Research Article
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Year 2024, , 1151 - 1164, 30.08.2024
https://doi.org/10.18596/jotcsa.1457169

Abstract

References

  • 1. Hameduh T, Haddad Y, Adam V, Heger Z. Homology modeling in the time of collective and artificial intelligence. Comput Struct Biotechnol J [Internet]. 2020 Jan 1;18:3494–506. Available from: <URL>.
  • 2. Coskuner-Weber O, Uversky VN. Current stage and future perspectives for homology modeling, molecular dynamics simulations, machine learning with molecular dynamics, and quantum computing for intrinsically disordered proteins and proteins with intrinsically disordered regions. Curr Protein Pept Sci [Internet]. 2024 Feb 17;25(2):163–71. Available from: <URL>.
  • 3. Uversky VN. Introduction to Intrinsically disordered proteins (IDPs). Chem Rev [Internet]. 2014 Jul 9;114(13):6557–60. Available from: <URL>.
  • 4. Uversky VN. Dancing protein clouds: The strange biology and chaotic physics of intrinsically disordered proteins. J Biol Chem [Internet]. 2016 Mar 25;291(13):6681–8. Available from: <URL>.
  • 5. Coskuner-Weber O, Mirzanli O, Uversky VN. Intrinsically disordered proteins and proteins with intrinsically disordered regions in neurodegenerative diseases. Biophys Rev [Internet]. 2022 Jun 8;14(3):679–707. Available from: <URL>.
  • 6. Dunker AK, Obradovic Z. The protein trinity—linking function and disorder. Nat Biotechnol [Internet]. 2001 Sep;19(9):805–6. Available from: <URL>.
  • 7. Trivedi R, Nagarajaram HA. Intrinsically disordered proteins: An overview. Int J Mol Sci [Internet]. 2022 Nov 14;23(22):14050. Available from: <URL>.
  • 8. Liu Y, Wang X, Liu B. A comprehensive review and comparison of existing computational methods for intrinsically disordered protein and region prediction. Brief Bioinform [Internet]. 2019 Jan 18;20(1):330–46. Available from: <URL>.
  • 9. Cramer P. AlphaFold2 and the future of structural biology. Nat Struct Mol Biol [Internet]. 2021 Sep 10;28(9):704–5. Available from: <URL>.
  • 10. Bryant P, Pozzati G, Elofsson A. Improved prediction of protein-protein interactions using AlphaFold2. Nat Commun [Internet]. 2022 Mar 10;13(1):1265. Available from: <URL>.
  • 11. Jones DT, Thornton JM. The impact of AlphaFold2 one year on. Nat Methods [Internet]. 2022 Jan 11;19(1):15–20. Available from: <URL>.
  • 12. Jumper J, Evans R, Pritzel A, Green T, Figurnov M, Ronneberger O, et al. Highly accurate protein structure prediction with AlphaFold. Nature [Internet]. 2021 Aug 26;596(7873):583–9. Available from: <URL>.
  • 13. Ruff KM, Pappu R V. AlphaFold and implications for intrinsically disordered proteins. J Mol Biol [Internet]. 2021 Oct 1;433(20):167208. Available from: <URL>.
  • 14. Yang Z, Zeng X, Zhao Y, Chen R. AlphaFold2 and its applications in the fields of biology and medicine. Signal Transduct Target Ther [Internet]. 2023 Mar 14;8(1):115. Available from: <URL>.
  • 15. Cecchini M, Rao F, Seeber M, Caflisch A. Replica exchange molecular dynamics simulations of amyloid peptide aggregation. J Chem Phys [Internet]. 2004 Dec 1;121(21):10748–56. Available from: <URL>.
  • 16. Nguyen PH, Ramamoorthy A, Sahoo BR, Zheng J, Faller P, Straub JE, et al. Amyloid Oligomers: A joint experimental/computational perspective on Alzheimer’s disease, Parkinson’s disease, type II diabetes, and amyotrophic lateral sclerosis. Chem Rev [Internet]. 2021 Feb 24;121(4):2545–647. Available from: <URL>.
  • 17. Nguyen P, Derreumaux P. Understanding amyloid fibril nucleation and Aβ oligomer/drug interactions from computer simulations. Acc Chem Res [Internet]. 2014 Feb 18;47(2):603–11. Available from: <URL>.
  • 18. Coskuner-Weber O, Uversky V. Insights into the molecular mechanisms of Alzheimer’s and Parkinson’s diseases with molecular simulations: Understanding the roles of artificial and pathological missense mutations in intrinsically disordered proteins related to pathology. Int J Mol Sci [Internet]. 2018 Jan 24;19(2):336. Available from: <URL>.
  • 19. Coskuner-Weber O, Uversky VN. Alanine scanning effects on the biochemical and biophysical properties of intrinsically disordered proteins: A case study of the histidine to alanine mutations in amyloid-β 42. J Chem Inf Model [Internet]. 2019 Feb 25;59(2):871–84. Available from: <URL>.
  • 20. Zhou R. Replica exchange molecular dynamics method for protein folding simulation. In: Protein Folding Protocols [Internet]. New Jersey: Humana Press; 2007. p. 205–24. Available from: <URL>.
  • 21. Allison TC, Coskuner O, Gonzalez CA. Metallic systems: A quantum chemist’s perspective [Internet]. Allison TC, Coskuner O, Gonzalez CA, editors. CRC Press; 2011. Available from: <URL>.
  • 22. Coskuner-Weber O, Habiboglu MG, Teplow D, Uversky VN. From quantum mechanics, classical mechanics, and bioinformatics to artificial intelligence studies in neurodegenerative diseases. In: Methods in Molecular Biology [Internet]. Humana, New York, NY; 2022. p. 139–73. Available from: <URL>.
  • 23. Tycko R. Solid-State NMR studies of amyloid fibril structure. Annu Rev Phys Chem [Internet]. 2011 May 5;62(1):279–99. Available from: <URL>.
  • 24. Karamanos TK, Kalverda AP, Thompson GS, Radford SE. Mechanisms of amyloid formation revealed by solution NMR. Prog Nucl Magn Reson Spectrosc [Internet]. 2015 Aug 1;88–89:86–104. Available from: <URL>.
  • 25. Fawzi NL, Ying J, Ghirlando R, Torchia DA, Clore GM. Atomic-resolution dynamics on the surface of amyloid-β protofibrils probed by solution NMR. Nature [Internet]. 2011 Dec 8;480(7376):268–72. Available from: <URL>.
  • 26. Ma B, Nussinov R. Simulations as analytical tools to understand protein aggregation and predict amyloid conformation. Curr Opin Chem Biol [Internet]. 2006 Oct 1;10(5):445–52. Available from: <URL>.
  • 27. Buchete NV, Tycko R, Hummer G. Molecular dynamics simulations of Alzheimer’s β-amyloid protofilaments. J Mol Biol [Internet]. 2005 Nov 4;353(4):804–21. Available from: <URL>.
  • 28. Zhang M, Ren B, Chen H, Sun Y, Ma J, Jiang B, et al. Molecular simulations of amyloid structures, toxicity, and inhibition. Isr J Chem [Internet]. 2017 Jul 16;57(7–8):586–601. Available from: <URL>.
  • 29. Zheng W, Zhang C, Li Y, Pearce R, Bell EW, Zhang Y. Folding non-homologous proteins by coupling deep-learning contact maps with I-TASSER assembly simulations. Cell Reports Methods [Internet]. 2021 Jul 26;1(3):100014. Available from: <URL>.
  • 30. Yang J, Zhang Y. I-TASSER server: New development for protein structure and function predictions. Nucleic Acids Res [Internet]. 2015 Jul 1;43(W1):W174–81. Available from: <URL>.
  • 31. Roy A, Kucukural A, Zhang Y. I-TASSER: a unified platform for automated protein structure and function prediction. Nat Protoc [Internet]. 2010 Apr 25;5(4):725–38. Available from: <URL>.
  • 32. Kelley LA, Mezulis S, Yates CM, Wass MN, Sternberg MJE. The Phyre2 web portal for protein modeling, prediction and analysis. Nat Protoc [Internet]. 2015 Jun 7;10(6):845–58. Available from: <URL>.
  • 33. Waterhouse A, Bertoni M, Bienert S, Studer G, Tauriello G, Gumienny R, et al. SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res [Internet]. 2018 Jul 2;46(W1):W296–303. Available from: <URL>.
  • 34. Akdel M, Pires DE V., Pardo EP, Jänes J, Zalevsky AO, Mészáros B, et al. A structural biology community assessment of AlphaFold2 applications. Nat Struct Mol Biol [Internet]. 2022 Nov 7;29(11):1056–67. Available from: <URL>.
  • 35. Mirdita M, Schütze K, Moriwaki Y, Heo L, Ovchinnikov S, Steinegger M. ColabFold: Making protein folding accessible to all. Nat Methods [Internet]. 2022 Jun 30;19(6):679–82. Available from: <URL>.
  • 36. Shafat Z, Ahmed A, Parvez MK, Parveen S. Intrinsic disorder in the open reading frame 2 of hepatitis E virus: A protein with multiple functions beyond viral capsid. J Genet Eng Biotechnol [Internet]. 2023 Dec 1;21(1):33. Available from: <URL>.
  • 37. O’Brien DP, Hernandez B, Durand D, Hourdel V, Sotomayor-Pérez AC, Vachette P, et al. Structural models of intrinsically disordered and calcium-bound folded states of a protein adapted for secretion. Sci Rep [Internet]. 2015 Sep 16;5(1):14223. Available from: <URL>.
  • 38. Kheirabadi M, Taghdir M. Is unphosphorylated Rex, as multifunctional protein of HTLV-1, a fully intrinsically disordered protein? An in silico study. Biochem Biophys Reports [Internet]. 2016 Dec 1;8:14–22. Available from: <URL>.
  • 39. Yang J, Zhang Y. Protein structure and function prediction using I‐TASSER. Curr Protoc Bioinforma [Internet]. 2015 Dec 17;52(1):5.8.1-5.8.15. Available from: <URL>.
  • 40. Lee YT, Ayoub A, Park SH, Sha L, Xu J, Mao F, et al. Mechanism for DPY30 and ASH2L intrinsically disordered regions to modulate the MLL/SET1 activity on chromatin. Nat Commun [Internet]. 2021 May 19;12(1):2953. Available from: <URL>.
  • 41. Case DA, Aktulga HM, Belfon K, Cerutti DS, Cisneros GA, Cruzeiro VWD, et al. AmberTools. J Chem Inf Model [Internet]. 2023 Oct 23;63(20):6183–91. Available from: <URL>.
  • 42. Caliskan M, Mandaci SY, Uversky VN, Coskuner‐Weber O. Secondary structure dependence of amyloid‐β(1–40) on simulation techniques and force field parameters. Chem Biol Drug Des [Internet]. 2021 May 22;97(5):1100–8. Available from: <URL>.
  • 43. Weber OC, Uversky VN. How accurate are your simulations? Effects of confined aqueous volume and AMBER FF99SB and CHARMM22/CMAP force field parameters on structural ensembles of intrinsically disordered proteins: Amyloid-β 42 in water. Intrinsically Disord Proteins [Internet]. 2017 Jan 30;5(1):e1377813. Available from: <URL>.
  • 44. Darden T, York D, Pedersen L. Particle mesh Ewald: An N ⋅log( N ) method for Ewald sums in large systems. J Chem Phys [Internet]. 1993 Jun 15;98(12):10089–92. Available from: <URL>.
  • 45. Wise-Scira O, Xu L, Kitahara T, Perry G, Coskuner O. Amyloid-β peptide structure in aqueous solution varies with fragment size. J Chem Phys [Internet]. 2011 Nov 28;135(20):1448–57. Available from: <URL>.
  • 46. Sgourakis NG, Yan Y, McCallum SA, Wang C, Garcia AE. The Alzheimer’s Peptides Aβ40 and 42 Adopt Distinct Conformations in Water: A Combined MD / NMR Study. J Mol Biol [Internet]. 2007 May 18;368(5):1448–57. Available from: <URL>.
  • 47. Tomaselli S, Esposito V, Vangone P, van Nuland NAJ, Bonvin AMJJ, Guerrini R, et al. The α‐to‐β Conformational Transition of Alzheimer’s Aβ‐(1–42) Peptide in Aqueous Media is Reversible: A Step by Step Conformational Analysis Suggests the Location of β Conformation Seeding. ChemBioChem [Internet]. 2006 Feb 6;7(2):257–67. Available from: <URL>.
  • 48. Nag S, Sarkar B, Banerjee A, Sahoo B, Varun KAS, Maiti S. The Nature of the Amyloid-β Monomer and the Monomer-Oligomer Equilibrium. Biophys J [Internet]. 2011 Feb 2;100(3):202a. Available from: <URL>.
  • 49. Murray MM, Krone MG, Bernstein SL, Baumketner A, Condron MM, Lazo ND, et al. Amyloid β-protein: Experiment and theory on the 21−30 fragment. J Phys Chem B [Internet]. 2009 Apr 30;113(17):6041–6. Available from: <URL>.
  • 50. Yang M, Teplow DB. Amyloid β-protein monomer folding: Free-energy surfaces reveal alloform-specific differences. J Mol Biol [Internet]. 2008 Dec 12;384(2):450–64. Available from: <URL>.
  • 51. Piovesan D, Del Conte A, Clementel D, Monzon AM, Bevilacqua M, Aspromonte MC, et al. MobiDB: 10 years of intrinsically disordered proteins. Nucleic Acids Res [Internet]. 2023 Jan 6;51(D1):D438–44. Available from: <URL>.

Intrinsically Disordered Proteins by Homology Modeling and Replica Exchange Molecular Dynamics Simulations: A Case Study of Amyloid-β42

Year 2024, , 1151 - 1164, 30.08.2024
https://doi.org/10.18596/jotcsa.1457169

Abstract

Homology modeling emerges as a potent tool unveiling the structural enigma of intrinsically disordered proteins (IDPs), with recent advancements such as AlphaFold2 enhancing the precision of these analyses. The process usually involves identifying homologous proteins with known structures and utilizing their templates to predict the three-dimensional architecture of the target IDP. However, IDPs lack a well-defined three-dimensional structure, and their flexibility makes it difficult to accurately predict their conformations. On the other hand, special sampling molecular dynamics simulations have been shown to be useful in defining the distinct structural properties of IDPs. Here, the structural properties of the disordered amyloid-β42 peptide were predicted using various homology modeling tools including C-I-TASSER, I-TASSER, Phyre2, SwissModel and AlphaFold2. In parallel, extensive replica exchange molecular dynamics simulations of Aβ42 were conducted. Results from homology modeling were compared to our replica exchange molecular dynamics simulations and experiments for gaining insights into the accuracy of homology modeling tools for IDPs used in this work. Based on our findings, none of the homology modeling tools used in this work can capture fully the structural properties of Aβ42. However, C-I-TASSER yields a radius of gyration and tertiary structure properties that are more in accord with the simulations and experimental data rather than I-TASSER, Phyre2, SwissModel and AlphaFold2.

References

  • 1. Hameduh T, Haddad Y, Adam V, Heger Z. Homology modeling in the time of collective and artificial intelligence. Comput Struct Biotechnol J [Internet]. 2020 Jan 1;18:3494–506. Available from: <URL>.
  • 2. Coskuner-Weber O, Uversky VN. Current stage and future perspectives for homology modeling, molecular dynamics simulations, machine learning with molecular dynamics, and quantum computing for intrinsically disordered proteins and proteins with intrinsically disordered regions. Curr Protein Pept Sci [Internet]. 2024 Feb 17;25(2):163–71. Available from: <URL>.
  • 3. Uversky VN. Introduction to Intrinsically disordered proteins (IDPs). Chem Rev [Internet]. 2014 Jul 9;114(13):6557–60. Available from: <URL>.
  • 4. Uversky VN. Dancing protein clouds: The strange biology and chaotic physics of intrinsically disordered proteins. J Biol Chem [Internet]. 2016 Mar 25;291(13):6681–8. Available from: <URL>.
  • 5. Coskuner-Weber O, Mirzanli O, Uversky VN. Intrinsically disordered proteins and proteins with intrinsically disordered regions in neurodegenerative diseases. Biophys Rev [Internet]. 2022 Jun 8;14(3):679–707. Available from: <URL>.
  • 6. Dunker AK, Obradovic Z. The protein trinity—linking function and disorder. Nat Biotechnol [Internet]. 2001 Sep;19(9):805–6. Available from: <URL>.
  • 7. Trivedi R, Nagarajaram HA. Intrinsically disordered proteins: An overview. Int J Mol Sci [Internet]. 2022 Nov 14;23(22):14050. Available from: <URL>.
  • 8. Liu Y, Wang X, Liu B. A comprehensive review and comparison of existing computational methods for intrinsically disordered protein and region prediction. Brief Bioinform [Internet]. 2019 Jan 18;20(1):330–46. Available from: <URL>.
  • 9. Cramer P. AlphaFold2 and the future of structural biology. Nat Struct Mol Biol [Internet]. 2021 Sep 10;28(9):704–5. Available from: <URL>.
  • 10. Bryant P, Pozzati G, Elofsson A. Improved prediction of protein-protein interactions using AlphaFold2. Nat Commun [Internet]. 2022 Mar 10;13(1):1265. Available from: <URL>.
  • 11. Jones DT, Thornton JM. The impact of AlphaFold2 one year on. Nat Methods [Internet]. 2022 Jan 11;19(1):15–20. Available from: <URL>.
  • 12. Jumper J, Evans R, Pritzel A, Green T, Figurnov M, Ronneberger O, et al. Highly accurate protein structure prediction with AlphaFold. Nature [Internet]. 2021 Aug 26;596(7873):583–9. Available from: <URL>.
  • 13. Ruff KM, Pappu R V. AlphaFold and implications for intrinsically disordered proteins. J Mol Biol [Internet]. 2021 Oct 1;433(20):167208. Available from: <URL>.
  • 14. Yang Z, Zeng X, Zhao Y, Chen R. AlphaFold2 and its applications in the fields of biology and medicine. Signal Transduct Target Ther [Internet]. 2023 Mar 14;8(1):115. Available from: <URL>.
  • 15. Cecchini M, Rao F, Seeber M, Caflisch A. Replica exchange molecular dynamics simulations of amyloid peptide aggregation. J Chem Phys [Internet]. 2004 Dec 1;121(21):10748–56. Available from: <URL>.
  • 16. Nguyen PH, Ramamoorthy A, Sahoo BR, Zheng J, Faller P, Straub JE, et al. Amyloid Oligomers: A joint experimental/computational perspective on Alzheimer’s disease, Parkinson’s disease, type II diabetes, and amyotrophic lateral sclerosis. Chem Rev [Internet]. 2021 Feb 24;121(4):2545–647. Available from: <URL>.
  • 17. Nguyen P, Derreumaux P. Understanding amyloid fibril nucleation and Aβ oligomer/drug interactions from computer simulations. Acc Chem Res [Internet]. 2014 Feb 18;47(2):603–11. Available from: <URL>.
  • 18. Coskuner-Weber O, Uversky V. Insights into the molecular mechanisms of Alzheimer’s and Parkinson’s diseases with molecular simulations: Understanding the roles of artificial and pathological missense mutations in intrinsically disordered proteins related to pathology. Int J Mol Sci [Internet]. 2018 Jan 24;19(2):336. Available from: <URL>.
  • 19. Coskuner-Weber O, Uversky VN. Alanine scanning effects on the biochemical and biophysical properties of intrinsically disordered proteins: A case study of the histidine to alanine mutations in amyloid-β 42. J Chem Inf Model [Internet]. 2019 Feb 25;59(2):871–84. Available from: <URL>.
  • 20. Zhou R. Replica exchange molecular dynamics method for protein folding simulation. In: Protein Folding Protocols [Internet]. New Jersey: Humana Press; 2007. p. 205–24. Available from: <URL>.
  • 21. Allison TC, Coskuner O, Gonzalez CA. Metallic systems: A quantum chemist’s perspective [Internet]. Allison TC, Coskuner O, Gonzalez CA, editors. CRC Press; 2011. Available from: <URL>.
  • 22. Coskuner-Weber O, Habiboglu MG, Teplow D, Uversky VN. From quantum mechanics, classical mechanics, and bioinformatics to artificial intelligence studies in neurodegenerative diseases. In: Methods in Molecular Biology [Internet]. Humana, New York, NY; 2022. p. 139–73. Available from: <URL>.
  • 23. Tycko R. Solid-State NMR studies of amyloid fibril structure. Annu Rev Phys Chem [Internet]. 2011 May 5;62(1):279–99. Available from: <URL>.
  • 24. Karamanos TK, Kalverda AP, Thompson GS, Radford SE. Mechanisms of amyloid formation revealed by solution NMR. Prog Nucl Magn Reson Spectrosc [Internet]. 2015 Aug 1;88–89:86–104. Available from: <URL>.
  • 25. Fawzi NL, Ying J, Ghirlando R, Torchia DA, Clore GM. Atomic-resolution dynamics on the surface of amyloid-β protofibrils probed by solution NMR. Nature [Internet]. 2011 Dec 8;480(7376):268–72. Available from: <URL>.
  • 26. Ma B, Nussinov R. Simulations as analytical tools to understand protein aggregation and predict amyloid conformation. Curr Opin Chem Biol [Internet]. 2006 Oct 1;10(5):445–52. Available from: <URL>.
  • 27. Buchete NV, Tycko R, Hummer G. Molecular dynamics simulations of Alzheimer’s β-amyloid protofilaments. J Mol Biol [Internet]. 2005 Nov 4;353(4):804–21. Available from: <URL>.
  • 28. Zhang M, Ren B, Chen H, Sun Y, Ma J, Jiang B, et al. Molecular simulations of amyloid structures, toxicity, and inhibition. Isr J Chem [Internet]. 2017 Jul 16;57(7–8):586–601. Available from: <URL>.
  • 29. Zheng W, Zhang C, Li Y, Pearce R, Bell EW, Zhang Y. Folding non-homologous proteins by coupling deep-learning contact maps with I-TASSER assembly simulations. Cell Reports Methods [Internet]. 2021 Jul 26;1(3):100014. Available from: <URL>.
  • 30. Yang J, Zhang Y. I-TASSER server: New development for protein structure and function predictions. Nucleic Acids Res [Internet]. 2015 Jul 1;43(W1):W174–81. Available from: <URL>.
  • 31. Roy A, Kucukural A, Zhang Y. I-TASSER: a unified platform for automated protein structure and function prediction. Nat Protoc [Internet]. 2010 Apr 25;5(4):725–38. Available from: <URL>.
  • 32. Kelley LA, Mezulis S, Yates CM, Wass MN, Sternberg MJE. The Phyre2 web portal for protein modeling, prediction and analysis. Nat Protoc [Internet]. 2015 Jun 7;10(6):845–58. Available from: <URL>.
  • 33. Waterhouse A, Bertoni M, Bienert S, Studer G, Tauriello G, Gumienny R, et al. SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res [Internet]. 2018 Jul 2;46(W1):W296–303. Available from: <URL>.
  • 34. Akdel M, Pires DE V., Pardo EP, Jänes J, Zalevsky AO, Mészáros B, et al. A structural biology community assessment of AlphaFold2 applications. Nat Struct Mol Biol [Internet]. 2022 Nov 7;29(11):1056–67. Available from: <URL>.
  • 35. Mirdita M, Schütze K, Moriwaki Y, Heo L, Ovchinnikov S, Steinegger M. ColabFold: Making protein folding accessible to all. Nat Methods [Internet]. 2022 Jun 30;19(6):679–82. Available from: <URL>.
  • 36. Shafat Z, Ahmed A, Parvez MK, Parveen S. Intrinsic disorder in the open reading frame 2 of hepatitis E virus: A protein with multiple functions beyond viral capsid. J Genet Eng Biotechnol [Internet]. 2023 Dec 1;21(1):33. Available from: <URL>.
  • 37. O’Brien DP, Hernandez B, Durand D, Hourdel V, Sotomayor-Pérez AC, Vachette P, et al. Structural models of intrinsically disordered and calcium-bound folded states of a protein adapted for secretion. Sci Rep [Internet]. 2015 Sep 16;5(1):14223. Available from: <URL>.
  • 38. Kheirabadi M, Taghdir M. Is unphosphorylated Rex, as multifunctional protein of HTLV-1, a fully intrinsically disordered protein? An in silico study. Biochem Biophys Reports [Internet]. 2016 Dec 1;8:14–22. Available from: <URL>.
  • 39. Yang J, Zhang Y. Protein structure and function prediction using I‐TASSER. Curr Protoc Bioinforma [Internet]. 2015 Dec 17;52(1):5.8.1-5.8.15. Available from: <URL>.
  • 40. Lee YT, Ayoub A, Park SH, Sha L, Xu J, Mao F, et al. Mechanism for DPY30 and ASH2L intrinsically disordered regions to modulate the MLL/SET1 activity on chromatin. Nat Commun [Internet]. 2021 May 19;12(1):2953. Available from: <URL>.
  • 41. Case DA, Aktulga HM, Belfon K, Cerutti DS, Cisneros GA, Cruzeiro VWD, et al. AmberTools. J Chem Inf Model [Internet]. 2023 Oct 23;63(20):6183–91. Available from: <URL>.
  • 42. Caliskan M, Mandaci SY, Uversky VN, Coskuner‐Weber O. Secondary structure dependence of amyloid‐β(1–40) on simulation techniques and force field parameters. Chem Biol Drug Des [Internet]. 2021 May 22;97(5):1100–8. Available from: <URL>.
  • 43. Weber OC, Uversky VN. How accurate are your simulations? Effects of confined aqueous volume and AMBER FF99SB and CHARMM22/CMAP force field parameters on structural ensembles of intrinsically disordered proteins: Amyloid-β 42 in water. Intrinsically Disord Proteins [Internet]. 2017 Jan 30;5(1):e1377813. Available from: <URL>.
  • 44. Darden T, York D, Pedersen L. Particle mesh Ewald: An N ⋅log( N ) method for Ewald sums in large systems. J Chem Phys [Internet]. 1993 Jun 15;98(12):10089–92. Available from: <URL>.
  • 45. Wise-Scira O, Xu L, Kitahara T, Perry G, Coskuner O. Amyloid-β peptide structure in aqueous solution varies with fragment size. J Chem Phys [Internet]. 2011 Nov 28;135(20):1448–57. Available from: <URL>.
  • 46. Sgourakis NG, Yan Y, McCallum SA, Wang C, Garcia AE. The Alzheimer’s Peptides Aβ40 and 42 Adopt Distinct Conformations in Water: A Combined MD / NMR Study. J Mol Biol [Internet]. 2007 May 18;368(5):1448–57. Available from: <URL>.
  • 47. Tomaselli S, Esposito V, Vangone P, van Nuland NAJ, Bonvin AMJJ, Guerrini R, et al. The α‐to‐β Conformational Transition of Alzheimer’s Aβ‐(1–42) Peptide in Aqueous Media is Reversible: A Step by Step Conformational Analysis Suggests the Location of β Conformation Seeding. ChemBioChem [Internet]. 2006 Feb 6;7(2):257–67. Available from: <URL>.
  • 48. Nag S, Sarkar B, Banerjee A, Sahoo B, Varun KAS, Maiti S. The Nature of the Amyloid-β Monomer and the Monomer-Oligomer Equilibrium. Biophys J [Internet]. 2011 Feb 2;100(3):202a. Available from: <URL>.
  • 49. Murray MM, Krone MG, Bernstein SL, Baumketner A, Condron MM, Lazo ND, et al. Amyloid β-protein: Experiment and theory on the 21−30 fragment. J Phys Chem B [Internet]. 2009 Apr 30;113(17):6041–6. Available from: <URL>.
  • 50. Yang M, Teplow DB. Amyloid β-protein monomer folding: Free-energy surfaces reveal alloform-specific differences. J Mol Biol [Internet]. 2008 Dec 12;384(2):450–64. Available from: <URL>.
  • 51. Piovesan D, Del Conte A, Clementel D, Monzon AM, Bevilacqua M, Aspromonte MC, et al. MobiDB: 10 years of intrinsically disordered proteins. Nucleic Acids Res [Internet]. 2023 Jan 6;51(D1):D438–44. Available from: <URL>.
There are 51 citations in total.

Details

Primary Language English
Subjects Biomolecular Modelling and Design
Journal Section RESEARCH ARTICLES
Authors

Orkid Coskuner Weber 0000-0002-0772-9350

Early Pub Date July 26, 2024
Publication Date August 30, 2024
Submission Date March 22, 2024
Acceptance Date June 22, 2024
Published in Issue Year 2024

Cite

Vancouver Coskuner Weber O. Intrinsically Disordered Proteins by Homology Modeling and Replica Exchange Molecular Dynamics Simulations: A Case Study of Amyloid-β42. JOTCSA. 2024;11(3):1151-64.