In silico analysis of substitution mutations in the β-globin gene in Turkish population of β-thalassemia

References

• Abdul Azeez, S., & Borgio, J. F. (2016). In-silico computing of the most deleterious nsSNPs in HBA1 gene. PloS One, 11(1), e0147702. https://doi.org/10.1371/journal.pone.0147702
   PubMed Web of Science ®Google Scholar
• Ali, S., Hassan, M., Islam, A., & Ahmad, F. (2014). A review of methods available to estimate solvent-accessible surface areas of soluble proteins in the folded and unfolded states. Current Protein & Peptide Science, 15(5), 456–476. https://doi.org/10.2174/1389203715666140327114232
   PubMed Web of Science ®Google Scholar
• Ali, A., Soman, S. S., & Vijayan, R. (2022). Dynamics of camel and human hemoglobin revealed by molecular simulations. Scientific Reports, 12(1), 122. https://doi.org/10.1038/s41598-021-04112-y
   PubMedGoogle Scholar
• Benkert, P., Biasini, M., & Schwede, T. (2011). Toward the estimation of the absolute quality of individual protein structure models. Bioinformatics (Oxford, England), 27(3), 343–350. https://doi.org/10.1093/bioinformatics/btq662
   PubMed Web of Science ®Google Scholar
• Bogatyreva, N. S., & Ivankov, D. N. (2008). The relationship between the solvent-accessible surface area of a protein and the number of native contacts in its structure. Molecular Biology, 42(6), 932–938. https://doi.org/10.1134/S0026893308060150
   Web of Science ®Google Scholar
• Bordoli, L., Kiefer, F., Arnold, K., Benkert, P., Battey, J., & Schwede, T. (2009). Protein structure homology modeling using SWISS-MODEL workspace. Nature Protocols, 4(1), 1–13. https://doi.org/10.1038/nprot.2008.197
   PubMed Web of Science ®Google Scholar
• Canatan, D., Kose, M. R., Ustundag, M., Haznedaroglu, D., & Ozbas, S. (2006). Hemoglobinopathy control program in Turkey. Community Genetics, 9(2), 124–126. https://doi.org/10.1159/000091493
   PubMedGoogle Scholar
• Chatzou, M., Magis, C., Chang, J. M., Kemena, C., Bussotti, G., Erb, I., & Notredame, C. (2016). Multiple sequence alignment modeling: Methods and applications. Briefings in Bioinformatics, 17(6), 1009–1023. https://doi.org/10.1093/BIB/BBV099
   PubMed Web of Science ®Google Scholar
• Chen, W.-R., Yu, Y., Zulfajri, M., Lin, P.-C., & Wang, C. C. (2017). Phthalide derivatives from Angelica sinensis decrease hemoglobin oxygen affinity: A new allosteric-modulating mechanism and potential use as 2,3-BPG functional substitutes. Scientific Reports, 7(1), 5504. https://doi.org/10.1038/s41598-017-04554-3
   PubMedGoogle Scholar
• Colovos, C., Yeates, T. O. (1993). Verification of protein structures: patterns of nonbonded atomic interactions. Protein science, 2(9), 1511–1519.
   Google Scholar
• Damm, K. L., & Carlson, H. A. (2006). Gaussian-weighted RMSD superposition of proteins: a structural comparison for flexible proteins and predicted protein structures. Biophysical Journal, 90(12), 4558–4573. https://doi.org/10.1529/biophysj.105.066654
   PubMed Web of Science ®Google Scholar
• David, C. C., & Jacobs, D. J. (2014). Principal component analysis: A method for determining the essential dynamics of proteins. Methods and protocols, 1084, 193-226. https://doi.org/10.1007/978-1-62703-658-0_11
   Google Scholar
• David, A., & Sternberg, M. J. E. (2015). The contribution of missense mutations in core and rim residues of protein–protein interfaces to human disease. Journal of Molecular Biology, 427(17), 2886–2898. https://doi.org/10.1016/j.jmb.2015.07.004
   PubMed Web of Science ®Google Scholar
• Fuglebakk, E., Echave, J., & Reuter, N. (2012). Measuring and comparing structural fluctuation patterns in large protein datasets. Bioinformatics (Oxford, England), 28(19), 2431–2440. https://doi.org/10.1093/bioinformatics/bts445
   PubMed Web of Science ®Google Scholar
• Galzitskaya, O. V., Bogatyreva, N. S., & Ivankov, D. N. (2008). Compactness determines protein folding type. Journal of Bioinformatics and Computational Biology, 6(4), 667–680. https://doi.org/10.1142/S0219720008003618
   PubMedGoogle Scholar
• Giardine, B., Borg, J., Viennas, E., Pavlidis, C., Moradkhani, K., Joly, P., Bartsakoulia, M., Riemer, C., Miller, W., Tzimas, G., Wajcman, H., Hardison, R. C., & Patrinos, G. P. (2014). Updates of the HbVar database of human hemoglobin variants and thalassemia mutations. Nucleic Acids Research, 42(Database issue), D1063–D1069. https://doi.org/10.1093/nar/gkt911
   PubMed Web of Science ®Google Scholar
• Gunes, A. K., & Gozden, H. E. (2021). The spectrum of beta-thalassemia mutations in Syrian refugees and Turkish citizens. Cureus, 13(6), e15434. https://doi.org/10.7759/cureus.15434
   PubMed Web of Science ®Google Scholar
• Hollingsworth, S. A., & Dror, R. O. (2018). Molecular dynamics simulation for all. Neuron, 99(6), 1129–1143. https://doi.org/10.1016/j.neuron.2018.08.011
   PubMed Web of Science ®Google Scholar
• Hoyer, J. D., Wendt, P. C., Hogan, W. J., & Oliveira, J. L. (2011). Hb Nebraska [β86(F2)Ala→Ile (HBB:c.259G > A;260C > T)]: A unique high oxygen affinity hemoglobin variant with a double nucleotide substitution within the same codon. Hemoglobin, 35(1), 22–27. https://doi.org/10.3109/03630269.2011.552380
   PubMed Web of Science ®Google Scholar
• Khan, M. T., & Malik, S. I. (2020). Structural dynamics behind variants in pyrazinamidase and pyrazinamide resistance. Journal of Biomolecular Structure & Dynamics, 38(10), 3003–3017. https://doi.org/10.1080/07391102.2019.1650113
   PubMed Web of Science ®Google Scholar
• Lobanov, M. Y., Bogatyreva, N. S., & Galzitskaya, O. V. (2008). Radius of gyration as an indicator of protein structure compactness. Molecular Biology, 42(4), 623–628. https://doi.org/10.1134/S0026893308040195
   Web of Science ®Google Scholar
• López-Llano, J., Campos, L. A., Sancho, J., & Sancho, J. (2006). α-helix stabilization by alanine relative to glycine: Roles of polar and apolar solvent exposures and of backbone entropy. Proteins, 64(3), 769–778. https://doi.org/10.1002/prot.21041
   PubMed Web of Science ®Google Scholar
• Moosavi-Movahedi, A. A., Mousavy, S. J., Divsalar, A., Babaahmadi, A., Karimian, K., Shafiee, A., Kamarie, M., Poursasan, N., Farzami, B., Riazi, G. H., Hakimelahi, G. H., Tsai, F.-Y., Ahmad, F., Amani, M., & Saboury, A. A. (2009). The effects of deferiprone and deferasirox on the structure and function of β-thalassemia hemoglobin. Journal of Biomolecular Structure & Dynamics, 27(3), 319–339. https://doi.org/10.1080/07391102.2009.10507319
   PubMed Web of Science ®Google Scholar
• Oliveira, J. L., Coon, L. M., Frederick, L. A., Hein, M., Swanson, K. C., Savedra, M. E., Porter, T. R., Patnaik, M. M., Tefferi, A., Pardanani, A., Grebe, S. K., Viswanatha, D. S., & Hoyer, J. D. (2018). Genotype-phenotype correlation of hereditary erythrocytosis mutations, a single center experience. American Journal of Hematology, 93(8), 1029–1041. https://doi.org/10.1002/ajh.25150
   Web of Science ®Google Scholar
• Orgogozo, V., Morizot, B., & Martin, A. (2015). The differential view of genotype-phenotype relationships. Frontiers in Genetics, 6, 179. https://doi.org/10.3389/fgene.2015.00179
   PubMed Web of Science ®Google Scholar
• Origa, R. (2017). β-Thalassemia. Genetics in Medicine, 19(6), 609–619. https://doi.org/10.1038/gim.2016.173
   PubMed Web of Science ®Google Scholar
• Pace, C. N., Fu, H., Lee Fryar, K., Landua, J., Trevino, S. R., Schell, D., Thurlkill, R. L., Imura, S., Scholtz, J. M., Gajiwala, K., Sevcik, J., Urbanikova, L., Myers, J. K., Takano, K., Hebert, E. J., Shirley, B. A., & Grimsley, G. R. (2014). Contribution of hydrogen bonds to protein stability. Protein Science: A Publication of the Protein Society, 23(5), 652–661. https://doi.org/10.1002/pro.2449
   PubMed Web of Science ®Google Scholar
• Petukh, M., Kucukkal, T. G., & Alexov, E. (2015). On human disease-causing amino acid variants: Statistical study of sequence and structural patterns. Human Mutation, 36(5), 524–534. https://doi.org/10.1002/humu.22770
   PubMed Web of Science ®Google Scholar
• Ronda, L., Bruno, S., & Bettati, S. (2013). Tertiary and quaternary effects in the allosteric regulation of animal hemoglobins. Biochimica et Biophysica Acta, 1834(9), 1860–1872. https://doi.org/10.1016/j.bbapap.2013.03.013
   PubMed Web of Science ®Google Scholar
• Sherry, S. T., Ward, M. H., Kholodov, M., Baker, J., Phan, L., Smigielski, E. M., & Sirotkin, K. (2001). dbSNP: The NCBI database of genetic variation. Nucleic Acids Research, 29(1), 308–311. https://doi.org/10.1093/nar/29.1.308
   PubMed Web of Science ®Google Scholar
• Taher, A. T., Weatherall, D. J., & Cappellini, M. D. (2018). Thalassaemia. The Lancet, 391(10116), 155–167. https://doi.org/10.1016/S0140-6736(17)31822-6
   PubMed Web of Science ®Google Scholar
• Thein, S. L. (2013). The molecular basis of β-thalassemia. Cold Spring Harbor Perspectives in Medicine, 3(5), a011700. https://doi.org/10.1101/cshperspect.a011700
   PubMed Web of Science ®Google Scholar
• van der Spoel, D., Lindahl, E., Hess, B., Groenhof, G., Mark, A. E., & Berendsen, H. J. C. (2005). GROMACS: Fast, flexible, and free. Journal of Computational Chemistry, 26(16), 1701–1718. https://doi.org/10.1002/jcc.20291
   PubMed Web of Science ®Google Scholar
• Weatherall, D. (2008). Hemoglobinopathies Worldwide: Present and future. Current Molecular Medicine, 8(7), 592–599. https://doi.org/10.2174/156652408786241375
   PubMed Web of Science ®Google Scholar
• Williams, C. J., Headd, J. J., Moriarty, N. W., Prisant, M. G., Videau, L. L., Deis, L. N., Verma, V., Keedy, D. A., Hintze, B. J., Chen, V. B., Jain, S., Lewis, S. M., Arendall, W. B., Snoeyink, J., Adams, P. D., Lovell, S. C., Richardson, J. S., & Richardson, D. C. (2018). MolProbity: More and better reference data for improved all-atom structure validation. Protein Science: A Publication of the Protein Society, 27(1), 293–315. https://doi.org/10.1002/pro.3330
   PubMed Web of Science ®Google Scholar
• Yuan, S., Chan, H. C. S., Filipek, S., & Vogel, H. (2016). PyMOL and Inkscape bridge the data and the data visualization. Structure (London, England: 1993), 24(12), 2041–2042. https://doi.org/10.1016/j.str.2016.11.012
   PubMed Web of Science ®Google Scholar
• Zhou, X., Iversen, E. S., & Parmigiani, G. (2005). Classification of missense mutations of disease genes. Journal of the American Statistical Association, 100(469), 51–60. https://doi.org/10.1198/016214504000001817
   PubMed Web of Science ®Google Scholar