design and Selection, 18(1), 51–58. https://doi.org/10.1093/protein/gzi005.

    Article  CAS  Google Scholar 

  123. Polson, A., Potgieter, G. M., Largier, J. F., Mears, G. E. F., & Joubert, F. J. (1964). The fractionation of protein mixtures by linear polymers of high molecular weight. Biochimica et Biophysica Acta (BBA)—General Subjects, 82(3), 463–475. https://doi.org/10.1016/0304-4165(64)90438-6.

    Article  CAS  Google Scholar 

  124. Klinman, J. P., Offenbacher, A. R., & Hu, S. (2017). Origins of enzyme catalysis: experimental findings for C–H activation, new models, and their relevance to prevailing theoretical constructs. Journal of the American Chemical Society, 139(51), 18409–18427. https://doi.org/10.1021/jacs.7b08418.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  125. Schnell, S. (2014). Validity of the Michaelis–Menten equation–steady-state or reactant stationary assumption: that is the question. The FEBS Journal, 281(2), 464–472. https://doi.org/10.1111/febs.12564.

    Article  PubMed  CAS  Google Scholar 

  126. Xu, R., Gu, E., Zhou, Q., Yuan, L., Hu, X., Cai, J., & Hu, G. (2016). Effects of 22 novel CYP2D6 variants found in Chinese population on the metabolism of dapoxetine. Drug Design, Development and Therapy, 10, 687–696. https://doi.org/10.2147/DDDT.S97789.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  127. Cornish-Bowden, A. (2013). The origins of enzyme kinetics. FEBS Letters, 587(17), 2725–2730. https://doi.org/10.1016/j.febslet.2013.06.009.

    Article  PubMed  CAS  Google Scholar 

  128. Eliot, A. C., & Kirsch, J. F. (2004). Pyridoxal phosphate enzymes: mechanistic, structural, and evolutionary considerations. Annual Review of Biochemistry, 73(1), 383–415. https://doi.org/10.1146/annurev.biochem.73.011303.074021.

    Article  PubMed  CAS  Google Scholar 

  129. Catazaro, J., Caprez, A., Guru, A., Swanson, D., & Powers, R. (2014). Functional evolution of PLP-dependent enzymes based on active-site structural similarities. Proteins, 82(10), 2597–2608. https://doi.org/10.1002/prot.24624.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  130. Yoshimura, T., Jhee, K. H., & Soda, K. (1996). Stereospecificity for the hydrogen transfer and molecular evolution of pyridoxal enzymes. Bioscience, Biotechnology, and Biochemistry, 60(2), 181–187. https://doi.org/10.1271/bbb.60.181.

    Article  PubMed  CAS  Google Scholar 

  131. Schaefer, M., Pollex, T., Hanna, K., Tuorto, F., Meusburger, M., Helm, M., & Lyko, F. (2010). RNA methylation by Dnmt2 protects transfer RNAs against stress-induced cleavage. Genes & Development, 24(15), 1590–1595. https://doi.org/10.1101/gad.586710.

    Article  CAS  Google Scholar 

  132. Rose, N. R., & Klose, R. J. (2014). Understanding the relationship between DNA methylation and histone lysine methylation. Biochimica et Biophysica Acta (BBA)—Gene Regulatory Mechanisms, 1839(12), 1362–1372. https://doi.org/10.1016/j.bbagrm.2014.02.007.

    Article  CAS  Google Scholar 

  133. Jaenisch, R., & Bird, A. (2003). Epigenetic regulation of gene expression: how the genome integrates intrinsic and environmental signals. Nature Genetics, 33, 245–254. https://doi.org/10.1038/ng1089.

    Article  PubMed  CAS  Google Scholar 

  134. Tessarz, P., & Kouzarides, T. (2014). Histone core modifications regulating nucleosome structure and dynamics. Nature Reviews Molecular Cell Biology, 15(11), 703–708. https://doi.org/10.1038/nrm3890.

    Article  PubMed  CAS  Google Scholar 

  135. Collins, R. E., Tachibana, M., Tamaru, H., Smith, K. M., Jia, D., Zhang, X., Selker, E. U., Shinkai, Y., & Cheng, X. (2005). In vitro and in vivo analyses of a Phe/Tyr switch controlling product specificity of histone lysine methyltransferases. The Journal of Biological Chemistry, 280(7), 5563–5570. https://doi.org/10.1074/jbc.M410483200.

    Article  PubMed  CAS  Google Scholar 

  136. Rathert, P., Zhang, X., Freund, C., Cheng, X., & Jeltsch, A. (2008). Analysis of the substrate specificity of the Dim-5 histone lysine methyltransferase using peptide arrays. Chemistry & Biology, 15(1), 5–11. https://doi.org/10.1016/j.chembiol.2007.11.013.

    Article  CAS  Google Scholar 

  137. Couture, J.-F., Collazo, E., Brunzelle, J. S., & Trievel, R. C. (2005). Structural and functional analysis of SET8, a histone H4 Lys-20 methyltransferase. Genes & Development, 19(12), 1455–1465. https://doi.org/10.1101/gad.1318405.

    Article  CAS  Google Scholar 

  138. Xiao, B., Jing, C., Kelly, G., Walker, P. A., Muskett, F. W., Frenkiel, T. A., Martin, S. R., Sarma, K., Reinberg, D., Gamblin, S. J., & Wilson, J. R. (2005). Specificity and mechanism of the histone methyltransferase Pr-Set7. Genes & Development, 19(12), 1444–1454. https://doi.org/10.1101/gad.1315905.

    Article  CAS  Google Scholar 

  139. Wu, H., Siarheyeva, A., Zeng, H., Lam, R., Dong, A., Wu, X.-H., Li, Y., Schapira, M., Vedadi, M., & Min, J. (2013). Crystal structures of the human histone H4K20 methyltransferases SUV420H1 and SUV420H2. FEBS Letters, 587(23), 3859–3868. https://doi.org/10.1016/j.febslet.2013.10.020.

    Article  PubMed  CAS  Google Scholar 

  140. Wilson, J. R., Jing, C., Walker, P. A., Martin, S. R., Howell, S. A., Blackburn, G. M., Gamblin, S. J., & Xiao, B. (2002). Crystal structure and functional analysis of the histone methyltransferase SET7/9. Cell, 111(1), 105–115. https://doi.org/10.1016/S0092-8674(02)00964-9.

    Article  PubMed  CAS  Google Scholar 

  141. Zhang, X., Yang, Z., Khan, S. I., Horton, J. R., Tamaru, H., Selker, E. U., & Cheng, X. (2003). Structural basis for the product specificity of histone lysine methyltransferases. Molecular Cell, 12(1), 177–185. https://doi.org/10.1016/S1097-2765(03)00224-7.

    Article  PubMed  PubMed Central  Google Scholar 

  142. Zhang, X., Tamaru, H., Khan, S. I., Horton, J. R., Keefe, L. J., Selker, E. U., & Cheng, X. (2002). Structure of the neurospora SET domain protein DIM-5, a histone H3 lysine methyltransferase. Cell, 111(1), 117–127. https://doi.org/10.1016/S0092-8674(02)00999-6.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  143. Trievel, R. C. (2004). Structure and function of histone methyltransferases. Critical Reviews in Eukaryotic Gene Expression, 14(3), 147–169. https://doi.org/10.1615/CritRevEukaryotGeneExpr.v14.i3.10.

    Article  PubMed  CAS  Google Scholar 

  144. Qian, C., & Zhou, M.-M. (2006). SET domain protein lysine methyltransferases: Structure, specificity and catalysis. Cellular and Molecular Life Sciences CMLS, 63(23), 2755–2763. https://doi.org/10.1007/s00018-006-6274-5.

    Article  PubMed  CAS  Google Scholar 

  145. Dillon, S. C., Zhang, X., Trievel, R. C., & Cheng, X. (2005). The SET-domain protein superfamily: protein lysine methyltransferases. Genome Biology, 6(8), 227. https://doi.org/10.1186/gb-2005-6-8-227.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  146. Kudithipudi, S., Dhayalan, A., Kebede, A. F., & Jeltsch, A. (2012). The SET8 H4K20 protein lysine methyltransferase has a long recognition sequence covering seven amino acid residues. Biochimie, 94(11), 2212–2218. https://doi.org/10.1016/j.biochi.2012.04.024.

    Article  PubMed  CAS  Google Scholar 

  147. Qian, C., Wang, X., Manzur, K., Sachchidanand, A. F., Zeng, L., & Zhou, M.-M. (2006). Structural insights of the specificity and catalysis of a viral histone H3 lysine 27 methyltransferase. Journal of Molecular Biology, 359(1), 86–96. https://doi.org/10.1016/j.jmb.2006.03.006.

    Article  PubMed  CAS  Google Scholar 

  148. Dhayalan, A., Kudithipudi, S., Rathert, P., & Jeltsch, A. (2011). Specificity analysis-based identification of new methylation targets of the SET7/9 protein lysine methyltransferase. Chemistry & Biology, 18(1), 111–120. https://doi.org/10.1016/j.chembiol.2010.11.014.

    Article  CAS  Google Scholar 

  149. Mozzetta, C., Pontis, J., Fritsch, L., Robin, P., Portoso, M., Proux, C., Margueron, R., & Ait-Si-Ali, S. (2014). The histone H3 lysine 9 methyltransferases G9a and GLP regulate polycomb repressive complex 2-mediated gene silencing. Molecular Cell, 53(2), 277–289. https://doi.org/10.1016/j.molcel.2013.12.005.

    Article  PubMed  CAS  Google Scholar 

  150. West, L. E., Roy, S., Lachmi-Weiner, K., Hayashi, R., Shi, X., Appella, E., Kutateladze, T. J., & Gozani, O. (2010). The MBT repeats of L3MBTL1 link SET8-mediated p53 methylation at lysine 382 to target gene repression. Journal of Biological Chemistry, 285(48), 37725–37732. https://doi.org/10.1074/jbc.M110.139527.

    Article  CAS  Google Scholar 

  151. Zhang, Y., Ye, J., & Liu, M. (2017). Enantioselective biotransformation of chiral persistent organic pollutants. Current Protein & Peptide Science, 18(1), 48–56.

    Article  CAS  Google Scholar 

  152. Guo, F., Zhang, J., & Wang, C. (2017). Enantioselectivity in environmental safety and metabolism of typical chiral organic pollutants. Current Protein & Peptide Science, 18(1), 4–9.

    Article  CAS  Google Scholar 

  153. Golub, M., Lehofer, B., Martinez, N., Ollivier, J., Kohlbrecher, J., Prassl, R., & Peters, J. (2017). High hydrostatic pressure specifically affects molecular dynamics and shape of low-density lipoprotein particles. Scientific Reports, 7, 46034. https://doi.org/10.1038/srep46034.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  154. Makarov, A. A., Helmy, R., Joyce, L., Reibarkh, M., Maust, M., Ren, S., Mergelsberg, I., & Welch, C. J. (2016). Use of hydrostatic pressure for modulation of protein chemical modification and enzymatic selectivity. Organic & Biomolecular Chemistry, 14(19), 4448–4455. https://doi.org/10.1039/C6OB00550K.

    Article  CAS  Google Scholar 

  155. Didier, R. (2000). Understanding and Engineering the Enantioselectivity of Candida antarctica Lipase B towards sec-Alcohols (Thesis). KTH Royal Institute of Technology, Stockholm.

    Google Scholar 

  156. Boersma, Y. L., Dröge, M. J., van der Sloot, A. M., Pijning, T., Cool, R. H., Dijkstra, B. W., & Quax, W. J. (2008). A novel genetic selection system for improved enantioselectivity of Bacillus subtilis lipase A. ChemBioChem, 9(7), 1110–1115. https://doi.org/10.1002/cbic.200700754.

    Article  PubMed  CAS  Google Scholar 

  157. Xiao, H., Bao, Z., & Zhao, H. (2015). High throughput screening and selection methods for directed enzyme evolution. Industrial & Engineering Chemistry Research, 54(16), 4011–4020. https://doi.org/10.1021/ie503060a.

    Article  CAS  Google Scholar 

  158. Zhang, C., Kenski, D. M., Paulson, J. L., Bonshtien, A., Sessa, G., Cross, J. V., Templeton, D. J., & Shokat, K. M. (2005). A second-site suppressor strategy for chemical genetic analysis of diverse protein kinases. Nature Methods, 2(6), 435–441. https://doi.org/10.1038/nmeth764.

    Article  PubMed  CAS  Google Scholar 

  159. Jimenez-Rosales, A. (2015). Methyltransferases as bioorthogonal labeling tools for proteins (PhD thesis). The University of Manchester, Manchester, United Kingdom.

    Google Scholar 

  160. Allen, J. J., Lazerwith, S. E., & Shokat, K. M. (2005). Bio-orthogonal affinity purification of direct kinase substrates. Journal of the American Chemical Society, 127(15), 5288–5289. https://doi.org/10.1021/ja050727t.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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Acknowledgements

We thank Jason Micklefield, Binuraj R. K. Menon, Anna-Winona Struck, Matthew Bennett, Mark Thomson and Brian Law for their support on the research work by Ph.D. Jimenez-Rosales at the University of Manchester. We also gratefully acknowledge financial support from both CONACYT scholarship 310271 and to SEP-PRODEP 511-6/17-9932.

Funding

This work was supported by CONACYT doctoral funding 310271 and SEP-PRODEP award 511-6/17-9932 postdoctoral funding 993201.

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Jimenez-Rosales, A., Flores-Merino, M.V. Tailoring Proteins to Re-Evolve Nature: A Short Review. Mol Biotechnol 60, 946–974 (2018). https://doi.org/10.1007/s12033-018-0122-3

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