پیوندهای مفید
آمار
| تعداد نشریات | 30 |
| تعداد شماره‌ها | 467 |
| تعداد مقالات | 4,522 |
| تعداد مشاهده مقاله | 7,145,291 |
| تعداد دریافت فایل اصل مقاله | 5,334,968 |
Evaluating Functional and Structural Consequences of the most Deleterious Single Nucleotide Polymorphisms of Human C-X-C Motif Chemokine 10 (CXCL10) Using in silico Analyses | ||
| Journal of Genetic Resources | ||
| دوره 7، شماره 2، 2021، صفحه 227-245 اصل مقاله (680.15 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22080/jgr.2021.21373.1252 | ||
| نویسندگان | ||
| Mozhdeh Riahi1، 2؛ Modjtaba Emadi-Baygi* 1، 2 | ||
| 1Department of Genetics, Faculty of Basic Sciences, Shahrekord University, Shahrekord, Iran | ||
| 2Biotechnology Research Institute, Shahrekord University, Shahrekord, Iran | ||
| تاریخ دریافت: 07 فروردین 1400، تاریخ بازنگری: 09 خرداد 1400، تاریخ پذیرش: 12 خرداد 1400 | ||
| چکیده | ||
| Single Nucleotide Polymorphisms, especially non-synonymous single-nucleotide polymorphisms (nsSNPs), which are the cause of various diseases, are a major issue in genetics. NsSNPs in protein-coding genes can cause functional and structural variations in the altered protein. The human CXCL10 gene, localized on chromosome 4q21, is a pro-inflammatory cytokine and plays a role in diverse and critical biological mechanisms. Despite its significance, there is not any document about the impact of variations mapped to this protein. Accordingly, we gathered data about SNPs on the CXCL10 protein and examined the diverse effects of deleterious ones on the function and structure of the protein using various web-based tools. Our analyses indicated that 9 most deleterious nsSNPs (identified by SIFT, PROVEAN, PolyPhen-2, SNPs&GO, PhD-SNP, SNAP2, and PMut) in the conserved region of the CXCL10 affect the molecular function and stability of the protein. By utilizing RMSD values, we concluded that these substitutions in the native structure cause several changes in the protein, including in the N-terminal end, which is vital for binding to the receptor, and finally results in altered regulation, expression, function, and consequently leads to different diseases. Furthermore, some SNPs on the 3′ UTR site showed pattern alterations in the upstream open reading frames (uORFs) and BRD-BOX; moreover, SNPs in this area result in significant changes in miRNA binding sites consequently. Finally, by some analyses, we identified that the CXCL10 deregulation might be a proper prognostic marker in gastric and ovarian cancer. These types of studies help scientists determine whether SNPs are worth following for additional experimental studies to maximize the outcome while studying human health. | ||
| کلیدواژه‌ها | ||
| CXCL10؛ Deleterious substitution؛ Kaplan-Meier؛ nsSNP؛ SIFT | ||
| مراجع | ||
|
Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, Kondrashov AS, Sunyaev SR. 2010. A method and server for predicting damaging missense mutations. Nat Methods 7: 248-249.
Akhoundi F, Parvaneh N, Modjtaba EB. 2016. In silico analysis of deleterious single nucleotide polymorphisms in human BUB1 mitotic checkpoint serine/threonine kinase B gene. Meta Gene 9: 142-150.
Antonelli A, Ferrari SM, Giuggioli D, Ferrannini E, Ferri C, Fallahi P. 2014. Chemokine (C-X-C motif) ligand (CXCL)10 in autoimmune diseases. Autoimmun Rev 13(3): 272-280.
Arshad M, Bhatti AJP. 2018. Identification and in silico analysis of functional SNPs of human TAGAP protein: A comprehensive study. Plos One 13(1): 1-13.
Ashkenazy H, Abadi S, Martz E, Chay O, Mayrose I, Pupko T, Ben-Tal N. 2016. ConSurf 2016 : an improved methodology to estimate and visualize evolutionary conservation in macromolecules. Nucleic Acids Res 44: 344-350.
Ashkenazy H, Erez E, Martz E, Pupko T BN. 2010. ConSurf 2010 : calculating evolutionary conservation in sequence and structure of proteins and nucleic acids. Nucleic Acids Res 38: 529-533.
Au KK, Peterson N, Truesdell P, Reid-Schachter G, Khalaj K, Ren R, Francis JA, Graham CH, Craig AW, Koti M. 2017. CXCL10 alters the tumour immune microenvironment and disease progression in a syngeneic murine model of high-grade serous ovarian cancer. Gynecol Oncol 145(3): 436-445.
Arenberg D, Luckhardt TR, Carskadon S, Zhao L, Amin MA, Koch AE. 2010. Macrophage migration inhibitory factor promotes tumor growth in the context of lung injury and repair. Am J Respir Crit Care Med 182(8): 1030-1037.
Barbosa C, Peixeiro I, Romão L. 2013. Gene expression regulation by upstream open reading frames and human disease. PLoS Genet 9(8): e1003529.
Bhattacharya A, Ziebarth JD, Cui Y. 2014. PolymiRTS database 3.0: linking polymorphisms in microRNAs and their target sites with human diseases and biological pathways. Nucleic Acids Res 42: D86-91.
Booth V, Keizer DW, Kamphuis MB, Clark-lewis I, Sykes BD. 2002. The CXCR3 binding chemokine IP-10 / CXCL10 : structure and receptor. Biochemistry 41(33): 10418-10425.
Bronger H, Singer J, Windmüller C, Reuning U, Zech D, Delbridge C, Dorn J, Kiechle M, Schmalfeldt B, Schmitt M, Avril S. 2016. CXCL9 and CXCL10 predict survival and are regulated by cyclooxygenase inhibition in advanced serous ovarian cancer. Br J Cancer 115(5): 553-563.
Campanella GS, Lee EM, Sun JLA. 2003. CXCR3 and Heparin binding sites of the chemokine ip-10. J Biol Chem 278(19): 17066-17074.
Capriotti E, Calabrese R, Casadio R. 2006. Predicting the insurgence of human genetic diseases associated to single point protein mutations with support vector machines and evolutionary information. Bioinformatics 22(22): 2729-2734
Capriotti E, Calabrese R, Fariselli P, Martelli P, Altman RB, 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.
Capriotti E, Fariselli P, Rossi I, Casadio R. 2008. A three-state prediction of single point mutations on protein stability changes. BMC Bioinformatics 9(s6): 1-9.
Choi Y, Chan AP. 2015. PROVEAN web server : a tool to predict the functional effect of amino acid substitutions and indels. Bioinformatics 31(16): 2745-2747.
Clark-lewis I, Mattioli I, Gong J, Loetscher P. 2003. Structure-function relationship between the human chemokine receptor CXCR3 and its ligands. J Biol Chem 278(1): 289-295.
Colobran R, Pujol-Borrell R, Armengol MP JM. 2007. The chemokine network. II. On how polymorphisms and alternative splicing increase the number of molecular species and configure intricate patterns of disease susceptibility. Clin Exp Immunol 150(1): 1-12.
Coperchini F, Chiovato L, Croce L, Magri F, Rotondi M. 2020. The cytokine storm in COVID-19: An overview of the involvement of the chemokine/chemokine-receptor system. Cytokine Growth Factor Rev 53: 25-32.
Deng G, Zhou G, Zhang R, Zhai Y, Zhao W, Yan Z, Deng C, Yuan X, Xu B, Dong X, Zhang X. 2008. Regulatory polymorphisms in the promoter of CXCL10 gene and disease progression in male Hepatitis B virus carriers. Gastroenterology 134(3): 716-726.
Dimberg J, Skarstedt M, Löfgren S, Zar N, Matussek A. 2014. Protein expression and gene polymorphism of CXCL10 in patients with colorectal cancer. Biomed Rep 2: 340-343.
Dong C, Wei P, Jian X, Gibbs R, Boerwinkle E, Wang K, Liu X. 2015. Comparison and integration of deleteriousness prediction methods for nonsynonymous SNVs in whole exome sequencing studies. Hum Mol Genet 24(8): 2125-2137.
Fernald GH, Capriotti E, Daneshjou R, Karczewski KJ, Altman RB. 2011. Bioinformatics challenges for personalized medicine. Bioinformatics 27(13): 1741-1748.
Ferrer-Costa C, Gelpí JL, Zamakola L, Parraga I, de la Cruz X, Orozco M. 2005. Structural bioinformatics PMUT: a web-based tool for the annotation of pathological mutations on proteins. Bioinformatics 21(14): 3176-3178.
Grillo G, Turi A, Licciulli F, Mignone F, Liuni S, Banfi S, Gennarino VA, Horner DS, Pavesi G, Picardi E, Pesole G. 2009. UTRdb and UTRsite (RELEASE 2010): A collection of sequences and regulatory motifs of the untranslated regions of eukaryotic mRNAs. Nucleic Acids Res 38: D75-80.
Hayney MS, Henriquez KM, Barnet JH, Ewers T, Al E. 2017. Serum IFN-gamma-induced protein 10 (IP-10) as a biomarker for severity of acute respiratory infection in healthy adults. J Clin Virol 90: 32-37.
Hecht M, Bromberg Y, Rost B. 2015. Better prediction of functional effects for sequence variants. BMC Genomics 16(8): S1. https://doi.org/10.1186/1471-2164-16-S8-S1
Jabeen T, Leonard P, Jamaluddin H, Acharya K.R. 2008. Structure of mouse IP-10, a chemokine. Acta Crystallogr D Biol Crystallogr 64(6): 611-619.
Johansson MU, Zoete V, Michielin O, Guex N. 2012. Defining and searching for structural motifs using DeepView / Swiss-PdbViewer. BMC Bioinformatics 13 (173). https://doi.org/10.1186/1471-2105-13-173
Karbassi I, Maston GA, Love A, DiVincenzo C, Braastad CD, Elzinga CD, Bright AR, Previte D, Zhang K, Rowland CM, McCarthy M. 2015. A standardized DNA variant scoring system for pathogenicity assessments in mendelian disorders. Hum Mutat 37(1): 127-134.
Kishore J, Goel M, Khanna P. 2010. Understanding survival analysis: Kaplan-Meier estimate. Int J Ayurveda Res 1(4): 274-278.
Kulshreshtha S, Chaudhary V, Goswami GK, Mathur N. 2016. Computational approaches for predicting mutant protein stability. J Comput Aided Mol Des 30(5): 401-412.
Kumar P, Henikoff S, Ng P. 2009. Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat Protoc 4(7): 1073-1082.
Lai EC. 2002. Micro RNAs are complementary to 3′UTR sequence motifs that mediate negative post-transcriptional. Nat Genet 30: 363-364.
Li B, Krishnan VG, Mort ME, Xin F, Kamati KK, Cooper DN, Mooney SD, Radivojac P. 2009. Automated inference of molecular mechanisms of disease from amino acid substitutions. Bioinformatics 25(21): 2744-2750.
Liu M, Guo S, Hibbert JM, Jain V, Singh N, Wilson NO SJ. 2011. CXCL10/IP-10 in infectious diseases pathogenesis and potential therapeutic implications. Cytokine Growth Factor Rev 22(3): 121-130.
Liu M, Guo S SJ. 2011. The emerging role of CXCL10 in cancer. Oncol Lett 2(4): 583-589.
Lucca LE, Hafler DA. 2017. Resisting fatal attraction : a glioma oncometabolite prevents CD8+ T cell recruitment. J Clin Invest 127(4): 1218-1220.
Mah JTL, Low ESH, Lee E. 2011. In silico SNP analysis and bioinformatics tools : a review of the state of the art to aid drug discovery. Drug Discov Today 16: 800-809.
Maiti R, Domselaar GH Van, Zhang H, Wishart DS. 2004. SuperPose : a simple server for sophisticated structural superposition. Nucleic Acids Res 32: 590-594.
Meng Q, Yihong Z, George H.L. 2020. Targeting autophagy facilitates T lymphocyte migration by inducing the expression of CXCL10 in gastric cancer cell lines. Front Oncol 10: 886. https://doi.org/10.3389/fonc.2020.00886
Mignone F, Gissi C, Liuni S. 2002. Untranslated regions of mRNAs. Genome Biol 3. https://doi.org/10.1186/gb-2002-3-3-reviews0004
Miller MP, Kumar S. 2001. Understanding human disease mutations through the use of interspecific genetic variation. Hum Mol Genet 10(21): 2319-28.
O'Brien J, Hayder H, Zayed Y, Peng C. 2018. Overview of microRNA biogenesis, mechanisms of actions, and circulation. Front Endocrin 9: 402. https://doi.org/10.3389/fendo.2018.00402
Pejaver V, Urresti J, Lugo-Martinez J, Pagel KA, Lin GN, Nam HJ, Mort M, Cooper DN, Sebat J, Iakoucheva LM, Mooney SD. 2017. MutPred2 : inferring the molecular and phenotypic impact of amino acid variants. Nat Commun 11: 5918. https://doi.org/10.1038/s41467-020-19669-x
Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE. 2004. UCSF Chimera - a visualization system for exploratory research and analysis. J Comput Chem 25(13): 1605-1612.
Proudfoot AE, Fritchley S, Borlat F, Shaw JP, Vilbois F, Zwahlen C, Trkola A, Marchant D, Clapham PR, Wells TN. 2001. The BBXB motif of RANTES is the principal site for heparin binding and controls receptor selectivity. J Biol Chem 276(14): 10620-10626.
Sayers EW, Agarwala R, Bolton EE, Brister JR, Canese K, Clark K, Connor R, Fiorini N, Funk K, Hefferon T, Holmes JB. 2019. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res 47(D1): D23–D28.
Shendure J, Akey JM. 2015. The origins, determinants, and consequences of human mutations. Science 349: 1478-1483.
Swaminathan GJ, Holloway DE, Colvin RA, Campanella GK, Papageorgiou AC, Luster AD, Acharya KR. 2003. Crystal structures of oligomeric forms of the IP-10/CXCL10 chemokine. Structure 11(5): 521-532.
Tokunaga R, Zhang WU, Naseem M, Puccini A, Berger MD, Soni S, McSkane M, Baba H, Lenz HJ. 2018. CXCL9, CXCL10, CXCL11/CXCR3 axis for immune activation - a target for novel cancer therapy. Cancer Treat Rev 63: 40-47.
Venselaar H, Te Beek TA, Kuipers RK, Hekkelman ML, Vriend G. 2010. Protein structure analysis of mutations causing inheritable diseases. An e-Science approach with life scientist friendly interfaces. BMC Bioinformatics 11: 548. https://doi.org/10.1186/1471-2105-11-548
Vinet J, De Jong EK, Boddeke HW, Stanulovic V, Brouwer N, Granic I, Eisel UL, Liem RS, Biber K. 2010. Expression of CXCL10 in cultured cortical neurons. J Neurochem 112(3): 703-714.
Wang LL, Li Y, Zhou SF. 2009. A bioinformatics approach for the phenotype prediction of nonsynonymous single nucleotide polymorphisms in human cytochromes P450. Drug Metab Dispos 37(5): 977-991.
Wang Z, Moult J. 2001. SNPs, protein structure, and disease. Hum Mut 17(4): 263-270.
Yang J, Richmond A. 2004. The angiostatic activity of interferon-inducible protein-10/CXCL10 in human melanoma depends on binding to CXCR3 but not to glycosaminoglycan. Mol Ther 9(6): 846-855.
Yang J, Yan R, Roy A, Xu D, Poisson J, Zhang Y. 2014. The I-TASSER suite: protein structure and function prediction. Nat Methods 12(1): 7-8.
Yin S, Ding F, Dokholyan NV. 2007. Eris: an automated estimator of protein stability. Nat Methods 4(6): 466-467.
Young E, Lee Z, Wook Y. 2009. CXCL10 and autoimmune diseases. Autoimmun Rev 8(5): 379-383.
Yuan Y, Weidhaas JB. 2018. Functional microRNA binding site variants. Mol Oncol 13(1): 4-8.
Yue P, Li Z MJ. 2005. Loss of protein structure stability as a major causative factor in monogenic disease. J Mol Biol 353(2): 459-473.
Zhao M, Ma Q, Xu J, Fu S, Chen L, Wang B, Wu J, Yang L. 2015. Combining CXCL10 gene therapy and radiotherapy improved therapeutic efficacy in cervical cancer HeLa cell xenograft tumor models. Oncol Lett 2: 768-772. | ||
|
آمار تعداد مشاهده مقاله: 484 تعداد دریافت فایل اصل مقاله: 451 |
||