In-silico structural analysis of Heterocephalus glaber amyloid beta: an anti-Alzheimer's peptide

Document Type : Original article

Authors

Faculty of Life Sciences and Biotechnology, Shahid Beheshti University, Tehran, Iran

Abstract

Heterocephalus glaber, known as the Naked mole-rat, has an extraordinary immunity to Alzheimer's disease. The pathological hallmark of Alzheimer’s disease is cerebral accumulations of plaques, consisting of self-aggregated amyloid beta peptides. Homo sapiens and H. glaber amyloid beta peptides are different in only one amino acid. Herein, computational structural analyses were carried out to determine whether plaque development in H. glaber is prevented by the replacement of His13 with Arg13 in the amyloid beta peptide. AlphaFold2 was used to predict the structure of the H. glaber amyloid beta peptide. HADDOCK and Hex were used to self-dock the peptides and dock ions on peptides, respectively. Illustrations were made by PyMol and ChimeraX. Using VMD, we calculated the radius of gyration. The phylogenetic analysis was conducted by Mega. The results showed an accurate structure with two alpha helices separated by a short coil for H. glaber. Self-docking of the two amyloid beta peptides demonstrated a globular conformation in the H. glaber dimer, implying the unlikeliness of amyloid beta peptides’ self-aggregation to form fibrillar structures. This conformational state resulted in lower electrostatic energy compared to H. sapiens, contributing to H. glaber’s lower tendency for fibril and, ultimately, plaque formation. Phylogenetic analysis confirmed that amyloid precursor protein is highly conserved in each taxon of rodentia and primata. This study provides insight into the connection between the structure of H. glaber amyloid beta and its plaque formation properties, showing that the Arg13 in H. glaber leads to fibril instability, and might prevent senile plaque accumulation.

Keywords

References

  1. Scheltens P, De Strooper B, Kivipelto M, Holstege H, Chételat G, Teunissen CE, Cummings J, van der Flier WM. Alzheimer's disease. Lancet 2021;397(10284):1577-1590. 
  2. Busche MA, Hyman BT. Synergy between amyloid-β and tau in Alzheimer’s disease. Nat Neurosci 2020;23:1183-1193.
  3. Chen GF, Xu TH, Yan Y, Zhou YR, Jiang Y, Melcher K, Xu HE. Amyloid beta: structure, biology and structure-based therapeutic development. Acta Pharmacol Sin 2017;38:1205-1235.
  4. Guo Y, Wang Q, Chen S, Xu C. Functions of amyloid precursor protein in metabolic diseases. Metabolism 2021;115:154454.
  5. Gallardo G, Holtzman DM. Amyloid-β and Tau at the Crossroads of Alzheimer’s Disease. Adv Exp Med Biol 2019;1184:187-203.
  6. Rosen RF, Tomidokoro Y, Farberg AS, Dooyema J, Ciliax B, Preuss TM, Neubert TA, Ghiso JA, 3rd HL, Walker LC. Comparative pathobiology of β-amyloid and the unique susceptibility of humans to Alzheimer’s disease. Neurobiol Aging 2016;44:185-196.
  7. Walker LC, Jucker M. The exceptional vulnerability of humans to Alzheimer’s disease. Trends Mol Med 2017;23:534-545.
  8. Edler MK, Sherwood CC, Meindl RS, Hopkins WD, Ely JJ, Erwin JM, Mufson EJ, Hof PR, Raghanti MA. Aged chimpanzees exhibit pathologic hallmarks of Alzheimer’s disease. Neurobiol Aging 2017;59:107-120.
  9. Toledano A, Álvarez MI, López-Rodríguez AB, Toledano-Díaz A, Fernández-Verdecia CI. [Does Alzheimer’s disease exist in all primates? Alzheimer pathology in non-human primates and its pathophysiological implications (II)]. Neurologia 2014;29:42-55.
  10. Heuer E, Rosen RF, Cintron A, Walker LC. Nonhuman primate models of Alzheimer-like cerebral proteopathy. Curr Pharm Des 2012;18:1159-1169.
  11. Chan AWS, Cho IK, Li CX, Zhang X, Patel S, Rusnak R, Raper J, Bachevalier J, Moran SP, Chi T, Cannon KH, Hunter CE, Martin RC, Xiao H, Yang SH, Gumber S, Herndon JG, Rosen RF, Hu WT, Lah JJ, Levey AI, Smith Y, Walker LC. Cerebral Aβ deposition in an Aβ-precursor protein-transgenic rhesus monkey. Aging Brain 2022;2:100044.
  12. Poon CH, Wang Y, Fung ML, Zhang C, Lim LW. Rodent models of amyloid-beta feature of Alzheimer’s disease: Development and potential treatment implications. Aging Dis 2020; 11:1235-1259.
  13. Otvos Jr L, Szendrei GI, Lee VM, Mantsch HH. Human and rodent Alzheimer β-amyloid peptides acquire distinct conformations in membrane-mimicking solvents. Eur J Biochem 1993;211(1-2):249-257.
  14. Götz J, Bodea LG, Goedert M. Rodent models for Alzheimer disease. Nat Rev Neurosci 2018;19:583-598.
  15. Do Carmo S, Cuello AC. Modeling Alzheimer’s disease in transgenic rats. Mol Neurodegener 2013;8:37.
  16. Dyrks T, Dyrks E, Masters CL, Beyreuther K. Amyloidogenicity of rodent and human βA4 sequences. FEBS Lett 1993;324:231-236.
  17. Liu ST, Howlett G, Barrow CJ. Histidine-13 is a crucial residue in the zinc ion-induced aggregation of the Aβ peptide of Alzheimer’s disease. Biochemistry 1999;38:9373-9378.
  18. National center for biotechnology information [Internet]. [cited 2023 Feb 22]. Available from: https://www.ncbi.nlm.nih.gov
  19. Tamura K, Stecher G, Kumar S. MEGA11: Molecular evolutionary genetics analysis version 11. Mol Biol Evol 2021;38:3022-3027.
  20. Jumper J, Evans R, Pritzel A, Green T, Figurnov M, Ronneberger O, Tunyasuvunakool K, Bates R, Zidek A, Potapenko A, Bridgland A, Meyer C, Kohl SAA, Ballard AJ, Coeie A, Romera-Paredes B, Nikolov S, Jain R, Adler J, Back T, Petersen S, Reiman D, Clancy E, Zielinski M, Steinegger M, Pacholska M, Berghammer T, Bodenstein S, Silver D, Vinyals O, Senior AW, Kavukcuoglu K, Kohli P, Hassabis D. Highly accurate protein structure prediction with AlphaFold. Nature 2021;596:583-589.
  21. Mirdita M, Schütze K, Moriwaki Y, Heo L, Ovchinnikov S, Steinegger M. ColabFold: making protein folding accessible to all. Nature Methods 2022;19:679-682.
  22. Bisong E. Google Colaboratory. In: Building Machine Learning and Deep Learning Models on Google Cloud Platform. Berkeley, CA: Apress; 2019;7:59-64.
  23. Edrey YH, Medina DX, Gaczynska M, Osmulski PA, Oddo S, Caccamo A, Buffenstein R. Amyloid beta and the longest-lived rodent: the naked mole-rat as a model for natural protection from Alzheimer’s disease. Neurobiol Aging 2013;34:2352-2360.
  24. Steinegger M, Söding J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat Biotechnol 2017;35:1026-108.
  25. Varadi M, Anyango S, Deshpande M, Nair S, Natassia C, Yordanova G, Yuan D, Store O, Wood G, Laydon A, Zidek A, Green T, Tunyasuvunakool K, Petersen S, Jumper J, Clancy E, Green R, Vora A, Lutfi M, Figurnov M, Cowie A, Hobbs N, Kohli P, Kleywegt G, Birney E, Hassabis D, Velankar S. AlphaFold protein structure database: massively expanding the structural coverage of protein-sequence space with high-accuracy models. Nucleic Acids Res 2022;7;50:D439-D444.
  26. Pettersen EF, Goddard TD, Huang CC, Meng EC, Couch GS, Croll TI, Morris JH, Ferrin TE. UCSF ChimeraX: Structure visualization for researchers, educators, and developers. Protein Sci 2021;30:70-82.
  27. Tunyasuvunakool K, Adler J, Wu Z, Green T, Zielinski M, Žídek A, Bridgland A, Cowie A, Meyer C, Laydon A, Velankar S, Kleywegt GJ, Bateman A, Evans R, Pritzel A, Figurnov M, Ronneberger O, Bates R, Kohl SAA, Potapenko A, Ballard AJ, Romera-Paredes B, Nikolov S, Jain R, Clancy E, Reiman D, Petersen S, Senior AW, Kavukcuoglu K, Birney E, Kohli P, Jumper J, Hassabis D. Highly accurate protein structure prediction for the human proteome. Nature 2021;596:590-596.
  28. Schrödinger LLC. The PyMOL Molecular Graphics System, Version 1.8. 2015.
  29. Torsten Schwede, Jürgen Kopp, Nicolas Guex, Manuel C. Peitsch. SWISS-MODEL: an automated protein homology-modeling server. Nucleic Acids Res 2003;31:3381-3385.
  30. Laskowski RA, Macarthur MW, Moss DS, Thornton JM. ProCheck: A program to check the stereochemical quality of protein structures. J Appl Crystallogr 1993;26:283-291
  31. Honorato RV, Koukos PI, Jiménez-García B, Tsaregorodtsev A, Verlato M, Giachetti A, Rosato A, Bonvin AMJJ. Structural Biology in the Clouds: The WeNMR-EOSC Ecosystem. Front Mol Biosci 2021;8:729513.
  32. van Zundert GCP, Rodrigues JPGLM, Trellet M, Schmitz C, Kastritis PL, Karaca E, Melquiond ASJ, Van Dijk M, de Vries SJ, Bonvin AMJJ. The HADDOCK2.2 web server: User-friendly integrative modeling of biomolecular complexes. J Mol Biol 2016;428:720-725.
  33. Ritchie DW. Evaluation of protein docking predictions using Hex 3.1 in CAPRI rounds 1 and 2. Proteins 2003;52:98-106.
  34. Hex Protein Docking [Internet]. [cited 2023 Feb 22]. Available from: http://hex.loria.fr/
  35. PubChem. PubChem [Internet]. [cited 2023 Feb 22]. Available from: https://pubchem.ncbi.nlm.nih.gov/
  36. Humphrey W, Dalke A, Schulten K. VMD: visual molecular dynamics. J Mol Graph 1996; 14:33-38, 27-28.
  37. Landau LJB, de Oliveira Fam BS, Yépez Y, Caldas-Garcia GB, Pissinatti A, Falótico T, Reales G, Schuler-Faccini L, Sortica VA, Bortolini MC. Evolutionary analysis of the anti-viral STAT2 gene of primates and rodents: Signature of different stages of an arms race. Infect Genet Evol 2021;95:105030.
  38. Boso G, Buckler-White A, Kozak CA. Ancient Evolutionary Origin and Positive Selection of the Retroviral Restriction Factor Fv1 in Muroid Rodents. J Virol 2018;92:e00850.
  39. Finder VH, Glockshuber R. Amyloid-beta aggregation. Neurodegener Dis 2007;4:13-27.
  40. Murphy MP, 3rd Levine H. Alzheimer’s disease and the amyloid-beta peptide. J Alzheimers Dis 2010;19:311-323.
  41. Salazar C, Valdivia G, Ardiles ÁO, Ewer J, Palacios AG. Genetic variants associated with neurodegenerative Alzheimer disease in natural models. Biol Res 2016;49:14.
  42. Bates K, Vink R, Martins R, Harvey A. Aging, cortical injury and Alzheimer’s disease-like pathology in the guinea pig brain. Neurobiol Aging 2014;35:1345-1351.
  43. Beck M, Bigl V, Rossner S. Guinea pigs as a nontransgenic model for APP processing in vitro and in vivo. Neurochem Res 2003;28:637-644.
  44. Fraser PE, Nguyen JT, Inouye H, Surewicz WK, Selkoe DJ, Podlisny MB, Kirschner DA. Fibril formation by primate, rodent, and Dutch-Hemorrhagic analogues of Alzheimer amyloid β-protein. Biochemistry 1992;31:10716-10723.
  45. Smith ESJ, Schuhmacher L-N, Husson Z. The naked mole-rat as an animal model in biomedical research: current perspectives. Open Access Anim Physiol 2015;7:137-48.
  46. Zhao Y, Qiao S, Zhang B, Cao Y, Tian H, Liu R, Sun L, Wang C, Li L, Wang R, Chen Y, Hou X, Li Y, Zhou J, Li L, Tian W. A novel neuroinflammation-responsive hydrogel based on mimicking naked mole rat brain microenvironment retards neurovascular dysfunction and cognitive decline in Alzheimer’s disease. Chem Eng J 2022;430:133090.
  47. Boyd-Kimball D, Sultana R, Mohmmad-Abdul H, Butterfield DA. Rodent Abeta(1-42) exhibits oxidative stress properties similar to those of human Abeta(1-42): Implications for proposed mechanisms of toxicity. J Alzheimers Dis 2004;6:515-525.
  48. Frankel D, Davies M, Bhushan B, Kulaberoglu Y, Urriola-Munoz P, Bertrand-Michel J, Pergande MR, Smith AA, Preet S, Park TJ, Vendruscolo M, Rankin KS,Cologna SM, Kumita JR, Cenac N, John Smith ES. Cholesterol-rich naked mole-rat brain lipid membranes are susceptible to amyloid beta-induced damage in vitro. Aging 2020;12:22266-22290.
  49. Edrey YH, Oddo S, Cornelius C, Caccamo A, Calabrese V, Buffenstein R. Oxidative damage and amyloid-β metabolism in brain regions of the longest-lived rodents. J Neurosci Res 2014;92:195-205.
  50. Steffen J, Krohn M, Paarmann K, Schwitlick C, Brüning T, Marreiros R, Muller-Schiffmann A, Korth C, Braun K, Pahnke J. Revisiting rodent models: Octodon degus as Alzheimer’s disease model? Acta Neuropathol Commun 2016;4:91.
  51. Menendez-Gonzalez M, Gasparovic C. Albumin exchange in Alzheimer’s disease: Might CSF be an alternative route to plasma? Front Neurol 2019;10:1036.
  52. Hashemi M, Zhang Y, Lv Z, Lyubchenko YL. Spontaneous self-assembly of amyloid β (1–40) into dimers. Nanoscale Adv 2019;1:3892-3899.

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