The impacts of the mitochondrial myopathy-associated G58R mutation on the dynamic structural properties of CHCHD10

References

• Ahmed, S. T., Craven, L., Russell, O. M., Turnbull, D. M., & Vincent, A. E. (2018). Diagnosis and treatment of mitochondrial myopathies. Neurotherapeutics : The Journal of the American Society for Experimental NeuroTherapeutics, 15(4), 943–953. https://doi.org/10.1007/s13311-018-00674-4
   PubMed Web of Science ®Google Scholar
• Ajroud-Driss, S., Fecto, F., Ajroud, K., Lalani, I., Calvo, S. E., Mootha, V. K., Deng, H.-X., Siddique, N., Tahmoush, A. J., Heiman-Patterson, T. D., & Siddique, T. (2015). Mutation in the novel nuclear-encoded mitochondrial protein CHCHD10 in a family with autosomal dominant mitochondrial myopathy. Neurogenetics, 16(1), 1–9. https://doi.org/10.1007/s10048-014-0421-1
   PubMed Web of Science ®Google Scholar
• Akbayrak, I. Y., Caglayan, S. I., Ozcan, Z., Uversky, V. N., & Coskuner-Weber, O. (2020). Current challenges and limitations in the studies of intrinsically disordered proteins in neurodegenerative diseases by computer simulations. Current Alzheimer Research, 17(9), 805–818. https://doi.org/10.2174/1567205017666201109094908
   PubMed Web of Science ®Google Scholar
• Alici, H., Uversky, V. N., Kang, D. E., Woo, J. A., & Coskuner-Weber, O. (2022). Structures of the wild-type and S59L mutant CHCHD10 proteins important in amyotrophic lateral sclerosis-frontotemporal dementia. ACS Chemical Neuroscience, 13(8), 1273–1280. https://doi.org/10.1021/acschemneuro.2c00011
   PubMed Web of Science ®Google Scholar
• Allison, T. C., Coskuner, O., & Gonzalez, C. A. (Eds.). (2011). Metallic systems: A quantum chemist’s perspective. CRC Press. https://doi.org/10.1201/b10835
   Google Scholar
• Beecher, G., Fleming, M. D., & Liewluck, T. (2022). Hereditary myopathies associated with hematological abnormalities. Muscle & Nerve, 65(4), 374–390. https://doi.org/10.1002/mus.27474
   PubMed Web of Science ®Google Scholar
• Berendsen, H. J. C., van der Spoel, D., & van Drunen, R. (1995). GROMACS: A message-passing parallel molecular dynamics implementation. Computer Physics Communications, 91(1-3), 43–56. https://doi.org/10.1016/0010-4655(95)00042-E
   Web of Science ®Google Scholar
• Bhatti, J. S., Bhatti, G. K., & Reddy, P. H. (2017). Mitochondrial dysfunction and oxidative stress in metabolic disorders—A step towards mitochondria based therapeutic strategies. Biochimica et Biophysica Acta. Molecular Basis of Disease, 1863(5), 1066–1077. https://doi.org/10.1016/j.bbadis.2016.11.010
   PubMed Web of Science ®Google Scholar
• Burstein, S. R., Valsecchi, F., Kawamata, H., Bourens, M., Zeng, R., Zuberi, A., Milner, T. A., Cloonan, S. M., Lutz, C., Barrientos, A., & Manfredi, G. (2018). In vitro and in vivo studies of the ALS-FTLD protein CHCHD10 reveal novel mitochondrial topology and protein interactions. Human Molecular Genetics, 27(1), 160–177. https://doi.org/10.1093/hmg/ddx397
   PubMed Web of Science ®Google Scholar
• 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/10.1063/1.464397
   Web of Science ®Google Scholar
• DiMauro, S. (2006). Mitochondrial myopathies. Current Opinion in Rheumatology, 18(6), 636–641. https://doi.org/10.1097/01.bor.0000245729.17759.f2
   PubMed Web of Science ®Google Scholar
• Dosztányi, Z., Csizmok, V., Tompa, P., & Simon, I. (2005). IUPred: Web server for the prediction of intrinsically unstructured regions of proteins based on estimated energy content. Bioinformatics (Oxford, England), 21(16), 3433–3434. https://doi.org/10.1093/bioinformatics/bti541
   PubMed Web of Science ®Google Scholar
• Dosztányi, Z., Mészáros, B., & Simon, I. (2009). ANCHOR: Web server for predicting protein binding regions in disordered proteins. Bioinformatics (Oxford, England), 25(20), 2745–2746. https://doi.org/10.1093/bioinformatics/btp518
   PubMed Web of Science ®Google Scholar
• El-Hattab, A. W., & Scaglia, F. (2013). Mitochondrial DNA depletion syndromes: Review and updates of genetic basis, manifestations, and therapeutic options. Neurotherapeutics : The Journal of the American Society for Experimental NeuroTherapeutics, 10(2), 186–198. https://doi.org/10.1007/s13311-013-0177-6
   PubMed Web of Science ®Google Scholar
• Erdős, G., & Dosztányi, Z. (2020). Analyzing protein disorder with IUPred2A. Current Protocols in Bioinformatics, 70(1), e99. https://doi.org/10.1002/cpbi.99
   PubMedGoogle Scholar
• Evans, D. J., & Holian, B. L. (1985). The Nose–Hoover thermostat. The Journal of Chemical Physics, 83(8), 4069–4074. https://doi.org/10.1063/1.449071
   Web of Science ®Google Scholar
• He, Z., Ning, N., Zhou, Q., Khoshnam, S. E., & Farzaneh, M. (2020). Mitochondria as a therapeutic target for ischemic stroke. Free Radical Biology & Medicine, 146, 45–58. https://doi.org/10.1016/j.freeradbiomed.2019.11.005
   PubMed Web of Science ®Google Scholar
• Hess, B. (2008). P-LINCS: A parallel linear constraint solver for molecular simulation. Journal of Chemical Theory and Computation, 4(1), 116–122. https://doi.org/10.1021/ct700200b
   PubMed Web of Science ®Google Scholar
• Huang, J., Rauscher, S., Nawrocki, G., Ran, T., Feig, M., de Groot, B. L., Grubmüller, H., & MacKerell, A. D. (2017). CHARMM36m: An improved force field for folded and intrinsically disordered proteins. Nature Methods, 14(1), 71–73. https://doi.org/10.1038/nmeth.4067
   PubMed Web of Science ®Google Scholar
• Lim, Y. Y., Miskon, A., & Zaidi, A. M. A. (2022). Structural strength analyses for low brass filler biomaterial with anti-trauma effects in articular cartilage scaffold design. Materials, 15(13), 4446. https://doi.org/10.3390/ma15134446
   PubMed Web of Science ®Google Scholar
• Lim, Y. Y., Zaidi, A. M. A., & Miskon, A. (2023). Combining copper and zinc into a biosensor for anti-chemoresistance and achieving osteosarcoma therapeutic efficacy. Molecules, 28(7), 2920. https://doi.org/10.3390/molecules28072920
   PubMed Web of Science ®Google Scholar
• Lu, J.-Q., & Tarnopolsky, M. A. (2021). Mitochondrial neuropathy and neurogenic features in mitochondrial myopathy. Mitochondrion, 56, 52–61. https://doi.org/10.1016/j.mito.2020.11.005
   PubMed Web of Science ®Google Scholar
• Macdonald, R., Barnes, K., Hastings, C., & Mortiboys, H. (2018). Mitochondrial abnormalities in Parkinson’s disease and Alzheimer’s disease: Can mitochondria be targeted therapeutically? Biochemical Society Transactions, 46(4), 891–909. https://doi.org/10.1042/BST20170501
   PubMedGoogle Scholar
• Mannella, C. A. (2020). Consequences of folding the mitochondrial inner membrane. Frontiers in Physiology, 11, 536. https://doi.org/10.3389/fphys.2020.00536
   PubMed Web of Science ®Google Scholar
• Mészáros, B., Erdos, G., & Dosztányi, Z. (2018). IUPred2A: Context-dependent prediction of protein disorder as a function of redox state and protein binding. Nucleic Acids Research, 46(W1), W329–W337. https://doi.org/10.1093/nar/gky384
   PubMed Web of Science ®Google Scholar
• Parrinello, M., & Rahman, A. (1981). Polymorphic transitions in single crystals: A new molecular dynamics method. Journal of Applied Physics, 52(12), 7182–7190. https://doi.org/10.1063/1.328693
   Web of Science ®Google Scholar
• Peng, K., Radivojac, P., Vucetic, S., Dunker, A. K., & Obradovic, Z. (2006). Length-dependent prediction of protein intrinsic disorder. BMC Bioinformatics, 7(1), 208. https://doi.org/10.1186/1471-2105-7-208
   PubMed Web of Science ®Google Scholar
• Peng, K., Vucetic, S., Radivojac, P., Brown, C. J., Dunker, A. K., & Obradovic, Z. (2005). Optimizing long intrinsic disorder predictors with protein evolutionary information. Journal of Bioinformatics and Computational Biology, 3(1), 35–60. https://doi.org/10.1142/s0219720005000886
   PubMedGoogle Scholar
• Radelfahr, F., & Klopstock, T. (2019). [Mitochondrial diseases]. Der Nervenarzt, 90(2), 121–130. https://doi.org/10.1007/s00115-018-0666-2
   PubMed Web of Science ®Google Scholar
• Romero, P., Obradovic, Z., Li, X., Garner, E. C., Brown, C. J., & Dunker, A. K. (2001). Sequence complexity of disordered protein. Proteins: Structure, Function, and Genetics, 42(1), 38–48. https://doi.org/10.1002/1097-0134(20010101)42:1<38::aid-prot50>3.0.co;2-3
   PubMed Web of Science ®Google Scholar
• Shammas, M. K., Huang, X., Wu, B. P., Fessler, E., Song, I. Y., Randolph, N. P., Li, Y., Bleck, C. K., Springer, D. A., Fratter, C., Barbosa, I. A., Powers, A. F., Quirós, P. M., Lopez-Otin, C., Jae, L. T., Poulton, J., & Narendra, D. P. (2022). OMA1 mediates local and global stress responses against protein misfolding in CHCHD10 mitochondrial myopathy. Journal of Clinical Investigation, 132(14), e157504. https://doi.org/10.1172/JCI157504
   PubMed Web of Science ®Google Scholar
• Tsang, S. H., Aycinena, A. R. P., & Sharma, T. (2018). Mitochondrial disorder: Kearns-Sayre Syndrome. Advances in Experimental Medicine and Biology, 1085, 161–162. https://doi.org/10.1007/978-3-319-95046-4_30
   PubMed Web of Science ®Google Scholar
• Vincent, A. E., Ng, Y. S., White, K., Davey, T., Mannella, C., Falkous, G., Feeney, C., Schaefer, A. M., McFarland, R., Gorman, G. S., Taylor, R. W., Turnbull, D. M., & Picard, M. (2016). The spectrum of mitochondrial ultrastructural defects in mitochondrial myopathy. Scientific Reports, 6, 30610. https://doi.org/10.1038/srep30610
   PubMed Web of Science ®Google Scholar
• Xia, W., Qiu, J., Peng, Y., Snyder, M. M., Gu, L., Huang, K., Luo, N., Yue, F., & Kuang, S. (2022). Chchd10 is dispensable for myogenesis but critical for adipose browning. Cell Regeneration, 11(1), 14. https://doi.org/10.1186/s13619-022-00111-0
   PubMedGoogle Scholar
• Xue, B., Dunbrack, R. L., Williams, R. W., Dunker, A. K., & Uversky, V. N. (2010). PONDR-FIT: A meta-predictor of intrinsically disordered amino acids. Biochimica et Biophysica Acta, 1804(4), 996–1010. https://doi.org/10.1016/j.bbapap.2010.01.011
   PubMed Web of Science ®Google Scholar
• Yang, J., & Zhang, Y. (2015). I-TASSER server: New development for protein structure and function predictions. Nucleic Acids Research, 43(W1), W174–W181. https://doi.org/10.1093/nar/gkv342
   PubMed Web of Science ®Google Scholar
• Zheng, W., Zhang, C., Li, Y., Pearce, R., Bell, E. W., & Zhang, Y. (2021). Folding non-homologous proteins by coupling deep-learning contact maps with I-TASSER assembly simulations. Cell Reports Methods, 1(3), 100014. https://doi.org/10.1016/j.crmeth.2021.100014
   PubMedGoogle Scholar
• Zhou, Z.-D., Saw, W.-T., & Tan, E.-K. (2017). Mitochondrial CHCHD-containing proteins: Physiologic functions and link with neurodegenerative diseases. Molecular Neurobiology, 54(7), 5534–5546. https://doi.org/10.1007/s12035-016-0099-5
   PubMed Web of Science ®Google Scholar
• Zhou, X., Zheng, W., Li, Y., Pearce, R., Zhang, C., Bell, E. W., Zhang, G., & Zhang, Y. (2022). I-TASSER-MTD: A deep-learning-based platform for multi-domain protein structure and function prediction. Nature Protocols, 17(10), 2326–2353. https://doi.org/10.1038/s41596-022-00728-0
   PubMed Web of Science ®Google Scholar