Dynamical comparison between Drosha and Dicer reveals functional motion similarities and dissimilarities
Autoři:
Rotem Aharoni aff001; Dror Tobi aff001
Působiště autorů:
Department of Molecular Biology, Ariel University, Ariel, Israel
aff001; Department of Computer Sciences, Ariel University, Ariel, Israel
aff002
Vyšlo v časopise:
PLoS ONE 14(12)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0226147
Souhrn
Drosha and Dicer are RNase III family members of classes II and III, respectively, which play a major role in the maturation of micro-RNAs. The two proteins share similar domain arrangement and overall fold despite no apparent sequence homology. The overall structural and catalytic reaction similarity of both proteins, on the one hand, and differences in the substrate and its binding mechanisms, on the other, suggest that both proteins also share dynamic similarities and dissimilarities. Since dynamics is essential for protein function, a comparison at their dynamics level is fundamental for a complete understanding of the overall relations between these proteins. In this study, we present a dynamical comparison between human Drosha and Giardia Dicer. Gaussian Network Model and Anisotropic Network Model modes of motion of the proteins are calculated. Dynamical comparison is performed using global and local dynamic programming algorithms for aligning modes of motion. These algorithms were recently developed based on the commonly used Needleman-Wunsch and Smith-Waterman algorithms for global and local sequence alignment. The slowest mode of Drosha is different from that of Dicer due to its more bended posture and allow the motion of the double-stranded RNA-binding domain toward and away from its substrate. Among the five slowest modes dynamics similarity exists only for the second slow mode of motion of Drosha and Dicer. In addition, high local dynamics similarity is observed at the catalytic domains, in the vicinity of the catalytic residues. The results suggest that the proteins exert a similar catalytic mechanism using similar motions, especially at the catalytic sites.
Klíčová slova:
Double stranded RNA – Giardia – MicroRNAs – Network analysis – Protein structure – Protein structure comparison – Ribonucleases – Sequence alignment
Zdroje
1. Needleman SB, Wunsch CD. A general method applicable to the search for similarities in the amino acid sequence of two proteins. J Mol Biol. 1970;48(3):443–53. Epub 1970/03/01. 0022-2836(70)90057-4 [pii]. doi: 10.1016/0022-2836(70)90057-4 5420325.
2. Smith TF, Waterman MS. Identification of common molecular subsequences. J Mol Biol. 1981;147(1):195–7. doi: 10.1016/0022-2836(81)90087-5 7265238.
3. Thompson JD, Higgins DG, Gibson TJ. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 1994;22(22):4673–80. doi: 10.1093/nar/22.22.4673 7984417; PubMed Central PMCID: PMC308517.
4. Pearl FM, Bennett CF, Bray JE, Harrison AP, Martin N, Shepherd A, et al. The CATH database: an extended protein family resource for structural and functional genomics. Nucleic Acids Res. 2003;31(1):452–5. Epub 2003/01/10. doi: 10.1093/nar/gkg062 12520050; PubMed Central PMCID: PMC165509.
5. Andreeva A, Howorth D, Brenner SE, Hubbard TJ, Chothia C, Murzin AG. SCOP database in 2004: refinements integrate structure and sequence family data. Nucleic Acids Res. 2004;32(Database issue):D226–9. Epub 2003/12/19. doi: 10.1093/nar/gkh039 32/suppl_1/D226 [pii]. 14681400; PubMed Central PMCID: PMC308773.
6. Holm L, Rosenstrom P. Dali server: conservation mapping in 3D. Nucleic Acids Res. 2010;38(Web Server issue):W545–9. Epub 2010/05/12. gkq366 [pii] doi: 10.1093/nar/gkq366 20457744; PubMed Central PMCID: PMC2896194.
7. Bakan A, Meireles LM, Bahar I. ProDy: protein dynamics inferred from theory and experiments. Bioinformatics. 2011;27(11):1575–7. Epub 2011/04/08. btr168 [pii] doi: 10.1093/bioinformatics/btr168 21471012; PubMed Central PMCID: PMC3102222.
8. Maguid S, Fernandez-Alberti S, Echave J. Evolutionary conservation of protein vibrational dynamics. Gene. 2008;422(1–2):7–13. Epub 2008/06/26. S0378-1119(08)00228-X [pii] doi: 10.1016/j.gene.2008.06.002 18577430.
9. Maguid S, Fernandez-Alberti S, Ferrelli L, Echave J. Exploring the common dynamics of homologous proteins. Application to the globin family. Biophys J. 2005;89(1):3–13. Epub 2005/03/08. S0006-3495(05)72652-7 [pii] doi: 10.1529/biophysj.104.053041 15749782; PubMed Central PMCID: PMC1366528.
10. Tobi D. Dynamics alignment: comparison of protein dynamics in the SCOP database. Proteins. 2012;80(4):1167–76. Epub 2012/01/26. doi: 10.1002/prot.24017 22275069.
11. Tobi D. Large-scale analysis of the dynamics of enzymes. Proteins. 2013;81:1910–8. Epub 2013/06/06. doi: 10.1002/prot.24335 23737241.
12. Tobi D. Normal Mode Dynamics Comparison of Proteins. Isr J Chem. 2014; doi: 10.1002/ijch.201300142
13. Tobi D. Dynamical differences of hemoglobin and the ionotropic glutamate receptor in different states revealed by a new dynamics alignment method. Proteins. 2017;85(8):1507–17. doi: 10.1002/prot.25311 28459140.
14. Munz M, Lyngso R, Hein J, Biggin PC. Dynamics based alignment of proteins: an alternative approach to quantify dynamic similarity. BMC Bioinformatics. 2010;11:188. Epub 2010/04/20. 1471-2105-11-188 [pii] doi: 10.1186/1471-2105-11-188 20398246; PubMed Central PMCID: PMC2868010.
15. Micheletti C. Comparing proteins by their internal dynamics: exploring structure-function relationships beyond static structural alignments. Phys Life Rev. 2013;10(1):1–26. Epub 2012/12/04. S1571-0645(12)00132-7 [pii] doi: 10.1016/j.plrev.2012.10.009 23199577.
16. Fuglebakk E, Tiwari SP, Reuter N. Comparing the intrinsic dynamics of multiple protein structures using elastic network models. Biochim Biophys Acta. 2015;1850(5):911–22. doi: 10.1016/j.bbagen.2014.09.021 25267310.
17. Tiwari SP, Reuter N. Conservation of intrinsic dynamics in proteins-what have computational models taught us? Curr Opin Struct Biol. 2017;50:75–81. doi: 10.1016/j.sbi.2017.12.001 29287233.
18. Bahar I, Atilgan AR, Erman B. Direct evaluation of thermal fluctuations in proteins using a single-parameter harmonic potential. Fold Des. 1997;2(3):173–81. Epub 1997/01/01. doi: 10.1016/S1359-0278(97)00024-2 9218955.
19. Eyal E, Chennubhotla C, Yang LW, Bahar I. Anisotropic fluctuations of amino acids in protein structures: insights from X-ray crystallography and elastic network models. Bioinformatics. 2007;23(13):i175–84. Epub 2007/07/25. 23/13/i175 [pii] doi: 10.1093/bioinformatics/btm186 17646294.
20. Atilgan AR, Durell SR, Jernigan RL, Demirel MC, Keskin O, Bahar I. Anisotropy of fluctuation dynamics of proteins with an elastic network model. Biophys J. 2001;80(1):505–15. Epub 2001/02/13. S0006-3495(01)76033-X [pii] doi: 10.1016/S0006-3495(01)76033-X 11159421; PubMed Central PMCID: PMC1301252.
21. Kitao A, Go N. Investigating protein dynamics in collective coordinate space. Curr Opin Struct Biol. 1999;9(2):164–9. Epub 1999/05/14. S0959-440X(99)80023-2 [pii] doi: 10.1016/S0959-440X(99)80023-2 10322205.
22. Bahar I, Lezon TR, Yang LW, Eyal E. Global dynamics of proteins: bridging between structure and function. Annu Rev Biophys. 2010;39:23–42. Epub 2010/03/03. doi: 10.1146/annurev.biophys.093008.131258 20192781; PubMed Central PMCID: PMC2938190.
23. Klepeis JL, Lindorff-Larsen K, Dror RO, Shaw DE. Long-timescale molecular dynamics simulations of protein structure and function. Curr Opin Struct Biol. 2009;19(2):120–7. Epub 2009/04/14. S0959-440X(09)00037-2 [pii] doi: 10.1016/j.sbi.2009.03.004 19361980.
24. Shaw DE, Maragakis P, Lindorff-Larsen K, Piana S, Dror RO, Eastwood MP, et al. Atomic-level characterization of the structural dynamics of proteins. Science. 2010;330(6002):341–6. Epub 2010/10/16. 330/6002/341 [pii] doi: 10.1126/science.1187409 20947758.
25. Gur M, Zomot E, Bahar I. Global motions exhibited by proteins in micro- to milliseconds simulations concur with anisotropic network model predictions. J Chem Phys. 2013;139(12):121912. Epub 2013/10/05. doi: 10.1063/1.4816375 24089724; PubMed Central PMCID: PMC3739829.
26. MacRae IJ, Doudna JA. Ribonuclease revisited: structural insights into ribonuclease III family enzymes. Curr Opin Struct Biol. 2007;17(1):138–45. doi: 10.1016/j.sbi.2006.12.002 17194582.
27. Conrad C, Rauhut R. Ribonuclease III: new sense from nuisance. Int J Biochem Cell Biol. 2002;34(2):116–29. doi: 10.1016/s1357-2725(01)00112-1 11809414.
28. Filippov V, Solovyev V, Filippova M, Gill SS. A novel type of RNase III family proteins in eukaryotes. Gene. 2000;245(1):213–21. doi: 10.1016/s0378-1119(99)00571-5 10713462.
29. Nicholson AW. Ribonuclease III mechanisms of double-stranded RNA cleavage. Wiley Interdiscip Rev RNA. 2014;5(1):31–48. doi: 10.1002/wrna.1195 24124076; PubMed Central PMCID: PMC3867540.
30. Gan J, Shaw G, Tropea JE, Waugh DS, Court DL, Ji X. A stepwise model for double-stranded RNA processing by ribonuclease III. Mol Microbiol. 2008;67(1):143–54. doi: 10.1111/j.1365-2958.2007.06032.x 18047582.
31. Lee Y, Ahn C, Han J, Choi H, Kim J, Yim J, et al. The nuclear RNase III Drosha initiates microRNA processing. Nature. 2003;425(6956):415–9. doi: 10.1038/nature01957 14508493.
32. Brodersen P, Voinnet O. The diversity of RNA silencing pathways in plants. Trends Genet. 2006;22(5):268–80. doi: 10.1016/j.tig.2006.03.003 16567016.
33. Han J, Lee Y, Yeom KH, Kim YK, Jin H, Kim VN. The Drosha-DGCR8 complex in primary microRNA processing. Genes Dev. 2004;18(24):3016–27. doi: 10.1101/gad.1262504 15574589; PubMed Central PMCID: PMC535913.
34. Lee Y, Kim M, Han J, Yeom KH, Lee S, Baek SH, et al. MicroRNA genes are transcribed by RNA polymerase II. EMBO J. 2004;23(20):4051–60. doi: 10.1038/sj.emboj.7600385 15372072; PubMed Central PMCID: PMC524334.
35. Kwon SC, Nguyen TA, Choi YG, Jo MH, Hohng S, Kim VN, et al. Structure of Human DROSHA. Cell. 2016;164(1–2):81–90. doi: 10.1016/j.cell.2015.12.019 26748718.
36. Li S, Patel DJ. Drosha and Dicer: Slicers cut from the same cloth. Cell Res. 2016;26(5):511–2. doi: 10.1038/cr.2016.19 27125999; PubMed Central PMCID: PMC4856758.
37. Zhang H, Kolb FA, Jaskiewicz L, Westhof E, Filipowicz W. Single processing center models for human Dicer and bacterial RNase III. Cell. 2004;118(1):57–68. doi: 10.1016/j.cell.2004.06.017 15242644.
38. Nguyen TA, Jo MH, Choi YG, Park J, Kwon SC, Hohng S, et al. Functional Anatomy of the Human Microprocessor. Cell. 2015;161(6):1374–87. doi: 10.1016/j.cell.2015.05.010 26027739.
39. Han J, Lee Y, Yeom KH, Nam JW, Heo I, Rhee JK, et al. Molecular basis for the recognition of primary microRNAs by the Drosha-DGCR8 complex. Cell. 2006;125(5):887–901. doi: 10.1016/j.cell.2006.03.043 16751099.
40. Macrae IJ, Zhou K, Li F, Repic A, Brooks AN, Cande WZ, et al. Structural basis for double-stranded RNA processing by Dicer. Science. 2006;311(5758):195–8. doi: 10.1126/science.1121638 16410517.
41. Macrae IJ, Li F, Zhou K, Cande WZ, Doudna JA. Structure of Dicer and mechanistic implications for RNAi. Cold Spring Harb Symp Quant Biol. 2006;71:73–80. doi: 10.1101/sqb.2006.71.042 17381283.
42. Starega-Roslan J, Galka-Marciniak P, Krzyzosiak WJ. Nucleotide sequence of miRNA precursor contributes to cleavage site selection by Dicer. Nucleic Acids Res. 2015;43(22):10939–51. doi: 10.1093/nar/gkv968 26424848; PubMed Central PMCID: PMC4678860.
43. Zamore PD. Thirty-three years later, a glimpse at the ribonuclease III active site. Mol Cell. 2001;8(6):1158–60. doi: 10.1016/s1097-2765(01)00418-x 11885596.
44. Denli AM, Tops BB, Plasterk RH, Ketting RF, Hannon GJ. Processing of primary microRNAs by the Microprocessor complex. Nature. 2004;432(7014):231–5. doi: 10.1038/nature03049 15531879.
45. Gregory RI, Yan KP, Amuthan G, Chendrimada T, Doratotaj B, Cooch N, et al. The Microprocessor complex mediates the genesis of microRNAs. Nature. 2004;432(7014):235–40. doi: 10.1038/nature03120 15531877.
46. Aharoni R, Tobi D. Dynamical comparison between myoglobin and hemoglobin. Proteins. 2018;86(11):1176–83. doi: 10.1002/prot.25598 30183107.
47. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, et al. The Protein Data Bank. Nucleic Acids Res. 2000;28(1):235–42. Epub 1999/12/11. gkd090 [pii]. doi: 10.1093/nar/28.1.235 10592235; PubMed Central PMCID: PMC102472.
48. Burley SK, Berman HM, Bhikadiya C, Bi C, Chen L, Di Costanzo L, et al. RCSB Protein Data Bank: biological macromolecular structures enabling research and education in fundamental biology, biomedicine, biotechnology and energy. Nucleic Acids Res. 2019;47(D1):D464–D74. doi: 10.1093/nar/gky1004 30357411; PubMed Central PMCID: PMC6324064.
49. Guex N, Peitsch MC. SWISS-MODEL and the Swiss-PdbViewer: an environment for comparative protein modeling. Electrophoresis. 1997;18(15):2714–23. doi: 10.1002/elps.1150181505 9504803.
50. Doruker P, Atilgan AR, Bahar I. Dynamics of proteins predicted by molecular dynamics simulations and analytical approaches: application to alpha-amylase inhibitor. Proteins. 2000;40(3):512–24. Epub 2000/06/22. doi: 10.1002/1097-0134(20000815)40:3<512::AID-PROT180>3.0.CO;2-M [pii]. 10861943.
51. Hensen U, Meyer T, Haas J, Rex R, Vriend G, Grubmuller H. Exploring protein dynamics space: the dynasome as the missing link between protein structure and function. PLoS One. 2012;7(5):e33931. Epub 2012/05/19. doi: 10.1371/journal.pone.0033931 PONE-D-11-18707 [pii]. 22606222; PubMed Central PMCID: PMC3350514.
52. Eyal E, Lum G, Bahar I. The anisotropic network model web server at 2015 (ANM 2.0). Bioinformatics. 2015;31(9):1487–9. doi: 10.1093/bioinformatics/btu847 25568280; PubMed Central PMCID: PMC4410662.
53. Li H, Chang YY, Yang LW, Bahar I. iGNM 2.0: the Gaussian network model database for biomolecular structural dynamics. Nucleic Acids Res. 2016;44(D1):D415–22. doi: 10.1093/nar/gkv1236 26582920; PubMed Central PMCID: PMC4702874.
54. The PyMOL Molecular Graphics System, Version 1.8. Schrödinger, LLC.
55. Tobi D. Dynamics based clustering of globin family members. PLoS One. 2018;13(12):e0208465. doi: 10.1371/journal.pone.0208465 30513111; PubMed Central PMCID: PMC6279032.
56. Law SM. https://pymolwiki.org/index.php/Modevectors. Available from: https://pymolwiki.org/index.php/Modevectors.
57. Yang LW, Bahar I. Coupling between catalytic site and collective dynamics: a requirement for mechanochemical activity of enzymes. Structure. 2005;13(6):893–904. Epub 2005/06/09. S0969-2126(05)00167-X [pii] doi: 10.1016/j.str.2005.03.015 15939021; PubMed Central PMCID: PMC1489920.
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