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Parkinson Hastalığı ile İlişkilendirilen PreNAC Fibril Kesiti ve Onun A53C, A53E, A53G, A53T, A53V Mutasyonlarının Yapısal Kararlılığın Araştırılması

Year 2021, Volume: 16 Issue: 1, 66 - 76, 27.05.2021
https://doi.org/10.29233/sdufeffd.824140

Abstract

Parkinson hastalığının (PD) başlıca patolojik işaretlerinden biri beyinde kümelenmiş alfa-sinüklein agregalarının oluşturdukları fibril yapılardır. Bu çalışmada PreNAC olarak adlandırılan bir alfa-sinüklein fibril kesiti ve onun 53. aminoasidinin A53C, A53E, A53G, A53T ve A53V mutasyon fibril yapıları üzerine odaklanılmıştır. Ele alınan tüm fibril kesiti sistemlerinin yapısal kararlılıkları ve yaprak tabakları arasındaki etkileşimler Moleküler Dinamik (MD) simülasyon yöntemi kullanılarak incelenmiştir. Böylece ilgilenilen fibril kesitlerinin gelecekteki muhtemel ilaç geliştirme çalışmaları için hedef yapı olabilme ihtimalleri değerlendirilmiştir. Çalışmada elde edilen bulgulara göre, vahşi tip fibril kesiti ve onun kalıtsal mutasyonlarını içeren A53E, A53T, A53V fibril kesitlerinin simülasyonlar boyunca önemli ölçüde konformasyonel formlarını kararlı bir şekilde koruduğu gözlemlenirken öte yandan A53G mutasyonunun fibril kesitini dağıtıcı bir etki gösterdiği tespit edilmiştir.

Supporting Institution

Zonguldak Bülent Ecevit Üniversitesi

Project Number

2015-22794455-03

Thanks

Bu çalışmaya 2015-22794455-03 nolu Altyapı Projesi ile kaynak sağlayan Zonguldak Bülent Ecevit Üniversitesi Bilimsel Araştırmalar Proje Birimi’ne teşekkür ederiz.

References

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  • 4 M. Goedert, R. Jakes, and M. G. Spillantini, “The synucleinopathies: Twenty years on,” J. Parkinson. Dis., 7 (s1), S51-S69, 2017.
  • 5 M. Goedert, M. G. Spillantini, K. Del Tredici, and H. Braak, “100 years of lewy pathology.” Nat. Rev. Neurol., 9 (1), 13, 2013.
  • 6 T. S. Ulmer, A. Bax, N. B. Cole, and R. L. Nussbaum, “Structure and dynamics of micelle-bound human alpha-synuclein,” J. Biol. Chem., 280 (10), 9595-9603, 2005.
  • 7 L. Xu, R. Nussinov, and B. Ma, “Coupling of the non-amyloid-component (nac) domain and the ktk(e/q)gv repeats stabilize the α-synuclein fibrils,” Eur. J. Med. Chem., 121, 841-850, 2016.
  • 8 J. A. Rodriguez, M. I. Ivanova, M. R. Sawaya, D. Cascio, F. E. Reyes, D. Shi, S. Sangwan, E. L. Guenther, L. M. Johnson, M. Zhang, L. Jiang, M. A. Arbing, B. L. Nannenga, J. Hattne, J. Whitelegge, A. S. Brewster, M. Messerschmidt, S. Boutet, N. K. Sauter, T. Gonen, and D. S. Eisenberg, “Structure of the toxic core of α-synuclein from invisible crystals,” Nature, 525 (7570), 486-490, 2015.
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  • 10 R. Guerrero-Ferreira, N. M. I. Taylor, A.-A. Arteni, P. Kumari, D. Mona, P. Ringler, M. Britschgi, M. E. Lauer, A. Makky, J. Verasdonck, R. Riek, R. Melki, B. H. Meier, A. Böckmann, L. Bousset, and H. Stahlberg, “Two new polymorphic structures of human full-length alpha-synuclein fibrils solved by cryo-electron microscopy,” eLife, 8, e48907, 2019.
  • 11 P. Pasanen, L. Myllykangas, M. Siitonen, A. Raunio, S. Kaakkola, J. Lyytinen, P. J. Tienari, M. Pöyhönen, and A. Paetau, “Novel α-synuclein mutation a53e associated with atypical multiple system atrophy and parkinson's disease-type pathology,” Neurobiol. Aging, 35 (9), 2180.e2181-2185, 2014.
  • 12 M. H. Polymeropoulos, C. Lavedan, E. Leroy, S. E. Ide, A. Dehejia, A. Dutra, B. Pike, H. Root, J. Rubenstein, R. Boyer, E. S. Stenroos, S. Chandrasekharappa, A. Athanassiadou, T. Papapetropoulos, W. G. Johnson, A. M. Lazzarini, R. C. Duvoisin, G. Di Iorio, L. I. Golbe, and R. L. Nussbaum, “Mutation in the alpha-synuclein gene identified in families with parkinson's disease,” Science, 276 (5321), 2045-2047, 1997.
  • 13 H. Yoshino, M. Hirano, A. J. Stoessl, Y. Imamichi, A. Ikeda, Y. Li, M. Funayama, I. Yamada, Y. Nakamura, V. Sossi, M. J. Farrer, K. Nishioka, and N. Hattori, “Homozygous alpha-synuclein p.A53v in familial parkinson's disease,” Neurobiol. Aging, 57, 248.e247-248.e212, 2017.
  • 14 W. L. DeLano, “Pymol: An open-source molecular graphics tool.” CCP4 Newsletter on protein crystallography, 40 (1), 82-92, 2002. Available: https://pymol.org/2/
  • 15 R. B. Best, X. Zhu, J. Shim, P. E. M. Lopes, J. Mittal, M. Feig, and A. D. MacKerell, “Optimization of the additive charmm all-atom protein force field targeting improved sampling of the backbone ϕ, ψ and side-chain χ1 and χ2 dihedral angles,” J. Chem. Theory Comput., 8 (9), 3257-3273, 2012.
  • 16 A. D. MacKerell, D. Bashford, M. Bellott, R. L. Dunbrack, J. D. Evanseck, M. J. Field, S. Fischer, J. Gao, H. Guo, S. Ha, D. Joseph-McCarthy, L. Kuchnir, K. Kuczera, F. T. Lau, C. Mattos, S. Michnick, T. Ngo, D. T. Nguyen, B. Prodhom, W. E. Reiher, B. Roux, M. Schlenkrich, J. C. Smith, R. Stote, J. Straub, M. Watanabe, J. Wiórkiewicz-Kuczera, D. Yin, and M. Karplus, “All-atom empirical potential for molecular modeling and dynamics studies of proteins,” J. Phys. Chem. B, 102 (18), 3586-3616, 1998.
  • 17 W. L. Jorgensen, J. Chandrasekhar, J. D. Madura, R. W. Impey, and M. L. Klein, “Comparison of simple potential functions for simulating liquid water,” J. Chem. Phys., 79 (2), 926-935, 1983.
  • 18 H. Alıcı, “Structural analyses and force fields comparison for nacore (68–78) and subnacore (69–77) fibril segments of parkinson’s disease,” J. Mol. Model., 26 (6), 132, 2020.
  • 19 H. Alıcı, “A conformational evaluation for PreNAC(46-56) fibril segment of alpha-synuclein using molecular dynamic simulation method,” KSU J. Agric. Nat., 24 (1), 11-21, 2021
  • 20 S. Pronk, S. Páll, R. Schulz, P. Larsson, P. Bjelkmar, R. Apostolov, M. R. Shirts, J. C. Smith, P. M. Kasson, D. van der Spoel, B. Hess, and E. Lindahl, “Gromacs 4.5: A high-throughput and highly parallel open source molecular simulation toolkit,” Bioinformatics, 29 (7), 845-854, 2013.
  • 21 L. Verlet, “Computer "experiments" on classical fluids. Ii. Equilibrium correlation functions,” Phys. Rev., 165 (1), 201-214, 1968.
  • 22 T. Darden, D. York, and L. Pedersen, “Particle mesh ewald: An n⋅log(n) method for ewald sums in large systems,” J. Chem. Phys., 98 (12), 10089-10092, 1993.
  • 23 U. Essmann, L. Perera, M. L. Berkowitz, T. Darden, H. Lee, and L. G. Pedersen, “A smooth particle mesh ewald method,” J. Chem. Phys., 103 (19), 8577-8593, 1995.
  • 24 G. Bussi, D. Donadio, and M. Parrinello, “Canonical sampling through velocity rescaling,” J. Chem. Phys., 126 (1), 014101, 2007.
  • 25 M. Parrinello, and A. Rahman, “Polymorphic transitions in single crystals: A new molecular dynamics method,” J. Appl. Phys., 52 (12), 7182-7190, 1981.
  • 26 R. Kumari, R. Kumar, and A. Lynn, “G_mmpbsa--a gromacs tool for high-throughput mm-pbsa calculations,” J. Chem. Inf. Model., 54 (7), 1951-1962, 2014.
  • 27 H. Alıcı, “In silico analysis: Structural insights about inter-protofilaments interactions for α-synuclein (50–57) fibrils and its familial mutation,” Mol. Simulat., 46 (12), 867-878, 2020.
  • 28 H. Luo, D.-F. Liang, M.-Y. Bao, R. Sun, Y.-Y. Li, J.-Z. Li, X. Wang, K.-M. Lu, and J.-K. Bao, “In silico identification of potential inhibitors targeting streptococcus mutans sortase a,” Int. J. Oral Sci., 9 (1), 53-62, 2017.
  • 29 W. M. Berhanu, and U. H. E. Hansmann, “Side-chain hydrophobicity and the stability of aβ₁₆₋₂₂ aggregates,” Protein Sci., 21 (12), 1837-1848, 2012.

Investigation of the Structural Stability of PreNAC and its A53C, A53E, A53G, A53T, A53V Mutant Fibril Segments Associated with Parkinson's Disease

Year 2021, Volume: 16 Issue: 1, 66 - 76, 27.05.2021
https://doi.org/10.29233/sdufeffd.824140

Abstract

A pathological hallmark of Parkinson's disease (PD) is the fibrillar structures formed by alpha-synuclein aggregates accumulated in the brain. In this study, we focused on an alpha-synuclein PreNAC fibril segment and it’s A53C, A53E, A53G, A53T and A53V mutations. The structural stability and the interactions between sheets of all fibril systems studied in this paper were examined using the Molecular Dynamic (MD) simulation method and thus the possibilities of these fibril segments to be target structures for future drug development efforts was evaluated. According to the findings obtained from our MD simulations, it was determined that the wild type (WT) fibril segment and its A53E, A53T and A53V fibril structures with hereditary mutations preserved significantly their stable conformational structure along the simulations, whereas the A53G mutation had a disruptive effect on the fibril segment.

Project Number

2015-22794455-03

References

  • 1 T. Lebouvier, T. Chaumette, S. Paillusson, C. Duyckaerts, S. Bruley des Varannes, M. Neunlist, and P. Derkinderen, “The second brain and parkinson's disease,” Eur. J. Neurosci., 30 (5), 735-741, 2009.
  • 2 T. R. Mhyre, J. T. Boyd, R. W. Hamill, and K. A. Maguire-Zeiss, Parkinson’s Disease. In: Harris J. (eds) Protein Aggregation and Fibrillogenesis in Cerebral and Systemic Amyloid Disease. Subcellular Biochemistry, vol 65, Springer, Dordrecht, pp. 2012, 389-455.
  • 3 M. G. Spillantini, M. L. Schmidt, V. M. Y. Lee, J. Q. Trojanowski, R. Jakes, and M. Goedert, “Α-synuclein in lewy bodies,” Nature, 388 (6645), 839-840, 1997.
  • 4 M. Goedert, R. Jakes, and M. G. Spillantini, “The synucleinopathies: Twenty years on,” J. Parkinson. Dis., 7 (s1), S51-S69, 2017.
  • 5 M. Goedert, M. G. Spillantini, K. Del Tredici, and H. Braak, “100 years of lewy pathology.” Nat. Rev. Neurol., 9 (1), 13, 2013.
  • 6 T. S. Ulmer, A. Bax, N. B. Cole, and R. L. Nussbaum, “Structure and dynamics of micelle-bound human alpha-synuclein,” J. Biol. Chem., 280 (10), 9595-9603, 2005.
  • 7 L. Xu, R. Nussinov, and B. Ma, “Coupling of the non-amyloid-component (nac) domain and the ktk(e/q)gv repeats stabilize the α-synuclein fibrils,” Eur. J. Med. Chem., 121, 841-850, 2016.
  • 8 J. A. Rodriguez, M. I. Ivanova, M. R. Sawaya, D. Cascio, F. E. Reyes, D. Shi, S. Sangwan, E. L. Guenther, L. M. Johnson, M. Zhang, L. Jiang, M. A. Arbing, B. L. Nannenga, J. Hattne, J. Whitelegge, A. S. Brewster, M. Messerschmidt, S. Boutet, N. K. Sauter, T. Gonen, and D. S. Eisenberg, “Structure of the toxic core of α-synuclein from invisible crystals,” Nature, 525 (7570), 486-490, 2015.
  • 9 H. Han, P. H. Weinreb, and P. T. Lansbury, “The core alzheimer's peptide nac forms amyloid fibrils which seed and are seeded by β-amyloid: Is nac a common trigger or target in neurodegenerative disease?,” Chem. Biol., 2 (3), 163-169, 1995.
  • 10 R. Guerrero-Ferreira, N. M. I. Taylor, A.-A. Arteni, P. Kumari, D. Mona, P. Ringler, M. Britschgi, M. E. Lauer, A. Makky, J. Verasdonck, R. Riek, R. Melki, B. H. Meier, A. Böckmann, L. Bousset, and H. Stahlberg, “Two new polymorphic structures of human full-length alpha-synuclein fibrils solved by cryo-electron microscopy,” eLife, 8, e48907, 2019.
  • 11 P. Pasanen, L. Myllykangas, M. Siitonen, A. Raunio, S. Kaakkola, J. Lyytinen, P. J. Tienari, M. Pöyhönen, and A. Paetau, “Novel α-synuclein mutation a53e associated with atypical multiple system atrophy and parkinson's disease-type pathology,” Neurobiol. Aging, 35 (9), 2180.e2181-2185, 2014.
  • 12 M. H. Polymeropoulos, C. Lavedan, E. Leroy, S. E. Ide, A. Dehejia, A. Dutra, B. Pike, H. Root, J. Rubenstein, R. Boyer, E. S. Stenroos, S. Chandrasekharappa, A. Athanassiadou, T. Papapetropoulos, W. G. Johnson, A. M. Lazzarini, R. C. Duvoisin, G. Di Iorio, L. I. Golbe, and R. L. Nussbaum, “Mutation in the alpha-synuclein gene identified in families with parkinson's disease,” Science, 276 (5321), 2045-2047, 1997.
  • 13 H. Yoshino, M. Hirano, A. J. Stoessl, Y. Imamichi, A. Ikeda, Y. Li, M. Funayama, I. Yamada, Y. Nakamura, V. Sossi, M. J. Farrer, K. Nishioka, and N. Hattori, “Homozygous alpha-synuclein p.A53v in familial parkinson's disease,” Neurobiol. Aging, 57, 248.e247-248.e212, 2017.
  • 14 W. L. DeLano, “Pymol: An open-source molecular graphics tool.” CCP4 Newsletter on protein crystallography, 40 (1), 82-92, 2002. Available: https://pymol.org/2/
  • 15 R. B. Best, X. Zhu, J. Shim, P. E. M. Lopes, J. Mittal, M. Feig, and A. D. MacKerell, “Optimization of the additive charmm all-atom protein force field targeting improved sampling of the backbone ϕ, ψ and side-chain χ1 and χ2 dihedral angles,” J. Chem. Theory Comput., 8 (9), 3257-3273, 2012.
  • 16 A. D. MacKerell, D. Bashford, M. Bellott, R. L. Dunbrack, J. D. Evanseck, M. J. Field, S. Fischer, J. Gao, H. Guo, S. Ha, D. Joseph-McCarthy, L. Kuchnir, K. Kuczera, F. T. Lau, C. Mattos, S. Michnick, T. Ngo, D. T. Nguyen, B. Prodhom, W. E. Reiher, B. Roux, M. Schlenkrich, J. C. Smith, R. Stote, J. Straub, M. Watanabe, J. Wiórkiewicz-Kuczera, D. Yin, and M. Karplus, “All-atom empirical potential for molecular modeling and dynamics studies of proteins,” J. Phys. Chem. B, 102 (18), 3586-3616, 1998.
  • 17 W. L. Jorgensen, J. Chandrasekhar, J. D. Madura, R. W. Impey, and M. L. Klein, “Comparison of simple potential functions for simulating liquid water,” J. Chem. Phys., 79 (2), 926-935, 1983.
  • 18 H. Alıcı, “Structural analyses and force fields comparison for nacore (68–78) and subnacore (69–77) fibril segments of parkinson’s disease,” J. Mol. Model., 26 (6), 132, 2020.
  • 19 H. Alıcı, “A conformational evaluation for PreNAC(46-56) fibril segment of alpha-synuclein using molecular dynamic simulation method,” KSU J. Agric. Nat., 24 (1), 11-21, 2021
  • 20 S. Pronk, S. Páll, R. Schulz, P. Larsson, P. Bjelkmar, R. Apostolov, M. R. Shirts, J. C. Smith, P. M. Kasson, D. van der Spoel, B. Hess, and E. Lindahl, “Gromacs 4.5: A high-throughput and highly parallel open source molecular simulation toolkit,” Bioinformatics, 29 (7), 845-854, 2013.
  • 21 L. Verlet, “Computer "experiments" on classical fluids. Ii. Equilibrium correlation functions,” Phys. Rev., 165 (1), 201-214, 1968.
  • 22 T. Darden, D. York, and L. Pedersen, “Particle mesh ewald: An n⋅log(n) method for ewald sums in large systems,” J. Chem. Phys., 98 (12), 10089-10092, 1993.
  • 23 U. Essmann, L. Perera, M. L. Berkowitz, T. Darden, H. Lee, and L. G. Pedersen, “A smooth particle mesh ewald method,” J. Chem. Phys., 103 (19), 8577-8593, 1995.
  • 24 G. Bussi, D. Donadio, and M. Parrinello, “Canonical sampling through velocity rescaling,” J. Chem. Phys., 126 (1), 014101, 2007.
  • 25 M. Parrinello, and A. Rahman, “Polymorphic transitions in single crystals: A new molecular dynamics method,” J. Appl. Phys., 52 (12), 7182-7190, 1981.
  • 26 R. Kumari, R. Kumar, and A. Lynn, “G_mmpbsa--a gromacs tool for high-throughput mm-pbsa calculations,” J. Chem. Inf. Model., 54 (7), 1951-1962, 2014.
  • 27 H. Alıcı, “In silico analysis: Structural insights about inter-protofilaments interactions for α-synuclein (50–57) fibrils and its familial mutation,” Mol. Simulat., 46 (12), 867-878, 2020.
  • 28 H. Luo, D.-F. Liang, M.-Y. Bao, R. Sun, Y.-Y. Li, J.-Z. Li, X. Wang, K.-M. Lu, and J.-K. Bao, “In silico identification of potential inhibitors targeting streptococcus mutans sortase a,” Int. J. Oral Sci., 9 (1), 53-62, 2017.
  • 29 W. M. Berhanu, and U. H. E. Hansmann, “Side-chain hydrophobicity and the stability of aβ₁₆₋₂₂ aggregates,” Protein Sci., 21 (12), 1837-1848, 2012.
There are 29 citations in total.

Details

Primary Language Turkish
Subjects Metrology, Applied and Industrial Physics
Journal Section Makaleler
Authors

Hakan Alıcı 0000-0001-5105-8331

Kadir Demir 0000-0001-7312-3878

Project Number 2015-22794455-03
Publication Date May 27, 2021
Published in Issue Year 2021 Volume: 16 Issue: 1

Cite

IEEE H. Alıcı and K. Demir, “Parkinson Hastalığı ile İlişkilendirilen PreNAC Fibril Kesiti ve Onun A53C, A53E, A53G, A53T, A53V Mutasyonlarının Yapısal Kararlılığın Araştırılması”, Süleyman Demirel Üniversitesi Fen Edebiyat Fakültesi Fen Dergisi, vol. 16, no. 1, pp. 66–76, 2021, doi: 10.29233/sdufeffd.824140.