Impact of nsSNPs in human AIM2 and IFI16 gene: a comprehensive in silico analysis

References

• Aalten, D. M. F., van Findlay, J. B. C., Amadei, A., & Berendsen, H. J. C. (1995). Essential dynamics of the cellular retinol-binding protein evidence for ligand-induced conformational changes. Protein Engineering, 8(11), 1129–1135. https://doi.org/10.1093/protein/8.11.1129
   PubMedGoogle Scholar
• Arshad, M., Bhatti, A., & John, P. (2018). Identification and in silico analysis of functional SNPs of human TAGAP protein: A comprehensive study. PLoS One, 13(1), e0188143. https://doi.org/10.1371/journal.pone.0188143
   PubMed Web of Science ®Google Scholar
• Asefa, B., Klarmann, K. D., Copeland, N. G., Gilbert, D. J., Jenkins, N. A., & Keller, J. R. (2004). The interferon-inducible p200 family of proteins: A perspective on their roles in cell cycle regulation and differentiation. Blood Cells, Molecules & Diseases, 32(1), 155–167. https://doi.org/10.1016/j.bcmd.2003.10.002
   PubMed Web of Science ®Google Scholar
• Bekker, H., Berendsen, H., Dijkstra, E., Achterop, S., Vondrumen, R., Vanderspoel, D., Sijbers, A., Keegstra, H., & Renardus, M. (1993). GROMACS - A parallel computer for molecular-dynamics simulations. In 4th International Conference on Computational Physics (PC 92). PHYSICS COMPUTING (vol. 92, pp. 252–256).
   Google Scholar
• Ben Chorin, A., Masrati, G., Kessel, A., Narunsky, A., Sprinzak, J., Lahav, S., Ashkenazy, H., & Ben-Tal, N. (2020). ConSurf-DB: An accessible repository for the evolutionary conservation patterns of the majority of PDB proteins. Protein Science : A Publication of the Protein Society, 29(1), 258–267. https://doi.org/10.1002/pro.3779
   PubMed Web of Science ®Google Scholar
• Berman, H. M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T. N., Weissig, H., Shindyalov, I. N., & Bourne, P. E. (2000). The Protein Data Bank. Nucleic Acids Research, 28(1), 235–242. https://doi.org/10.1093/nar/28.1.235
   PubMed Web of Science ®Google Scholar
• Bromberg, Y., & Rost, B. (2007). SNAP: Predict effect of non-synonymous polymorphisms on function. Nucleic Acids Research, 35(11), 3823–3835. https://doi.org/10.1093/nar/gkm238
   PubMed Web of Science ®Google Scholar
• Capriotti, E., Altman, R. B., & Bromberg, Y. (2013). Collective judgment predicts disease-associated single nucleotide variants. BMC Genomics. 14(Suppl 3), S2. https://doi.org/10.1186/1471-2164-14-S3-S2
   PubMedGoogle Scholar
• Capriotti, E., Calabrese, R., Fariselli, P., Martelli, P. L., Altman, R. B., & Casadio, R. (2013). WS-SNPs&GO: A web server for predicting the deleterious effect of human protein variants using functional annotation. BMC Genomics, 14(Suppl 3), S6. https://doi.org/10.1186/1471-2164-14-S3-S6
   PubMed Web of Science ®Google Scholar
• Capriotti, E., & Fariselli, P. (2017). PhD-SNPg: A webserver and lightweight tool for scoring single nucleotide variants. Nucleic Acids Research, 45(W1), W247–W252. https://doi.org/10.1093/nar/gkx369
   PubMed Web of Science ®Google Scholar
• 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 issue), W306–W310. https://doi.org/10.1093/nar/gki375
   PubMed Web of Science ®Google Scholar
• 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/10.1093/bioinformatics/btv195
   PubMed Web of Science ®Google Scholar
• Choubey, D., Duan, X., Dickerson, E., Ponomareva, L., Panchanathan, R., Shen, H., & Srivastava, R. (2010). Interferon-inducible p200-family proteins as novel sensors of cytoplasmic DNA: Role in inflammation and autoimmunity. Journal of Interferon & Cytokine Research : The Official Journal of the International Society for Interferon and Cytokine Research, 30(6), 371–380. https://doi.org/10.1089/jir.2009.0096
   PubMed Web of Science ®Google Scholar
• Dash, R., Mitra, S., Munni, Y. A., Choi, H. J., Ali, M. C., Barua, L., Jang, T. J., & Moon, I. S. (2021). Computational insights into the deleterious impacts of missense variants on N-acetyl-d-glucosamine kinase structure and function. International Journal of Molecular Sciences, 22(15), 8048. https://doi.org/10.3390/ijms22158048
   PubMed Web of Science ®Google Scholar
• de Zoete, M. R., Palm, N. W., Zhu, S., & Flavell, R. A. (2014). Inflammasomes. Cold Spring Harbor Perspectives in Biology, 6(12), a016287. https://doi.org/10.1101/cshperspect.a016287
   PubMed Web of Science ®Google Scholar
• DeYoung, K. L., Ray, M. E., Su, Y. A., Anzick, S. L., Johnstone, R. W., Trapani, J. A., Meltzer, P. S., & Trent, J. M. (1997). Cloning a novel member of the human interferon-inducible gene family associated with control of tumorigenicity in a model of human melanoma. Oncogene, 15(4), 453–457. https://doi.org/10.1038/sj.onc.1201206
   PubMed Web of Science ®Google Scholar
• Du, K., Sharma, M., & Lukacs, G. L. (2005). The DeltaF508 cystic fibrosis mutation impairs domain-domain interactions and arrests post-translational folding of CFTR. Nature Structural & Molecular Biology, 12(1), 17–25. https://doi.org/10.1038/nsmb882
   PubMed Web of Science ®Google Scholar
• Gosu, V., Sasidharan, S., Saudagar, P., Lee, H.-K., & Shin, D. (2021). Computational insights into the structural dynamics of MDA5 variants associated with Aicardi–Goutières Syndrome and Singleton–Merten Syndrome. Biomolecules, 11(8), 1251. https://doi.org/10.3390/biom11081251
   PubMed Web of Science ®Google Scholar
• Gosu, V., Shin, D., Song, K.-D., Heo, J., & Oh, J.-D. (2022). Molecular modeling and dynamic simulation of chicken Mx protein with the S631N polymorphism. Journal of Biomolecular Structure & Dynamics, 40(2), 612–621. https://doi.org/10.1080/07391102.2020.1819419
   PubMed Web of Science ®Google Scholar
• Guo, H., Callaway, J. B., & Ting, J. P.-Y. (2015). Inflammasomes: Mechanism of action, role in disease, and therapeutics. Nature Medicine, 21(7), 677–687. https://doi.org/10.1038/nm.3893
   PubMed Web of Science ®Google Scholar
• In silico Analysis of BRCA1 Gene and its Phylogenetic Relationship in some Selected Domestic Animal Species. (n.d.). https://doi.org/10.3923/tb.2017.1.10
   Google Scholar
• Jin, T., Perry, A., Jiang, J., Smith, P., Curry, J. A., Unterholzner, L., Jiang, Z., Horvath, G., Rathinam, V. A., Johnstone, R. W., Hornung, V., Latz, E., Bowie, A. G., Fitzgerald, K. A., & Xiao, T. S. (2012). Structures of the HIN domain:DNA complexes reveal ligand binding and activation mechanisms of the AIM2 inflammasome and IFI16 receptor. Immunity, 36(4), 561–571. https://doi.org/10.1016/j.immuni.2012.02.014
   PubMed Web of Science ®Google Scholar
• Jin, T., Perry, A., Smith, P., Jiang, J., & Xiao, T. S. (2013). Structure of the absent in melanoma 2 (AIM2) pyrin domain provides insights into the mechanisms of AIM2 autoinhibition and inflammasome assembly. The Journal of Biological Chemistry, 288(19), 13225–13235. https://doi.org/10.1074/jbc.M113.468033
   PubMed Web of Science ®Google Scholar
• Kalia, N., Sharma, A., Kaur, M., Kamboj, S. S., & Singh, J. (2016). A comprehensive in silico analysis of non-synonymous and regulatory SNPs of human MBL2 gene. SpringerPlus, 5(1), 811. https://doi.org/10.1186/s40064-016-2543-4
   PubMedGoogle Scholar
• Kaur, R., Singh, J., & Kaur, M. (2017). Structural and functional impact of SNPs in P-selectin gene: A comprehensive in silico analysis. Open Life Sciences, 12(1), 19–33. https://doi.org/10.1515/biol-2017-0003
   Web of Science ®Google Scholar
• Kayagaki, N., Warming, S., Lamkanfi, M., Vande Walle, L., Louie, S., Dong, J., Newton, K., Qu, Y., Liu, J., Heldens, S., Zhang, J., Lee, W. P., Roose-Girma, M., & Dixit, V. M. (2011). Non-canonical inflammasome activation targets caspase-11. Nature, 479(7371), 117–121. https://doi.org/10.1038/nature10558
   PubMed Web of Science ®Google Scholar
• Krawczak, M., Ball, E. V., Fenton, I., Stenson, P. D., Abeysinghe, S., Thomas, N., & Cooper, D. N. (2000). Human gene mutation database-a biomedical information and research resource. Human Mutation, 15(1), 45–51. https://doi.org/10.1002/(SICI)1098-1004(200001)15:1<45::AID-HUMU10>3.0.CO;2-T
   PubMed Web of Science ®Google Scholar
• Kumar, R., Bansal, A., Shukla, R., Raj Singh, T., Wasudeo Ramteke, P., Singh, S., & Gautam, B. (2019). In silico screening of deleterious single nucleotide polymorphisms (SNPs) and molecular dynamics simulation of disease associated mutations in gene responsible for oculocutaneous albinism type 6 (OCA 6) disorder. Journal of Biomolecular Structure & Dynamics, 37(13), 3513–3523. https://doi.org/10.1080/07391102.2018.1520649
   PubMed Web of Science ®Google Scholar
• Lamkanfi, M., & Dixit, V. M. (2012). Inflammasomes and their roles in health and disease. Annual Review of Cell and Developmental Biology, 28, 137–161. https://doi.org/10.1146/annurev-cellbio-101011-155745
   PubMed Web of Science ®Google Scholar
• Lander, E. S. (1996). The new genomics: Global views of biology. Science (New York, N.Y.), 274(5287), 536–539. https://doi.org/10.1126/science.274.5287.536
   PubMed Web of Science ®Google Scholar
• Laskowski, R. A., MacArthur, M. W., Moss, D. S., & Thornton, J. M. (1993). PROCHECK: A program to check the stereochemical quality of protein structures. Journal of Applied Crystallography, 26(2), 283–291. https://doi.org/10.1107/S0021889892009944
   Web of Science ®Google Scholar
• Lindorff-Larsen, K., Piana, S., Palmo, K., Maragakis, P., Klepeis, J. L., Dror, R. O., & Shaw, D. E. (2010). Improved side-chain torsion potentials for the Amber ff99SB protein force field. Proteins, 78(8), 1950–1958. https://doi.org/10.1002/prot.22711
   PubMed Web of Science ®Google Scholar
• Mi, H., Ebert, D., Muruganujan, A., Mills, C., Albou, L.-P., Mushayamaha, T., & Thomas, P. D. (2021). PANTHER version 16: A revised family classification, tree-based classification tool, enhancer regions and extensive API. Nucleic Acids Research, 49(D1), D394–D403. https://doi.org/10.1093/nar/gkaa1106
   PubMed Web of Science ®Google Scholar
• Pathak, R. K., Lim, B., Park, Y., & Kim, J.-M. (2022). Unraveling structural and conformational dynamics of DGAT1 missense nsSNPs in dairy cattle. Scientific Reports, 12(1). https://doi.org/10.1038/s41598-022-08833-6
   Web of Science ®Google Scholar
• Pejaver, V., Urresti, J., Lugo-Martinez, J., Pagel, K. A., Lin, G. N., Nam, H.-J., Mort, M., Cooper, D. N., Sebat, J., Iakoucheva, L. M., Mooney, S. D., & Radivojac, P. (2020). Inferring the molecular and phenotypic impact of amino acid variants with MutPred2. Nature Communications, 11(1). https://doi.org/10.1038/s41467-020-19669-x
   PubMed Web of Science ®Google Scholar
• Ramensky, V., Bork, P., & Sunyaev, S. (2002). Human non-synonymous SNPs: Server and survey. Nucleic Acids Research, 30(17), 3894–3900. https://doi.org/10.1093/nar/gkf493
   PubMed Web of Science ®Google Scholar
• Ru, H., Ni, X., Zhao, L., Crowley, C., Ding, W., Hung, L.-W., Shaw, N., Cheng, G., & Liu, Z.-J. (2013). Structural basis for termination of AIM2-mediated signaling by p202. Cell Research, 23(6), 855–858. https://doi.org/10.1038/cr.2013.52
   PubMed Web of Science ®Google Scholar
• Sherry, S. T., Ward, M., & Sirotkin, K. (1999). DbSNP-database for single nucleotide polymorphisms and other classes of minor genetic variation. Genome Research, 9(8), 677–679. https://doi.org/10.1101/gr.9.8.677
   PubMed Web of Science ®Google Scholar
• Sim, N.-L., Kumar, P., Hu, J., Henikoff, S., Schneider, G., & Ng, P. C. (2012). SIFT web server: Predicting effects of amino acid substitutions on proteins. Nucleic Acids Research, 40(W1), W452–W457. https://doi.org/10.1093/nar/gks539
   PubMed Web of Science ®Google Scholar
• Singh, S. M., Kongari, N., Cabello-Villegas, J., & Mallela, K. M. G. (2010). Missense mutations in dystrophin that trigger muscular dystrophy decrease protein stability and lead to cross-β aggregates. Proceedings of the National Academy of Sciences of the United States of America, 107(34), 15069–15074. https://doi.org/10.1073/pnas.1008818107
   PubMed Web of Science ®Google Scholar
• Söding, J., Biegert, A., & Lupas, A. N. (2005). The HHpred interactive server for protein homology detection and structure prediction. Nucleic Acids Research, 33(Web Server issue), W244–W248. https://doi.org/10.1093/nar/gki408
   PubMed Web of Science ®Google Scholar
• Szklarczyk, D., Gable, A. L., Lyon, D., Junge, A., Wyder, S., Huerta-Cepas, J., Simonovic, M., Doncheva, N. T., Morris, J. H., Bork, P., Jensen, L. J., & Mering, C. V. (2019). STRING v11: Protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Research, 47(D1), D607–D613. https://doi.org/10.1093/nar/gky1131
   PubMed Web of Science ®Google Scholar
• The UniProt Consortium. (2021). UniProt: The universal protein knowledgebase in 2021. Nucleic Acids Research, 49(D1), D480–D489. https://doi.org/10.1093/nar/gkaa1100
   PubMed Web of Science ®Google Scholar
• Van Opdenbosch, N., & Lamkanfi, M. (2019). Caspases in cell death, inflammation, and disease. Immunity, 50(6), 1352–1364. https://doi.org/10.1016/j.immuni.2019.05.020
   PubMed Web of Science ®Google Scholar
• Wang, B., & Yin, Q. (2017). AIM2 inflammasome activation and regulation: A structural perspective. Journal of Structural Biology, 200(3), 279–282. https://doi.org/10.1016/j.jsb.2017.08.001
   PubMed Web of Science ®Google Scholar
• Yamaguchi, H., van Aalten, D. M., Pinak, M., Furukawa, A., & Osman, R. (1998). Essential dynamics of DNA containing a cis.syn cyclobutane thymine dimer lesion. Nucleic Acids Research, 26(8), 1939–1946. https://doi.org/10.1093/nar/26.8.1939
   PubMed Web of Science ®Google Scholar