Abstract
Structural engineering of the recombinant thrombolytic drug, Reteplase, and its cost-effective production are important goals in the pharmaceutical industry. In this study, a single-point mutant of the protein was rationally designed and evaluated in terms of physicochemical characteristics, enzymatic activity, as well as large-scale production settings. An accurate homology model of Reteplase was used as the input to appropriate tools to identify the aggregation-prone sites, while considering the structural stability. Selected variants underwent extensive molecular dynamic simulations (total 540 ns) to assess their solvation profile and their thermal stability. The Reteplase-fibrin interaction was investigated by docking. The best variant was expressed in E. coli, and Box-Behnken design was used through response surface methodology to optimize its expression conditions. M72R mutant demonstrated appropriate stability, enhanced enzymatic activity (p < 0.05), and strengthened binding to fibrin, compared to the wild type. The optimal conditions for the variant’s production in a bioreactor was shown to be 37 ºC, induction with 0.5 mM IPTG, for 2 h of incubation. Under these conditions, the final amount of the produced enzyme was increased by about 23 mg/L compared to the wild type, with an increase in the enzymatic activity by about 2 IU/mL. This study thus offered a new Reteplase variant with nearly all favorable properties, except solubility. The impact of temperature and incubation time on its large-scale production were underlined as well.
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References
Adivitiya, Khasa YP (2017) The evolution of recombinant thrombolytics: current status and future directions. Bioengineered 8(4):331–358. https://doi.org/10.1080/21655979.2016.1229718
Assenberg R, Wan PT et al (2013) Advances in recombinant protein expression for use in pharmaceutical research. Curr Opin Struct Biol 23(3):393–402. https://doi.org/10.1016/j.sbi.2013.03.008
Baker NA, Sept D et al (2001) Electrostatics of nanosystems: application to microtubules and the ribosome. Proc Natl Acad Sci 98(18):10037–10041. https://doi.org/10.1073/pnas.181342398
Bezerra MA, Santelli RE et al (2008) Response surface methodology (RSM) as a tool for optimization in analytical chemistry. Talanta 76(5):965–977. https://doi.org/10.1016/j.talanta.2008.05.019
Cabrita LD, Gilis D et al (2007) Enhancing the stability and solubility of TEV protease using in silico design. Protein Sci 16(11):2360–2367. https://doi.org/10.1110/ps.072822507
Chen X, Li Y et al (2005) Application of response surface methodology in medium optimization for spore production of Coniothyrium minitans in solid-state fermentation. World J Microbiol Biotechnol 21(4):593–599. https://doi.org/10.1007/s11274-004-3492-6
Chester KW, Corrigan M et al (2019) Making a case for the right ‘-ase’in acute ischemic stroke: alteplase, tenecteplase, and reteplase. Expert Opin Drug Saf 18(2):87–96. https://doi.org/10.1080/14740338.2019.1573985
de Groot NS, Ventura S (2006) Effect of temperature on protein quality in bacterial inclusion bodies. FEBS Lett 580(27):6471–6476. https://doi.org/10.1016/j.febslet.2006.10.071
Dehouck, Y., Kwasigroch, J. M., et al. (2011). PoPMuSiC 2.1: a web server for the estimation of protein stability changes upon mutation and sequence optimality. BMC bioinformatics, 12(1), 1–12. https://doi.org/10.1186/1471-2105-12-151
Eisenberg D, Lüthy R et al (1997) VERIFY3D: assessment of protein models with three-dimensional profiles. Methods Enzymol 277:396–404. https://doi.org/10.1016/S0076-6879(97)77022-8
Esmaili I, Sadeghi HMM et al (2018) Effect of buffer additives on solubilization and refolding of reteplase inclusion bodies. Res Pharm Sci 13(5):413. https://doi.org/10.4103/1735-5362.236834
Ghaheh HS, Ganjalikhany MR et al (2019) Improving the solubility, activity, and stability of reteplase using in silico design of new variants. Res Pharm Sci 14(4):359. https://doi.org/10.4103/1735-5362.263560
Ghaheh HS, Ganjalikhany MR et al (2020) Investigation of supercharging as a strategy to enhance the solubility and plasminogen cleavage activity of Reteplase. Iran J Biotechnol 18(4):56. https://doi.org/10.30498/IJB.2020.2556
Gil-Garcia M, Bano-Polo M et al (2018) Combining structural aggregation propensity and stability predictions to redesign protein solubility. Mol Pharm 15(9):3846–3859. https://doi.org/10.1021/acs.molpharmaceut.8b00341
Gupta, S. K., Dangi, A. K., et al. (2019). Effectual bioprocess development for protein production. In Applied microbiology and bioengineering (pp. 203–227): Elsevier. https://doi.org/10.1016/B978-0-12-815407-6.00011-3
Gutiérrez-González M, Farías C et al (2019) Optimization of culture conditions for the expression of three different insoluble proteins in Escherichia coli. Sci Rep 9(1):1–11. https://doi.org/10.1038/s41598-019-53200-7
Hudson NE (2017) Biophysical mechanisms mediating fibrin fiber lysis. Biomed Res Int. https://doi.org/10.1155/2017/2748340
Kumar CV, Swetha RG et al (2014) Computational analysis reveals the association of threonine 118 methionine mutation in PMP22 resulting in CMT-1A. Adv Bioinform. https://doi.org/10.1155/2014/502618
Laskowski RA, MacArthur MW et al (1993) PROCHECK: a program to check the stereochemical quality of protein structures. J Appl Crystallogr 26(2):283–291. https://doi.org/10.1107/S0021889892009944
Lu G, Moriyama EN (2004) Vector NTI, a balanced all-in-one sequence analysis suite. Brief Bioinform 5(4):378–388. https://doi.org/10.1093/bib/5.4.378
Malik A, Alsenaidy AM et al (2016) Optimization of expression and purification of HSPA6 protein from Camelus dromedarius in E. coli. Saudi J Biol Sci 23(3):410–419. https://doi.org/10.1016/j.sjbs.2015.04.017
McNeil B, Harvey L (2008) Practical fermentation technology. Wiley, New York
Mohammadi E, Mahnam K et al (2021) Design and production of new chimeric reteplase with enhanced fibrin affinity: a theoretical and experimental study. J Biomol Struct Dyn 39(4):1321–1333. https://doi.org/10.1080/07391102.2020.1729865
Mosavi LK, Peng ZY (2003) Structure-based substitutions for increased solubility of a designed protein. Protein Eng 16(10):739–745. https://doi.org/10.1093/protein/gzg098
Nemaysh V, Luthra PM (2017) Computational analysis revealing that K634 and T681 mutations modulate the 3D-structure of PDGFR-β and lead to sunitinib resistance. RSC Adv 7(60):37612–37626. https://doi.org/10.1039/C7RA01305A
Nordt TK, Bode C (2003) Thrombolysis: newer thrombolytic agents and their role in clinical medicine. Heart 89(11):1358–1362. https://doi.org/10.1136/heart.89.11.1358
Osire T, Yang T et al (2019) Lys-Arg mutation improved the thermostability of Bacillus cereus neutral protease through increased residue interactions. World J Microbiol Biotechnol 35(11):1–11. https://doi.org/10.1007/s11274-019-2751-5
Pires DE, Ascher DB et al (2014) DUET: a server for predicting effects of mutations on protein stability using an integrated computational approach. Nucleic Acids Res 42(W1):W314–W319. https://doi.org/10.1093/nar/gku411
Ramirez O, Zamora R et al (1994) Kinetic study of penicillin acylase production by recombinant E. coli in batch cultures. Process Biochem 29(3):197–206. https://doi.org/10.1016/0032-9592(94)85004-6
Sadeghi HMM, Rabbani M et al (2011) Optimization of the expression of reteplase in Escherichia coli. Res Pharm Sci 6(2):87
Sadrjavadi K, Barzegari E et al (2020) Interactions of insulin with tragacanthic acid biopolymer: Experimental and computational study. Int J Biol Macromol 164:321–330. https://doi.org/10.1016/j.ijbiomac.2020.07.122
Shafiee F, Rabbani M et al (2017) Optimization of the expression of DT386-BR2 fusion protein in Escherichia coli using response surface methodology. Adv Biomed Res. https://doi.org/10.4103/2277-9175.201334
Sinha R, Shukla P (2019) Current trends in protein engineering: updates and progress. Curr Protein Pept Sci 20(5):398–407. https://doi.org/10.2174/1389203720666181119120120
Sokalingam S, Raghunathan G et al (2012) A study on the effect of surface lysine to arginine mutagenesis on protein stability and structure using green fluorescent protein. PLoS ONE 7(7):e40410. https://doi.org/10.1371/journal.pone.0040410
Strickler SS, Gribenko AV et al (2006) Protein stability and surface electrostatics: a charged relationship. Biochemistry 45(9):2761–2766. https://doi.org/10.1021/bi0600143
Turunen O, Vuorio M et al (2002) Engineering of multiple arginines into the Ser/Thr surface of Trichoderma reesei endo-1, 4-β-xylanase II increases the thermotolerance and shifts the pH optimum towards alkaline pH. Protein Eng 15(2):141–145. https://doi.org/10.1093/protein/15.2.141
Van Der Spoel D, Lindahl E et al (2005) GROMACS: fast, flexible, and free. J Comput Chem 26(16):1701–1718. https://doi.org/10.1002/jcc.20291
Van Zundert G, Rodrigues J et al (2016) The HADDOCK2 2 web server: user-friendly integrative modeling of biomolecular complexes. Journal of molecular biology 428(4):720–725. https://doi.org/10.1016/j.jmb.2015.09.014
Warwicker J, Charonis S et al (2014) Lysine and arginine content of proteins: computational analysis suggests a new tool for solubility design. Mol Pharm 11(1):294–303. https://doi.org/10.1021/mp4004749
Wei Y, Yi Z et al (2019) Study on the binding characteristics of hydroxylated polybrominated diphenyl ethers and thyroid transporters using the multispectral technique and computational simulation. J Biomol Struct Dyn 37(6):1402–1413. https://doi.org/10.1080/07391102.2018.1461134
Willard L, Ranjan A et al (2003) VADAR: a web server for quantitative evaluation of protein structure quality. Nucleic Acids Res 31(13):3316–3319. https://doi.org/10.1093/nar/gkg565
Witvliet DK, Strokach A et al (2016) ELASPIC web-server: proteome-wide structure-based prediction of mutation effects on protein stability and binding affinity. Bioinformatics 32(10):1589–1591. https://doi.org/10.1093/bioinformatics/btw031
Yin S, Ding F et al (2007) Modeling backbone flexibility improves protein stability estimation. Structure 15(12):1567–1576. https://doi.org/10.1016/j.str.2007.09.024
Yu Z, Liu Y et al (2020) Insights from molecular dynamics simulations and steered molecular dynamics simulations to exploit new trends of the interaction between HIF-1α and p300. J Biomol Struct Dyn 38(1):1–12. https://doi.org/10.1080/07391102.2019.1580616
Zare H, Sadeghi HMM et al (2019) Optimization of fermentation conditions for reteplase expression by Escherichia coli using response surface methodology. Avicenna J Med Biotechnol 11(2):162
Zeiske T, Stafford KA et al (2016) Thermostability of enzymes from molecular dynamics simulations. J Chem Theory Comput 12(6):2489–2492. https://doi.org/10.1021/acs.jctc.6b00120
Zhang Z, Kuipers G et al (2015) High-level production of membrane proteins in E. coli BL21 (DE3) by omitting the inducer IPTG. Microb Cell Factories 14(1):1–11. https://doi.org/10.1186/s12934-015-0328-z
Zhou Y, Han L-R et al (2018) Effects of agitation, aeration and temperature on production of a novel glycoprotein GP-1 by Streptomyces kanasenisi ZX01 and scale-up based on volumetric oxygen transfer coefficient. Molecules 23(1):125. https://doi.org/10.3390/molecules23010125
Acknowledgements
This study was supported by Isfahan University of Medical Sciences grant number 199477 (Ethical code: IR.MUI.RESEARCH.REC.1399.661) and the National Institute of Medical Research Development (NIMAD) grant number 958361.
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Seyedhosseini Ghaheh, H., Sajjadi, S., Shafiee, F. et al. Rational design of a new variant of Reteplase with optimized physicochemical profile and large-scale production in Escherichia coli. World J Microbiol Biotechnol 38, 29 (2022). https://doi.org/10.1007/s11274-021-03204-1
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DOI: https://doi.org/10.1007/s11274-021-03204-1