References
- &NA. (2011). Manual of oculoplastic surgery, fourth edition. Plastic and Reconstructive Surgery, 128(3), 805–806. https://doi.org/https://doi.org/10.1097/prs.0b013e318225c826
- Agrahari, A. K., Muskan, M., George Priya Doss, C., Siva, R., & Zayed, H. (2018). Computational insights of K1444N substitution in GAP-related domain of NF1 gene associated with neurofibromatosis type 1 disease: A molecular modeling and dynamics approach. Metabolic Brain Disease, 33(5), 1443–1457. https://doi.org/https://doi.org/10.1007/s11011-018-0251-1
- Bendl, J., Stourac, J., Salanda, O., Pavelka, A., Wieben, E. D., Zendulka, J., Brezovsky, J., & Damborsky, J. (2014). PredictSNP: Robust and accurate consensus classifier for prediction of disease-related mutations. PLoS Computational Biology, 10(1), e1003440. https://doi.org/https://doi.org/10.1371/journal.pcbi.1003440
- Berman, H. M., Battistuz, T., Bhat, T. N., Bluhm, W. F., Bourne, P. E., Burkhardt, K., Feng, Z., Gilliland, G. L., Iype, L., Jain, S., Fagan, P., Marvin, J., Padilla, D., Ravichandran, V., Schneider, B., Thanki, N., Weissig, H., Westbrook, J. D., & Zardecki, C. (2002). The protein data bank. Acta Crystallographica. Section D, Biological Crystallography, 58(Pt 6 No 1), 899–907. https://doi.org/https://doi.org/10.1107/s0907444902003451
- Blokhuis, A. M., Groen, E. J. N., Koppers, M., Van Den Berg, L. H., & Pasterkamp, R. J. (2013). Protein aggregation in amyotrophic lateral sclerosis. Acta Neuropathologica, 125(6), 777–794. https://doi.org/https://doi.org/10.1007/s00401-013-1125-6
- Bosshard, H. R., Marti, D. N., & Jelesarov, I. (2004). Protein stabilization by salt bridges: Concepts, experimental approaches and clarification of some misunderstandings. Journal of Molecular Recognition: JMR, 17(1), 1–16. https://doi.org/https://doi.org/10.1002/jmr.657
- Bulka, B., desJardins, M., & Freeland, S. J. (2006). An interactive visualization tool to explore the biophysical properties of amino acids and their contribution to substitution matrices. BMC Bioinformatics, 7, 329–329. https://doi.org/https://doi.org/10.1186/1471-2105-7-329
- Butti, Z., & Patten, S. A. (2018). RNA dysregulation in amyotrophic lateral sclerosis. Frontiers in Genetics, 9, 712–718. https://doi.org/https://doi.org/10.3389/fgene.2018.00712
- Capriotti, E., Fariselli, P., & Casadio, R. (2005). I-Mutant2.0: Predicting stability changes upon mutation from the protein sequence or structure. Nucleic Acids Research, 33(Web Server), W306–310. https://doi.org/https://doi.org/10.1093/nar/gki375
- Case, D. A., Berryman, J. T., Betz, R. M., Cai, Q., Cerutti, D. S., Cheatham III, T. E., Darden, T. A., Duke, R. E., Gohlke, H., Goetz, A. W., Gusarov, S., Homeyer, N., Janowski, P., Kaus, J., Kolossváry, I., Kovalenko, A., Lee, T. S., LeGrand, S., Luchko, T., … Kollman, P. A. (2014). The Amber Molecular Dynamics Package. Amber, 14. http://ambermd.org/doc12/Amber14.pdf%0Ahttp://ambermd.org/
- Celniker, G., Nimrod, G., Ashkenazy, H., Glaser, F., Martz, E., Mayrose, I., Pupko, T., & Ben-Tal, N. (2013). ConSurf: Using evolutionary data to raise testable hypotheses about protein function. Israel Journal of Chemistry, 53(3-4), 199–206. https://doi.org/https://doi.org/10.1002/ijch.201200096
- Chen, C. W., Lin, J., & Chu, Y. W. (2013). iStable: Off-the-shelf predictor integration for predicting protein stability changes. BMC Bioinformatics, 14(S2), S5. https://doi.org/https://doi.org/10.1186/1471-2105-14-S2-S5
- Chen, C., Ding, X., Akram, N., Xue, S., & Luo, S. Z. (2019). Fused in sarcoma: Properties, self-assembly and correlation with neurodegenerative diseases. Molecules, 24(8), 1622–1617. https://doi.org/https://doi.org/10.3390/molecules24081622
- Choi, Y., & Chan, A. P. (2015). PROVEAN web server: A tool to predict the functional effect of amino acid substitutions and indels. Bioinformatics (Oxford, England), 31(16), 2745–2747. https://doi.org/https://doi.org/10.1093/bioinformatics/btv195
- Costantini, S., Colonna, G., & Facchiano, A. M. (2008). ESBRI: A web server for evaluating salt bridges in proteins. Bioinformation, 3(3), 137–138. https://doi.org/https://doi.org/10.6026/97320630003137
- Darden, T., York, D., & Pedersen, L. (1993). Particle mesh Ewald: An N·log(N) method for Ewald sums in large systems. The Journal of Chemical Physics, 98(12), 10089–10092. https://doi.org/https://doi.org/10.1063/1.464397
- Daura, X., Gademann, K., Jaun, B., Seebach, D., van Gunsteren, W. F., & Mark, A. E. (1999). Peptide folding: When simulation meets experiment. Angewandte Chemie International Edition, 38(1–2), 236–240. https://doi.org/https://doi.org/10.1002/(SICI)1521-3773(19990115)38:1/2<236::AID-ANIE236>3.0.CO;2-M
- Dehouck, Y., Kwasigroch, J. M., Rooman, M., & Gilis, D. (2013). BeAtMuSiC: Prediction of changes in protein-protein binding affinity on mutations. Nucleic Acids Research, 41(W1), W333–339. https://doi.org/https://doi.org/10.1093/nar/gkt450
- DeLano, W. L. (2002). Pymol: An open-source molecular graphics tool. CCP4 Newsletter on Protein Crystallography, 40, 82–92.
- Dill, K. A. (1990). Dominant forces in protein folding. Biochemistry, 29(31), 7133–7155. https://doi.org/https://doi.org/10.1021/bi00483a001
- Dormann, D., & Haass, C. (2011). TDP-43 and FUS: A nuclear affair. Trends in Neurosciences, 34(7), 339–348. https://doi.org/https://doi.org/10.1016/j.tins.2011.05.002
- Dormann, D., Rodde, R., Edbauer, D., Bentmann, E., Fischer, I., Hruscha, A., Than, M. E., MacKenzie, I. R. A., Capell, A., Schmid, B., Neumann, M., & Haass, C. (2010). ALS-associated fused in sarcoma (FUS) mutations disrupt transportin-mediated nuclear import. The EMBO Journal, 29(16), 2841–2857. https://doi.org/https://doi.org/10.1038/emboj.2010.143
- Drepper, C., Herrmann, T., Wessig, C., Beck, M., & Sendtner, M. (2011). C-terminal FUS/TLS mutations in familial and sporadic ALS in Germany. Neurobiology of Aging, 32(3), 548.e1–e4. https://doi.org/https://doi.org/10.1016/j.neurobiolaging.2009.11.017
- Fenwick, R. B., Orellana, L., Esteban-Martín, S., Orozco, M., & Salvatella, X. (2014). Correlated motions are a fundamental property of β-sheets. Nature Communications, 5(1), 1–9. https://doi.org/https://doi.org/10.1038/ncomms5070
- Gitler, A. D., & Shorter, J. (2011). RNA-binding proteins with prion-like domains in ALS and FTLD-U. Prion, 5(3), 179–187. https://doi.org/https://doi.org/10.4161/pri.5.3.17230
- Glaser, F., Pupko, T., Paz, I., Bell, R. E., Bechor-Shental, D., Martz, E., & Ben-Tal, N. (2003). ConSurf: Identification of functional regions in proteins by surface-mapping of phylogenetic information. Bioinformatics (Oxford, England), 19(1), 163–164. https://doi.org/https://doi.org/10.1093/bioinformatics/19.1.163
- Głowacki, E. D., Irimia-Vladu, M., Bauer, S., & Sariciftci, N. S. (2013). Hydrogen-bonds in molecular solids - from biological systems to organic electronics. Journal of Materials Chemistry. B, 1(31), 3742–3753. https://doi.org/https://doi.org/10.1039/c3tb20193g
- Guex, N., Peitsch, M. C., & Schwede, T. (2009). Automated comparative protein structure modeling with SWISS-MODEL and Swiss-PdbViewer: A historical perspective. Electrophoresis, 30(S1), S162–S173. https://doi.org/https://doi.org/10.1002/elps.200900140
- Humphrey, W., Dalke, A., & Schulten, K. (1996). Sartorius products. Journal of Molecular Graphics, 14(1), 33–38. https://doi.org/https://doi.org/10.1016/0263-7855(96)00018-5
- Jorgensen, W. L., Chandrasekhar, J., Madura, J. D., Impey, R. W., & Klein, M. L. (1983). Comparison of simple potential functions for simulating liquid water. The Journal of Chemical Physics, 79(2), 926–935. https://doi.org/https://doi.org/10.1063/1.445869
- Kabsch, W., & Sander, C. (1983). Dictionary of protein secondary structure: Pattern recognition of hydrogen-bonded and geometrical features. Biopolymers, 22(12), 2577–2637. https://doi.org/https://doi.org/10.1002/bip.360221211
- Kamaraj, B., Rajendran, V., Sethumadhavan, R., Kumar, C. V., & Purohit, R. (2015). Mutational analysis of FUS gene and its structural and functional role in amyotrophic lateral sclerosis 6. Journal of Biomolecular Structure & Dynamics, 33(4), 834–844. https://doi.org/https://doi.org/10.1080/07391102.2014.915762
- Kamelgarn, M., Chen, J., Kuang, L., Jin, H., Kasarskis, E. J., & Zhu, H. (2018). ALS mutations of FUS suppress protein translation and disrupt the regulation of nonsense-mediated decay. Proceedings of the National Academy of Sciences of the United States of America, 115(51), E11904–E11913. https://doi.org/https://doi.org/10.1073/pnas.1810413115
- Karplus, M., & Ichiye, T. (1996). Comment on a “Fluctuation and cross-correlation analysis of protein motions observed in nanosecond molecular dynamics simulations. Journal of Molecular Biology, 263(2), 120–503. https://doi.org/https://doi.org/10.1006/jmbi.1996.0562
- Kauzmann, W. (1959). Some Factors in the Interpretation of Protein Denaturation. Advances in Protein Chemistry, 14(C), 1–63. https://doi.org/https://doi.org/10.1016/S0065-3233(08)60608-7
- Kiernan, M. C., Vucic, S., Cheah, B. C., Turner, M. R., Eisen, A., Hardiman, O., Burrell, J. R., & Zoing, M. C. (2011). Amyotrophic lateral sclerosis. The Lancet, 377(9769), 942–955. https://doi.org/https://doi.org/10.1016/S0140-6736(10)61156-7
- Kuang, L., Kamelgarn, M., Arenas, A., Gal, J., Taylor, D., Gong, W., Brown, M., St Clair, D., Kasarskis, E. J., & Zhu, H. (2017). Clinical and experimental studies of a novel P525R FUS mutation in amyotrophic lateral sclerosis. Neurology: Genetics, 3(4), e172. https://doi.org/https://doi.org/10.1212/NXG.0000000000000172
- Kumar, C. V., Swetha, R. G., Anbarasu, A., & Ramaiah, S. (2014). Computational analysis reveals the association of threonine 118 methionine mutation in PMP22 resulting in CMT-1A. Advances in Bioinformatics, 2014, 502618. https://doi.org/https://doi.org/10.1155/2014/502618
- Laimer, J., Hofer, H., Fritz, M., Wegenkittl, S., & Lackner, P. (2015). MAESTRO - multi agent stability prediction upon point mutations. BMC Bioinformatics, 16(1), 1–13. https://doi.org/https://doi.org/10.1186/s12859-015-0548-6
- Li, Y. R., King, O. D., Shorter, J., & Gitler, A. D. (2013). Stress granules as crucibles of ALS pathogenesis. The Journal of Cell Biology, 201(3), 361–372. https://doi.org/https://doi.org/10.1083/jcb.201302044
- Lindström, M., & Liu, B. (2018). Yeast as a model to unravel mechanisms behind FUS toxicity in amyotrophic lateral sclerosis. Frontiers in Molecular Neuroscience, 11(June), 218–210. https://doi.org/https://doi.org/10.3389/fnmol.2018.00218
- Loncharich, R. J., Brooks, B. R., & Pastor, R. W. (1992). Langevin dynamics of peptides: The frictional dependence of isomerization rates of N-acetylalanyl-N'-methylamide. Biopolymers, 32(5), 523–535. https://doi.org/https://doi.org/10.1002/bip.360320508
- López-Ferrando, V., Gazzo, A., De La Cruz, X., Orozco, M., & Gelpí, J. L. (2017). PMut: A web-based tool for the annotation of pathological variants on proteins, 2017 update. Nucleic Acids Research, 45(W1), W222–W228. https://doi.org/https://doi.org/10.1093/nar/gkx313
- Mackenzie, I. R. A., Ansorge, O., Strong, M., Bilbao, J., Zinman, L., Ang, L. C., Baker, M., Stewart, H., Eisen, A., Rademakers, R., & Neumann, M. (2011). Pathological heterogeneity in amyotrophic lateral sclerosis with FUS mutations: Two distinct patterns correlating with disease severity and mutation. Acta Neuropathologica, 122(1), 87–98. https://doi.org/https://doi.org/10.1007/s00401-011-0838-7
- McAlary, L., Plotkin, S. S., Yerbury, J. J., & Cashman, N. R. (2019). Prion-like propagation of protein misfolding and aggregation in amyotrophic lateral sclerosis. Frontiers in Molecular Neuroscience, 12(November), 1–21. https://doi.org/https://doi.org/10.3389/fnmol.2019.00262
- Naganska, E., & Matyja, E. (2011). Amyotrophic lateral sclerosis - Looking for pathogenesis and effective therapy. Folia Neuropathologica, 49(1), 1–13.
- Nakaya, T., & Maragkakis, M. (2018). Amyotrophic Lateral Sclerosis associated FUS mutation shortens mitochondria and induces neurotoxicity. Scientific Reports, 8(1), 1–15. https://doi.org/https://doi.org/10.1038/s41598-018-33964-0
- Ni, D., Song, K., Zhang, J., & Lu, S. (2017). Molecular dynamics simulations and dynamic network analysis reveal the allosteric unbinding of monobody to H-Ras triggered by R135K mutation. International Journal of Molecular Sciences, 18(11), 2249. https://doi.org/https://doi.org/10.3390/ijms18112249
- Niroula, A., Urolagin, S., & Vihinen, M. (2015). PON-P2: Prediction method for fast and reliable identification of harmful variants. PLoS One, 10(2), e0117380. https://doi.org/https://doi.org/10.1371/journal.pone.0117380
- Niu, C., Zhang, J., Gao, F., Yang, L., Jia, M., Zhu, H., & Gong, W. (2012). FUS-NLS/Transportin 1 complex structure provides insights into the nuclear targeting mechanism of FUS and the implications in ALS. PLoS One, 7(10), e47056. https://doi.org/https://doi.org/10.1371/journal.pone.0047056
- Nolan, M., Talbot, K., & Ansorge, O. (2016). Pathogenesis of FUS-associated ALS and FTD: Insights from rodent models. Acta Neuropathologica Communications, 4(1), 99. https://doi.org/https://doi.org/10.1186/s40478-016-0358-8
- Patel, A., Lee, H. O., Jawerth, L., Maharana, S., Jahnel, M., Hein, M. Y., Stoynov, S., Mahamid, J., Saha, S., Franzmann, T. M., Pozniakovski, A., Poser, I., Maghelli, N., Royer, L. A., Weigert, M., Myers, E. W., Grill, S., Drechsel, D., Hyman, A. A., & Alberti, S. (2015). A liquid-to-solid phase transition of the ALS Protein FUS accelerated by disease mutation. Cell, 162(5), 1066–1077. https://doi.org/https://doi.org/10.1016/j.cell.2015.07.047
- Peters, O. M., Ghasemi, M., & Brown, R. H. (2015). Emerging mechanisms of molecular pathology in ALS. The Journal of Clinical Investigation, 125(5), 1767–1779. https://doi.org/https://doi.org/10.1172/JCI71601
- Piovesan, D., Minervini, G., & Tosatto, S. C. E. (2016). The RING 2.0 web server for high quality residue interaction networks. Nucleic Acids Research, 44(W1), W367–W374. https://doi.org/https://doi.org/10.1093/nar/gkw315
- Pires, D. E. V., Ascher, D. B., & Blundell, T. L. (2014). DUET: A server for predicting effects of mutations on protein stability using an integrated computational approach. Nucleic Acids Research, 42(W1), W314–319. https://doi.org/https://doi.org/10.1093/nar/gku411
- Prakash, A., Kumar, V., Banerjee, A., Lynn, A. M., & Prasad, R. (2020). Structural heterogeneity in RNA recognition motif 2 (RRM2) of TAR DNA-binding protein 43 (TDP-43): Clue to amyotrophic lateral sclerosis. Journal of Biomolecular Structure and Dynamics, 1–11. https://doi.org/https://doi.org/10.1080/07391102.2020.1714481
- Ren, J., Wen, L., Gao, X., Jin, C., Xue, Y., & Yao, X. (2009). DOG 1.0: Illustrator of protein domain structures. Cell Research, 19(2), 271–273. https://doi.org/https://doi.org/10.1038/cr.2009.6
- Ribeiro, A. A. S. T., & De Alencastro, R. B. (2013). Mixed Monte Carlo/Molecular Dynamics simulations of the prion protein. Journal of Molecular Graphics & Modelling, 42, 1–6. https://doi.org/https://doi.org/10.1016/j.jmgm.2013.02.007
- Rodrigues, C. H. M., Myung, Y., Pires, D. E. V., & Ascher, D. B. (2019). mCSM-PPI2: Predicting the effects of mutations on protein-protein interactions. Nucleic Acids Research, 47(W1), W338–W344. https://doi.org/https://doi.org/10.1093/nar/gkz383
- Rodrigues, C. H. M., Pires, D. E. V., & Ascher, D. B. (2018). DynaMut: Predicting the impact of mutations on protein conformation, flexibility and stability. Nucleic Acids Research, 46(W1), W350–W355. https://doi.org/https://doi.org/10.1093/nar/gky300
- Rogers, M. F., Shihab, H. A., Mort, M., Cooper, D. N., Gaunt, T. R., & Campbell, C. (2018). FATHMM-XF: Accurate prediction of pathogenic point mutations via extended features. Bioinformatics (Oxford, England), 34(3), 511–513. https://doi.org/https://doi.org/10.1093/bioinformatics/btx536
- Ryckaert, J. P., Ciccotti, G., & Berendsen, H. J. C. (1977). Numerical integration of the Cartesian equations of motion of a system with constraints: Molecular dynamics of n-alkanes. Journal of Computational Physics, 23(3), 327–341. https://doi.org/https://doi.org/10.1016/0021-9991(77)90098-5
- Seneverthina, S., Rajeev, A. S., & Kader, D. F. (2011). Cement reactions in hemiarthroplasty of hip in elderly patients with fracture neck of femurs. Injury Extra, 42(9), 98–99. https://doi.org/https://doi.org/10.1016/j.injury.2011.06.210
- Shang, Y., & Huang, E. J. (2016). Mechanisms of FUS mutations in familial amyotrophic lateral sclerosis. Brain Research, 1647, 65–78. https://doi.org/https://doi.org/10.1016/j.brainres.2016.03.036
- Somavarapu, A. K., & Kepp, K. P. (2016). Loss of stability and hydrophobicity of presenilin 1 mutations causing Alzheimer's disease. Journal of Neurochemistry, 137(1), 101–111. https://doi.org/https://doi.org/10.1111/jnc.13535
- Srinivasan, E., & Rajasekaran, R. (2017). Computational investigation of the human SOD1 mutant, Cys146Arg, that directs familial amyotrophic lateral sclerosis. Molecular Biosystems, 13(8), 1495–1503. https://doi.org/https://doi.org/10.1039/c7mb00106a
- Swetha, R. G., Ramaiah, S., & Anbarasu, A. (2017). R521C and R521H mutations in FUS result in weak binding with Karyopherinβ2 leading to Amyotrophic lateral sclerosis: A molecular docking and dynamics study. Journal of Biomolecular Structure & Dynamics, 35(10), 2169–2185. https://doi.org/https://doi.org/10.1080/07391102.2016.1209130
- Taylor, J. P., Brown, R. H., & Cleveland, D. W. (2016). Decoding ALS: From genes to mechanism. Nature, 539(7628), 197–206. https://doi.org/https://doi.org/10.1038/nature20413
- Thirumal Kumar, D., Jerushah Emerald, L., George Priya Doss, C., Sneha, P., Siva, R., Charles Emmanuel Jebaraj, W., & Zayed, H. (2018). Computational approach to unravel the impact of missense mutations of proteins (D2HGDH and IDH2) causing D-2-hydroxyglutaric aciduria 2. Metabolic Brain Disease, 33(5), 1699–1710. https://doi.org/https://doi.org/10.1007/s11011-018-0278-3
- Ticozzi, N., Silani, V., Leclerc, A. L., Keagle, P., Gellera, C., Ratti, A., Taroni, F., Kwiatkowski, T. J., McKenna-Yasek, D. M., Sapp, P. C., Brown, R. H., & Landers, J. E. (2009). Analysis of FUS gene mutation in familial amyotrophic lateral sclerosis within an Italian cohort. Neurology, 73(15), 1180–1185. https://doi.org/https://doi.org/10.1212/WNL.0b013e3181bbff05
- Tina, K. G., Bhadra, R., & Srinivasan, N. (2007). PIC: Protein Interactions Calculator. Nucleic Acids Research, 35(Web Server), W473–476. https://doi.org/https://doi.org/10.1093/nar/gkm423
- Tsubota, A., Ichijo, H., & Homma, K. (2016). Mislocalization, aggregation formation and defect in proteolysis in ALS. AIMS Molecular Science, 3(2), 246–268. https://doi.org/https://doi.org/10.3934/molsci.2016.2.246
- Verma, D., Jacobs, D. J., & Livesay, D. R. (2012). Changes in lysozyme flexibility upon mutation are frequent, large and long-ranged. PLoS Computational Biology, 8(3), e1002409. https://doi.org/https://doi.org/10.1371/journal.pcbi.1002409
- Walsh, I., Minervini, G., Corazza, A., Esposito, G., Tosatto, S. C. E., & Fogolari, F. (2012). Bluues server: Electrostatic properties of wild-type and mutated protein structures. Bioinformatics (Oxford, England), 28(16), 2189–2190. https://doi.org/https://doi.org/10.1093/bioinformatics/bts343
- Wang, Q., Johnson, J. L., Agar, N. Y. R., & Agar, J. N. (2008). Protein aggregation and protein instability govern familial amyotrophic lateral sclerosis patient survival. PLoS Biology, 6(7), e170. https://doi.org/https://doi.org/10.1371/journal.pbio.0060170
- Zhang, J., Liu, S., Shang, Z., Shi, L., & Yun, J. (2012). Analysis of the relationship between end-to-end distance and activity of single-chain antibody against colorectal carcinoma. Theoretical Biology & Medical Modelling, 9(1), 38–11. https://doi.org/https://doi.org/10.1186/1742-4682-9-38
- Zhao, M., Kim, J. R., Bruggen, R., & van Park, J. (2018). RNA-binding proteins in amyotrophic lateral sclerosis. Molecules and Cells, 41(9), 818–829. https://doi.org/https://doi.org/10.14348/molcells.2018.0243