Molecular Dynamics Simulation of E412 Catalytic Residue Mutation of GOx-IPBCC

Asrul Fanani; Popi Asri Kurniatin; Setyanto Tri Wahyudi; Waras Nurcholis; Laksmi Ambarsari

doi:10.18596/jotcsa.1088587

Research Article

Molecular Dynamics Simulation of E412 Catalytic Residue Mutation of GOx-IPBCC

Year 2022, Volume: 9 Issue: 4, 1091 - 1106, 30.11.2022

Asrul Fanani Popi Asri Kurniatin Setyanto Tri Wahyudi Waras Nurcholis Laksmi Ambarsari

https://doi.org/10.18596/jotcsa.1088587

Abstract

The enzyme glucose oxidase from Aspergillus niger has a homodimeric structure, consisting of two identical subunits with a molecular weight of 150,000 Daltons. In this study, we used the structure of the enzyme glucose oxidase from Aspergillus niger IPBCC.08.610 (GOx-IPBCC), this enzyme had a total activity of 92.87 U (μmol/min) and a Michaelis-Menten constant (Km) of 2.9 mM (millimolar). This study was conducted to predict the molecular dynamics of E412 (Glu412) residue catalytic mutation belonging to the GOx-IPBCC enzyme was determine the effect of changes in the catalytic residue on substrate binding (β-D-glucose). The results of molecular docking of 19 mutant structures, six E412 mutant homologous structures were selected (E412C, E412K, E412Q, E412T, E412, E412V, and E412W), which were evaluated using molecular dynamics simulation for 50 ns. The results showed a decrease in ∆G values in two mutant structures is E412C and E412T, and there is one mutant structure that increased ∆G values, namely E412W, these three mutant structures showed the best stability, bond interaction, and salt bridge profile according to molecular dynamics simulation.

Keywords

GOx-IPBCC enzyme, molecular docking, molecular dynamics simulation

References

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24. Miller BR, McGee TD, Swails JM, Homeyer N, Gohlke H, Roitberg AE. MMPBSA.py: An efficient program for end-state free energy calculations. J Chem Theory Comput. 2012;8(9):3314–21.
25. Wohlfahrt G, Witt S, Hendle J, Schomburg D, Kalisz H, Hecht H. 1.8 and 1.9 Å resolution structures of the Penicillium amagasakiense and Aspergillus niger glucose oxidases as a basis for modelling substrate complexes. Acta Crystallogr Sect D Biol Crystallogr. 1999;969–77.
26. Singh R, Tiwari M, Singh R, Lee J. From protein engineering to immobilization: promising strategies for the upgrade of industrial enzymes. Int J Mol Sci. 2013;(14):1232–77.
27. Guterres H, Im W. Improving protein-ligand docking results with high-throughput molecular dynamics simulations. J Chem Inf Model. 2020;60(4):2189–98.
28. Yu H, Yan Y, Zhang C, Dalby PA. Two strategies to engineer flexible loops for improved enzyme thermostability. Sci Rep. 2017;7(1):1–15.
29. Vieira P, Simão R, Morais C, Henrique J. 310 Helices in channels and other membrane proteins. J Gen Physiol. 2010;136(6):585–92.
30. Basu S, Biswas P. Salt-bridge dynamics in intrinsically disordered proteins: A trade-off between electrostatic interactions and structural flexibility. Biochim Biophys Acta - Proteins Proteomics [Internet]. 2018;1866(5–6):624–41. Available from: https://doi.org/10.1016/j.bbapap.2018.03.002
31. Chen L, Li X, Wang R, Fang F, Yang W, Kan W. Thermal stability and unfolding pathways of hyperthermophilic and mesophilic periplasmic binding proteins studied by molecular dynamics simulation. J Biomol Struct Dyn. 2016;34(7):1576–89.
32. Anuar NFSK, Wahab RA, Huyop F, Amran SI, Hamid AAA, Halim KBA, et al. Molecular docking and molecular dynamics simulations of a mutant Acinetobacter haemolyticus alkaline-stable lipase against tributyrin. J Biomol Struct Dyn. 2020;1–13.
33. Ji B, Liu S, He X, Man VH, Xie XQ, Wang J. Prediction of the binding affinities and selectivity for CB1 and CB2 ligands using homology modeling, molecular docking, molecular dynamics simulations, and MM-PBSA binding free energy calculations. ACS Chem Neurosci. 2020;11(8):1139–58.
34. Aldeghi M, Bodkin MJ, Knapp S, Biggin PC. Statistical analysis on the performance of molecular mechanics poisson-boltzmann surface area versus absolute binding free energy calculations: bromodomains as a case study. J Chem Inf Model. 2017;57(9):2203–21.

Year 2022, Volume: 9 Issue: 4, 1091 - 1106, 30.11.2022

Asrul Fanani Popi Asri Kurniatin Setyanto Tri Wahyudi Waras Nurcholis Laksmi Ambarsari

https://doi.org/10.18596/jotcsa.1088587

Abstract

References

1. Obut S, Bahar T. Glucose oxidase immobilized biofuel cell flow channel geometry analysis by CFD simulations. Turkish J Chem. 2019;43(5):1486–502.
2. Sumaiya A, Trivedi R. A Review on Glucose OxidaseDepartment of Microbiology. Shree Ramkrishna Institute of Applied Sciences. int J curr Microbiol App sci. 2015;4:636–40.
3. Kriaa M, Kammoun R. Producing Aspergillus tubingensis CTM507 Glucose oxidase by Solid state fermentation versus submerged fermentation: Process optimization and enzyme stability by an intermediary metabolite in relation with diauxic growth. J Chem Technol Biotechnol. 2016;91(5):1540–50.
4. Anas A, Gunny N. Studies on the production of Glucose oxidase by Aspergillus terreus UniMAP AA-1. Universiti Malaysia Perlis (UniMAP); 2011.
5. Gutierrez A, Wallraf A, Balaceanu A, Bocola M, Davari M, Meier T, et al. How to engineer glucose oxidase for mediated electron transfer. Biotechnol Bioeng. 2018;115(10):2405–15.
6. Subiyono S, Martsiningsih MA, Gabrela D. Gambaran Kadar Glukosa Darah Metode GOD-PAP (Glucose Oxsidase–Peroxidase Aminoantypirin) Sampel Serum dan Plasma EDTA (Ethylen Diamin Terta Acetat). J Teknol Lab. 2016;5(1):45–8.
7. Ostafe R, Fontaine N, Frank D, Ng Fuk Chong M, Prodanovic R, Pandjaitan R, et al. One‐shot optimization of multiple enzyme parameters: Tailoring glucose oxidase for pH and electron mediators. Biotechnol Bioeng. 2020;117(1):17–29.
8. Mano N. Engineering glucose oxidase for bioelectrochemical applications. Bioelectrochemistry [Internet]. 2019;128:218–40. Available from: https://doi.org/10.1016/j.bioelechem.2019.04.015
9. Leech D, Kavanagh P, Schuhmann W. Enzymatic fuel cells: Recent progress. Electrochim Acta [Internet]. 2012;84:223–34. Available from: http://dx.doi.org/10.1016/j.electacta.2012.02.087
10. Vogt S, Schneider M, Schäfer-Eberwein H, Nöll G. Determination of the pH dependent redox potential of glucose oxidase by spectroelectrochemistry. Anal Chem. 2014;86(15):7530–5.
11. Triana R. Pemurnian dan karakterisasi enzim glukosa oksidase dari isolat lokal Aspergillus niger (IPBCC.08610). Institut Pertanian Bogor; 2013.
12. Indriani A. Pemurnian dengan kromatografi penukar anion dan karakterisasi glukosa oksidase dari aspergillus niger IPBCC 08.610. Institut Pertanian Bogor; 2018.
13. Maulana FA, Ambarsari L, Wahyudi ST. Homology modeling and structural dynamics of the glucose oxidase. Indones J Chem. 2019;20(1):43–53.
14. Kurniatin PA, Ambarsari L, Khanza ADA, Setyawati I, Seno DSH, Nurcholis W. Characteristics of glucose oxidase gene (GGOx) from Aspergillus niger IPBCC 08.610. J Kim Val. 2020;6(1):10–9.
15. Dwiastuti R, Radifar M, Marchaban M, Noegrohati S, Istyastono E., Dwiastuti R, et al. Molecular Dynamics Simulations and Empirical Observations on Soy Lecithin Liposome Preparation. Indones J Chem. 2016;16(2):222–8.
16. Sharma P, Joshi T, Mathpal S, Joshi T, Pundir H, Chandra S, et al. Identification of natural inhibitors against Mpro of SARS-CoV-2 by molecular docking, molecular dynamics simulation, and MM/PBSA methods. J Biomol Struct Dyn [Internet]. 2020;0(0):1–12. Available from: https://doi.org/10.1080/07391102.2020.1842806
17. Petrović D, Frank D, Kamerlin S, Hoffmann K, Strodel B. Shuffling active site substate populations affects catalytic activity: The case of glucose oxidase. ACS Catal. 2017;7(9):6188–6197.
18. Mu Q, Cui Y, Tian Y, Hu M, Tao Y, Wu B. Thermostability improvement of the glucose oxidase from Aspergilus niger for efficient gluconic acid production via computational design. Biol Macromol. 2019;136:1060–8.
19. Tu T, Wang Y, Huang H, Wang Y, Jiang X, Wang Z, et al. Improving the thermostability and catalytic efficiency of glucose oxidase from Aspergillus niger by molecular evolution. Food Chem. 2019;281:163–70.
20. Kaczmarski JA, Mahawaththa MC, Feintuch A, Clifton BE, Adams LA, Goldfarb D, et al. Altered conformational sampling along an evolutionary trajectory changes the catalytic activity of an enzyme. Nat Commun [Internet]. 2020;11(1):1–14. Available from: http://dx.doi.org/10.1038/s41467-020-19695-9
21. Case I, Ben-Shalom S, Brozell D, Cerutti T, Cheatham I, Cruzeiro T, et al. AMBER 2018. San Francisco: University of California; 2018.
22. Myers J, Grothaus G, Narayanan S, Onufriev A. A simple clustering algorithm can be accurate enough for use in calculations of pKs in macromolecules. Proteins Struct Funct Bioinforma. 2006;63(4):928–38.
23. Anandakrishnan R, Aguilar B, Onufriev A V. H++ 3.0: Automating pK prediction and the preparation of biomolecular structures for atomistic molecular modeling and simulations. Nucleic Acids Res. 2012;40(W1):W537–41.
24. Miller BR, McGee TD, Swails JM, Homeyer N, Gohlke H, Roitberg AE. MMPBSA.py: An efficient program for end-state free energy calculations. J Chem Theory Comput. 2012;8(9):3314–21.
25. Wohlfahrt G, Witt S, Hendle J, Schomburg D, Kalisz H, Hecht H. 1.8 and 1.9 Å resolution structures of the Penicillium amagasakiense and Aspergillus niger glucose oxidases as a basis for modelling substrate complexes. Acta Crystallogr Sect D Biol Crystallogr. 1999;969–77.
26. Singh R, Tiwari M, Singh R, Lee J. From protein engineering to immobilization: promising strategies for the upgrade of industrial enzymes. Int J Mol Sci. 2013;(14):1232–77.
27. Guterres H, Im W. Improving protein-ligand docking results with high-throughput molecular dynamics simulations. J Chem Inf Model. 2020;60(4):2189–98.
28. Yu H, Yan Y, Zhang C, Dalby PA. Two strategies to engineer flexible loops for improved enzyme thermostability. Sci Rep. 2017;7(1):1–15.
29. Vieira P, Simão R, Morais C, Henrique J. 310 Helices in channels and other membrane proteins. J Gen Physiol. 2010;136(6):585–92.
30. Basu S, Biswas P. Salt-bridge dynamics in intrinsically disordered proteins: A trade-off between electrostatic interactions and structural flexibility. Biochim Biophys Acta - Proteins Proteomics [Internet]. 2018;1866(5–6):624–41. Available from: https://doi.org/10.1016/j.bbapap.2018.03.002
31. Chen L, Li X, Wang R, Fang F, Yang W, Kan W. Thermal stability and unfolding pathways of hyperthermophilic and mesophilic periplasmic binding proteins studied by molecular dynamics simulation. J Biomol Struct Dyn. 2016;34(7):1576–89.
32. Anuar NFSK, Wahab RA, Huyop F, Amran SI, Hamid AAA, Halim KBA, et al. Molecular docking and molecular dynamics simulations of a mutant Acinetobacter haemolyticus alkaline-stable lipase against tributyrin. J Biomol Struct Dyn. 2020;1–13.
33. Ji B, Liu S, He X, Man VH, Xie XQ, Wang J. Prediction of the binding affinities and selectivity for CB1 and CB2 ligands using homology modeling, molecular docking, molecular dynamics simulations, and MM-PBSA binding free energy calculations. ACS Chem Neurosci. 2020;11(8):1139–58.
34. Aldeghi M, Bodkin MJ, Knapp S, Biggin PC. Statistical analysis on the performance of molecular mechanics poisson-boltzmann surface area versus absolute binding free energy calculations: bromodomains as a case study. J Chem Inf Model. 2017;57(9):2203–21.

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Primary Language	English
Journal Section	Articles
Authors	Asrul Fanani 0000-0001-7278-8309 Popi Asri Kurniatin This is me 0000-0002-9522-2129 Setyanto Tri Wahyudi This is me 0000-0003-0007-1186 Waras Nurcholis This is me 0000-0001-7047-5093 Laksmi Ambarsari 0000-0001-8981-792X
Publication Date	November 30, 2022
Submission Date	March 16, 2022
Acceptance Date	September 17, 2022
Published in Issue	Year 2022 Volume: 9 Issue: 4

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Vancouver	Fanani A, Kurniatin PA, Wahyudi ST, Nurcholis W, Ambarsari L. Molecular Dynamics Simulation of E412 Catalytic Residue Mutation of GOx-IPBCC. JOTCSA. 2022;9(4):1091-106.

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