References
1. 2021 Alzheimer’s disease facts and figures. Alzheimer’s & Dementia. 2021;17(3):327-406.
2. Gauthier S R-NP, Morais JA, & Webster C. World Alzheimer Report 2021:Journey
through the diagnosis of dementia Alzheimer’s & Dementia. 2021.
3. Yiannopoulou KG, Papageorgiou SG. Current and future treatments in Alzheimer disease: an update. Journal of central nervous system disease. 2020;12:1179573520907397.
4. Vaz M, Silvestre S. Alzheimer’s disease: Recent treatment strategies. European Journal of Pharmacology. 2020:173554.
5. Selkoe DJ, Hardy J. The amyloid hypothesis of Alzheimer’s disease at 25 years. EMBO molecular medicine. 2016;8(6):595-608.
6. Kametani F, Hasegawa M. Reconsideration of Amyloid Hypothesis and Tau Hypothesis in Alzheimer’s Disease. Front Neurosci. 2018;12:25-.
7. Poorkaj P, Bird TD, Wijsman E, Nemens E, Garruto RM, Anderson L, et al. Tau is a candidate gene for chromosome 17 frontotemporal dementia. Annals of neurology. 1998;43(6):815-25.
8. Himmler A, Drechsel D, Kirschner MW, Martin Jr DW. Tau consists of a set of proteins with repeated C-terminal microtubule-binding domains and variable N-terminal domains. Molecular and cellular biology. 1989;9(4):1381-8.
9. Goedert M, Spillantini M, Jakes R, Rutherford D, Crowther R. Multiple isoforms of human microtubule-associated protein tau: sequences and localization in neurofibrillary tangles of Alzheimer’s disease. Neuron. 1989;3(4):519-26.
10. Panda D, Samuel JC, Massie M, Feinstein SC, Wilson L. Differential regulation of microtubule dynamics by three-and four-repeat tau: implications for the onset of neurodegenerative disease. Proceedings of the National Academy of Sciences. 2003;100(16):9548-53.
11. Wang J-Z, Liu F. Microtubule-associated protein tau in development, degeneration and protection of neurons. Progress in neurobiology. 2008;85(2):148-75.
12. Drubin DG, Kirschner MW. Tau protein function in living cells. Journal of Cell Biology. 1986;103(6):2739-46.
13. Mukrasch MD, Bibow S, Korukottu J, Jeganathan S, Biernat J, Griesinger C, et al. Structural polymorphism of 441-residue tau at single residue resolution. PLoS biology. 2009;7(2):e1000034.
14. Lu S, Wagaman AS. On methods for determining solvent accessible surface area for proteins in their unfolded state. BMC research notes. 2014;7(1):1-7.
15. Alonso AdC, Zaidi T, Grundke-Iqbal I, Iqbal K. Role of abnormally phosphorylated tau in the breakdown of microtubules in Alzheimer disease. Proceedings of the National Academy of Sciences. 1994;91(12):5562-6.
16. LeBoeuf AC, Levy SF, Gaylord M, Bhattacharya A, Singh AK, Jordan MA, et al. FTDP-17 mutations in Tau alter the regulation of microtubule dynamics. Journal of Biological Chemistry. 2008;283(52):36406-15.
17. Gustke N, Trinczek B, Biernat J, Mandelkow E-M, Mandelkow E. Domains of tau protein and interactions with microtubules. Biochemistry. 1994;33(32):9511-22.
18. Barbier P, Zejneli O, Martinho M, Lasorsa A, Belle V, Smet-Nocca C, et al. Role of Tau as a Microtubule-Associated Protein: Structural and Functional Aspects. Frontiers in Aging Neuroscience. 2019;11(204).
19. Uversky VN. Intrinsically disordered proteins and their (disordered) proteomes in neurodegenerative disorders. Frontiers in aging neuroscience. 2015;7:18.
20. Alquezar C, Arya S, Kao AW. Tau post-translational modifications: Dynamic transformers of tau function, degradation, and aggregation. Frontiers in Neurology. 2021:1826.
21. Alquezar C, Arya S, Kao AW. Tau Post-translational Modifications: Dynamic Transformers of Tau Function, Degradation, and Aggregation. Frontiers in Neurology. 2020;11.
22. Haukedal H, Freude KK. Implications of Glycosylation in Alzheimer’s Disease. Front Neurosci. 2020;14:625348.
23. Ryan P, Xu M, Davey AK, Danon JJ, Mellick GD, Kassiou M, et al. O-GlcNAc modification protects against protein misfolding and aggregation in neurodegenerative disease. ACS chemical neuroscience. 2019;10(5):2209-21.
24. Hart GW, Slawson C, Ramirez-Correa G, Lagerlof O. Cross talk between O-GlcNAcylation and phosphorylation: roles in signaling, transcription, and chronic disease. Annual review of biochemistry. 2011;80:825-58.
25. Liu F, Zaidi T, Iqbal K, Grundke-Iqbal I, Merkle RK, Gong CX. Role of glycosylation in hyperphosphorylation of tau in Alzheimer’s disease. FEBS letters. 2002;512(1-3):101-6.
26. Sato Y, Naito Y, Grundke-Iqbal I, Iqbal K, Endo T. Analysis of N-glycans of pathological tau: possible occurrence of aberrant processing of tau in Alzheimer’s disease. FEBS letters. 2001;496(2-3):152-60.
27. Liu F, Zaidi T, Iqbal K, Grundke-Iqbal I, Merkle RK, Gong C-X. Role of glycosylation in hyperphosphorylation of tau in Alzheimer’s disease. FEBS letters. 2002;512(1-3):101-6.
28. Haukedal H, Freude KK. Implications of glycosylation in Alzheimer’s disease. Front Neurosci. 2021;14:1432.
29. Aebi M. N-linked protein glycosylation in the ER. Biochimica et Biophysica Acta (BBA)-Molecular Cell Research. 2013;1833(11):2430-7.
30. Wang J-Z, Grundke-Iqbal I, Iqbal K. Glycosylation of microtubule–associated protein tau: An abnormal posttranslational modification in Alzheimer’s disease. Nature medicine. 1996;2(8):871-5.
31. Losev Y, Frenkel-Pinter M, Abu-Hussien M, Viswanathan GK, Elyashiv-Revivo D, Geries R, et al. Differential effects of putative N-glycosylation sites in human Tau on Alzheimer’s disease-related neurodegeneration. Cellular and Molecular Life Sciences. 2021;78(5):2231-45.
32. Hospital A, Goñi JR, Orozco M, Gelpí JL. Molecular dynamics simulations: advances and applications. Advances and applications in bioinformatics and chemistry: AABC. 2015;8:37.
33. Durrant JD, McCammon JA. Molecular dynamics simulations and drug discovery. BMC Biology. 2011;9(1):71.
34. Barbier P, Zejneli O, Martinho M, Lasorsa A, Belle V, Smet-Nocca C, et al. Role of tau as a microtubule-associated protein: structural and functional aspects. Frontiers in Aging Neuroscience. 2019;11:204.
35. Fitzpatrick AW, Falcon B, He S, Murzin AG, Murshudov G, Garringer HJ, et al. Cryo-EM structures of tau filaments from Alzheimer’s disease. Nature. 2017;547(7662):185-90.
36. Wang JZ, Xia YY, Grundke-Iqbal I, Iqbal K. Abnormal hyperphosphorylation of tau: sites, regulation, and molecular mechanism of neurofibrillary degeneration. Journal of Alzheimer’s disease : JAD. 2013;33 Suppl 1:S123-39.
37. Sneha P, George Priya Doss C. Chapter Seven - Molecular Dynamics: New Frontier in Personalized Medicine. In: Donev R, editor. Advances in Protein Chemistry and Structural Biology. 102: Academic Press; 2016. p. 181-224.
38. Prigozhin MB, Scott GE, Denos S. Mechanical modeling and computer simulation of protein folding. Journal of Chemical Education. 2014;91(11):1939-42.
39. Sandoval C. Molecular Dynamics Simulation of Synthetic Polymers. Molecular Dynamics-Studies of Synthetic and Biological Macromolecules: IntechOpen; 2012.
40. Ausaf Ali S, Hassan I, Islam A, Ahmad F. A review of methods available to estimate solvent-accessible surface areas of soluble proteins in the folded and unfolded states. Current Protein and Peptide Science. 2014;15(5):456-76.
41. David CC, Jacobs DJ. Principal component analysis: a method for determining the essential dynamics of proteins. Protein dynamics: Springer; 2014. p. 193-226.
42. Tramontano A, Cozzetto D. The relationship between protein sequence, structure and function. Supramolecular Structure and Function 8: Springer; 2005. p. 15-29.
43. Valastyan JS, Lindquist S. Mechanisms of protein-folding diseases at a glance. Dis Model Mech. 2014;7(1):9-14.
44. Soeda Y, Takashima A. New insights into drug discovery targeting tau protein. Frontiers in Molecular Neuroscience. 2020;13.
45. von Bergen M, Barghorn S, Biernat J, Mandelkow E-M, Mandelkow E. Tau aggregation is driven by a transition from random coil to beta sheet structure. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 2005;1739(2):158-66.
46. Kabsch W, Sander C. Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers. 1983;22(12):2577-637.
47. Onuchic JN, Luthey-Schulten Z, Wolynes PG. Theory of protein folding: the energy landscape perspective. Annual review of physical chemistry. 1997;48(1):545-600.
48. Mallamace F, Corsaro C, Mallamace D, Vasi S, Vasi C, Baglioni P, et al. Energy landscape in protein folding and unfolding. Proceedings of the National Academy of Sciences. 2016;113(12):3159-63.
49. Gianni S, Freiberger MI, Jemth P, Ferreiro DU, Wolynes PG, Fuxreiter M. Fuzziness and frustration in the energy landscape of protein folding, function, and assembly. Accounts of chemical research. 2021;54(5):1251-9.
50. Chong S-H, Ham S. Folding free energy landscape of ordered and intrinsically disordered proteins. Scientific reports. 2019;9(1):1-9.
51. Strodel B. Energy landscapes of protein aggregation and conformation switching in intrinsically disordered proteins. Journal of Molecular Biology. 2021:167182.
52. Jong K, Grisanti L, Hassanali A. Hydrogen Bond Networks and Hydrophobic Effects in the Amyloid β30–35 Chain in Water: A Molecular Dynamics Study. Journal of Chemical Information and Modeling. 2017;57(7):1548-62.
53. Di Paola L, De Ruvo M, Paci P, Santoni D, Giuliani A. Protein contact networks: an emerging paradigm in chemistry. Chemical reviews. 2013;113(3):1598-613.
54. O’Rourke KF, Gorman SD, Boehr DD. Biophysical and computational methods to analyze amino acid interaction networks in proteins. Computational and structural biotechnology journal. 2016;14:245-51.
55. Brysbaert G, Lensink M. Centrality Measures in Residue Interaction Networks to Highlight Amino Acids in Protein–Protein Binding. 2021.
56. Dokholyan NV, Li L, Ding F, Shakhnovich EI. Topological determinants of protein folding. Proceedings of the National Academy of Sciences. 2002;99(13):8637-41.
57. Soundararajan V, Raman R, Raguram S, Sasisekharan V, Sasisekharan R. Atomic interaction networks in the core of protein domains and their native folds. PLoS One. 2010;5(2):e9391.
58. Süel GM, Lockless SW, Wall MA, Ranganathan R. Evolutionarily conserved networks of residues mediate allosteric communication in proteins. Nature structural biology. 2003;10(1):59-69.
59. Lopes TJS, Rios R, Nogueira T, Mello RF. Protein residue network analysis reveals fundamental properties of the human coagulation factor VIII. Scientific Reports. 2021;11(1):12625.
60. Yadav M, Igarashi M, Yamamoto N. Dynamic residue interaction network analysis of the oseltamivir binding site of N1 neuraminidase and its H274Y mutation site conferring drug resistance in influenza A virus. PeerJ. 2021;9:e11552.
61. Oldham S, Fulcher B, Parkes L, Arnatkevic Iūtė A, Suo C, Fornito A. Consistency and differences between centrality measures across distinct classes of networks. PLoS One. 2019;14(7):e0220061.
62. Yu H, Kim PM, Sprecher E, Trifonov V, Gerstein M. The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics. PLoS Comput Biol. 2007;3(4):e59.
63. Vendruscolo M, Dokholyan NV, Paci E, Karplus M. Small-world view of the amino acids that play a key role in protein folding. Physical Review E. 2002;65(6):061910.
64. Karain WI, Qaraeen NI. Weighted protein residue networks based on joint recurrences between residues. BMC Bioinformatics. 2015;16(1):173.
65. Dokholyan NV, Li L, Ding F, Shakhnovich EI. Topological determinants of protein folding. Proceedings of the National Academy of Sciences. 2002;99(13):8637.
66. Amitai G, Shemesh A, Sitbon E, Shklar M, Netanely D, Venger I, et al. Network analysis of protein structures identifies functional residues. J Mol Biol. 2004;344(4):1135-46.
67. Fitzpatrick AWP, Falcon B, He S, Murzin AG, Murshudov G, Garringer HJ, et al. Cryo-EM structures of tau filaments from Alzheimer’s disease. Nature. 2017;547(7662):185-90.
68. Sato Y, Naito Y, Grundke-Iqbal I, Iqbal K, Endo T. Analysis of N-glycans of pathological tau: possible occurrence of aberrant processing of tau in Alzheimer’s disease. FEBS Lett. 2001;496(2-3):152-60.
69. Zhang W, Tarutani A, Newell KL, Murzin AG, Matsubara T, Falcon B, et al. Novel tau filament fold in corticobasal degeneration. Nature. 2020;580(7802):283-7.
70. Jo S, Kim T, Iyer VG, Im W. CHARMM-GUI: a web-based graphical user interface for CHARMM. Journal of computational chemistry. 2008;29(11):1859-65.
71. Huang J, Rauscher S, Nawrocki G, Ran T, Feig M, de Groot BL, et al. CHARMM36m: an improved force field for folded and intrinsically disordered proteins. Nature Methods. 2017;14(1):71-3.
72. Bonate PL. A Brief Introduction to Monte Carlo Simulation. Clinical Pharmacokinetics. 2001;40(1):15-22.
73. Hess B, Bekker H, Berendsen HJC, Fraaije JGEM. LINCS: A linear constraint solver for molecular simulations. Journal of computational chemistry. 1997;18(12):1463-72.
74. Sidler D, Riniker S. Fast Nosé–Hoover thermostat: molecular dynamics in quasi-thermodynamic equilibrium. Physical Chemistry Chemical Physics. 2019;21(11):6059-70.
75. Parrinello M, Rahman A. Strain fluctuations and elastic constants. The Journal of Chemical Physics. 1982;76(5):2662-6.
76. Harvey MJ, De Fabritiis G. An Implementation of the Smooth Particle Mesh Ewald Method on GPU Hardware. Journal of chemical theory and computation. 2009;5(9):2371-7.
77. Van Der Spoel D, Lindahl E, Hess B, Groenhof G, Mark AE, Berendsen HJ. GROMACS: fast, flexible, and free. Journal of computational chemistry. 2005;26(16):1701-18.
78. Abraham MJ, Murtola T, Schulz R, Páll S, Smith JC, Hess B, et al. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX. 2015;1-2:19-25.
79. Maiorov VN, Crippen GM. Size-independent comparison of protein three-dimensional structures. Proteins. 1995;22(3):273-83.
80. Humphrey W, Dalke A, Schulten K. VMD: visual molecular dynamics. Journal of molecular graphics. 1996;14(1):33-8, 27-8.
81. Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, et al. UCSF Chimera–a visualization system for exploratory research and analysis. Journal of computational chemistry. 2004;25(13):1605-12.
82. Morris JH, Huang CC, Babbitt PC, Ferrin TE. structureViz: linking Cytoscape and UCSF Chimera. Bioinformatics (Oxford, England). 2007;23(17):2345-7.
83. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome research. 2003;13(11):2498-504.
84. Tang Y, Li M, Wang J, Pan Y, Wu FX. CytoNCA: a cytoscape plugin for centrality analysis and evaluation of protein interaction networks. Bio Systems. 2015;127:67-72.