MODELING, BINDING SITE, AND IMMUNOGENICITY ANALYSIS OF GENES ENCODING L-ASPARAGINASE FROM ARTHROSPIRA PLATENSIS NIES 39
DOI:
https://doi.org/10.22159/ijap.2023v15i1.46177Keywords:
Arthrospira platensis, Immune response, L-asparaginase, ModelingAbstract
Objective: This work aimed to study the modeling, binding site, and immunogenicity analysis of genes encoding L-asparaginase from Arthrospira platensis NIES 39.
Methods: Physicochemical characteristic of the gene was analyzed using ProtParam. I-TASSER, PROCHECK, ProSA, and ProQ were used to build the L-asparaginase model. The enzyme's binding site was achieved based on the SiteMap and COACH analysis. Immunogenicity analysis was based on MHC II binding epitopes on the immune epitope database with further epitope prediction, such as NN-align, SMM aligns, Combinatorial library, and Net MHCIIpan.
Results: The result showed that the protein had an aliphatic index of 94.46. It was dominated by strand, helix, and coil groups. The best template for building the model was the malonate-bound human L-asparaginase protein. The amino acid at 173,191,193, 201, 204, 205, 223, and 225 positions served as binding sites. The best substrate for A. platensis NIES 39 asparaginase was L-asparagine. There is no substantial evidence that the protein is highly allergenic.
Conclusion: In conclusion, this is the first report on the character of ASNase from microalgae A. platensis where the enzyme has the potential to be applied for health applications because of its low allergenicity.
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Nunes JCF, Cristovao RO, Santos Ebinuma VC, Faria JL, Silva CG, Neves MC. L-asparaginase-based biosensors. Encyclopedia. 2021 Aug 20;1(3):848-58. doi: 10.3390/encyclopedia1030065.
Onishi Y, Prihanto AA, Yano S, Takagi K, Umekawa M, Wakayama M. Effective treatment for suppression of acrylamide formation in fried potato chips using L-asparaginase from Bacillus subtilis. 3 Biotech. 2015 Feb 4;5(5):783-9. doi: 10.1007/s13205-015-0278-5, PMID 28324531.
Xu F, Oruna Concha MJ, Elmore JS. The use of asparaginase to reduce acrylamide levels in cooked food. Food Chem. 2016 Nov 1;210:163-71. doi: 10.1016/j.foodchem.2016.04.105, PMID 27211635.
Baskar G, Aiswarya R. Overview on mitigation of acrylamide in starchy fried and baked foods. J Sci Food Agric. 2018 May 11;98(12):4385-94. doi: 10.1002/jsfa.9013, PMID 29572830.
Prihanto AA, Wakayama M. Marine microorganism: an underexplored source of l-asparaginase. Adv Food Nutr Res. 2016 Aug 26;79:1-25. doi: 10.1016/bs.afnr.2016.07.005, PMID 27770857.
Kotzia GA, Labrou NE. Engineering thermal stability of l-asparaginase by in vitro directed evolution. FEBS Journal. 2009 Feb 25;276(6):1750-61. doi: 10.1111/j.1742-4658.2009.06910.x, PMID 19220855.
Verma S, Mehta RK, Maiti P, Rohm KH, Sonawane A. Improvement of stability and enzymatic activity by site-directed mutagenesis of E. coli asparaginase II. Biochim Biophys Acta. 2014 Apr 8;1844(7):1219-30. doi: 10.1016/j.bbapap.2014.03.013, PMID 24721562.
Ampofo J, Abbey L. Microalgae: Bioactive composition, health benefits, safety and prospects as potential high-value ingredients for the functional food industry. Foods. 2022 Jun 14;11(12):1744-64. doi: 10.3390/foods11121744, PMID 35741941.
Sharafi Z, Barati M, Khoshayand MR, Adrangi S. Screening for type II L-asparaginases: lessons from the genus Halomonas. Iran J Pharm Res. 2017;16(4):1565-73. PMID 29552065.
Prihanto AA, Wakayama M. Combination of environmental stress and localization of L-asparaginase in Arthrospira platensis for production improvement. 3 Biotech. 2014 Apr 13;4(6):647-53. doi: 10.1007/s13205-014-0215-z, PMID 28324309.
Halgren TA. Identifying and characterizing binding sites and assessing druggability. J Chem Inf Model. 2009 Jan 20;49(2):377-89. doi: 10.1021/ci800324m, PMID 19434839.
Wang P, Sidney J, Dow C, Mothe B, Sette A, Peters B. A systematic assessment of MHC class II peptide binding predictions and evaluation of a consensus approach. PLOS Comput Biol. 2008;4(4):e1000048. doi: 10.1371/journal.pcbi.1000048, PMID 18389056.
Nielsen M, Lund O. NN-align. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction. BMC Bioinf. 2009 Sep 18;10:296. doi: 10.1186/1471-2105-10-296, PMID 19765293.
Nielsen M, Lundegaard C, Lund O. Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method. BMC Bioinf. 2007 Jul 4;8(238):238. doi: 10.1186/1471-2105-8-238, PMID 17608956.
Sidney J, Assarsson E, Moore C, Ngo S, Pinilla C, Sette A. Quantitative peptide binding motifs for 19 human and mouse MHC class I molecules derived using positional scanning combinatorial peptide libraries. Immunome Res. 2008 Jan 25;4(1):1-14. doi: 10.1186/1745-7580-4-2.
Andreatta M, Karosiene E, Rasmussen M, Stryhn A, Buus S, Nielsen M. Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification. Immunogenetics. 2015 Sep 29;67(11-12):641-50. doi: 10.1007/s00251-015-0873-y, PMID 26416257.
de Belen RAJ, Bednarz T, Sowmya A, Del Favero D. Computer vision in autism spectrum disorder research: a systematic review of published studies from 2009 to 2019. Transl Psychiatry. 2020 Sep 30;10(1):333. doi: 10.1038/s41398-020-01015-w, PMID 32999273.
Jespersen MC, Peters B, Nielsen M, Marcatili P. MarcatiliBepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes. Nucleic Acids Res. 2017 Jul 3;45(W1):W24-9. doi: 10.1093/nar/gkx346, PMID 28472356.
Dimitrov I, Bangov I, Flower DR, Doytchinova I. AllerTOP v.2–a server for in silico prediction of allergens. J Mol Model. 2014 May 31;20(6):2278. doi: 10.1007/s00894-014-2278-5, PMID 24878803.
Maurer Stroh S, Krutz NL, Kern PS, Gunalan V, Nguyen MN, Limviphuvadh V. AllerCatPro-prediction of protein allergenicity potential from the protein sequence. Bioinformatics. 2019 Sep 1;35(17):3020-7. doi: 10.1093/bioinformatics/btz029, PMID 30657872.
Azabji Kenfack M, Dikosso SE, Loni EG, Onana EA, Sobngwi E, Gbaguidi E. Potential of Spirulina platensis as a nutritional supplement in malnourished HIV-Infected Adults in sub-Saharan Africa: A Randomised, single-blind study. Nutr Metab Insights. 2011;4:29-37. doi: 10.4137/NMI.S5862, PMID 23946659.
Gutierrez Salmean G, Fabila Castillo L, Chamorro Cevallos G. Nutritional and toxicological aspects of Spirulina (Arthrospira). Nutr Hosp. 2015 Jul 1;32(1):34-40. doi: 10.3305/nh.2015.32.1.9001, PMID 26262693.
Kulkarni S, Chavan D. Nutritional and therapeutic evaluation of Spirulina platensis. Asian J Pharm Clin Res. 2020 Jul;13(7):86-90. doi: 10.22159/ajpcr.2020.v13i7.34123.
Schalk AM, Nguyen HA, Rigouin C, Lavie A. Identification and structural analysis of an L-asparaginase enzyme from guinea pig with putative tumor cell killing properties. J Biol Chem. 2014 Nov 28;289(48):33175-86. doi: 10.1074/jbc.M114.609552. PMID 25320094.
Pritsa AA, Kyriakidis DA. L-asparaginase of thermus thermophilus: purification, properties and identification of essential amino acids for its catalytic activity. Mol Cell Biochem. 2001;216(1-2):93-101. doi: 10.1023/a:1011066129771. PMID 11216870.
Chand S, Mihooliya KN, Sahoo DK, Prasad JP, Sharma G. L-asparaginase from Bacillus flexus strain SS: isolation, screening, production process optimization, purification, and anticancer activity. Appl Biochem Microbiol. 2022;58(4):416-27. doi: 10.1134/S0003683822040032.
Sidoruk KV, Pokrovsky VS, Borisova AA, Omeljanuk NM, Aleksandrova SS, Pokrovskaya MV. Creation of a producent, optimization of expression, and purification of recombinant Yersinia pseudotuberculosis L-asparaginase. Bull Exp Biol Med. 2011;152(2):219-23. doi: 10.1007/s10517-011-1493-7. PMID 22808465.
Lubkowski J, Vanegas J, Chan WK, Lorenzi PL, Weinstein JN, Sukharev S. Mechanism of catalysis by l-asparaginase. Biochemistry. 2020 May 26;59(20):1927-45. doi: 10.1021/acs.biochem.0c00116. PMID 32364696.
Lubkowski J, Wlodawer A. Geometric considerations support the double-displacement catalytic mechanism of l-asparaginase. Protein Sci. 2019 Oct;28(10):1850-64. doi: 10.1002/pro.3709. PMID 31423681, PMC6740147.
https://prosite.expasy.org/PS00144. [Last accessed on 17 Dec 2022]
Feng Y, Liu S, Jiao Y, Gao H, Wang M, Du G. Enhanced extracellular production of L-asparaginase from bacillus subtilis 168 by B. subtilis WB600 through a combined strategy. Appl Microbiol Biotechnol. 2017;101(4):1509-20. doi: 10.1007/s00253-016-7816-x, PMID 27796436.
Agrawal S, Jana UK, Kango N. Heterologous expression and molecular modelling of L-asparaginase from Bacillus subtilis ETMC-2. Int J Biol Macromol. 2021;192:28-37. doi: 10.1016/j.ijbiomac.2021.09.186, PMID 34610352.
Li X, Zhang X, Xu S, Xu M, Yang T, Wang L. Insight into the thermostability of thermophilic L-asparaginase and non-thermophilic L-asparaginase II through bioinformatics and structural analysis. Appl Microbiol Biotechnol. 2019;103(17):7055-70. doi: 10.1007/s00253-019-09967-w, PMID 31273395.
Wetzler M. Asparaginase allergies: it’s all in the genes. Blood. 2014 Aug 21;124(8):1206-7. doi: 10.1182/blood-2014-07-585919, PMID 25147374.
Link J, Lundkvist Ryner M, Fink K, Hermanrud C, Lima I, Brynedal B. Human leukocyte antigen genes and interferon beta preparations influence risk of developing neutralizing anti-drug antibodies in multiple sclerosis. Plos One. 2014 Mar 7;9(3):e90479. doi: 10.1371/journal.pone.0090479. PMID 24608124.
Kutszegi N, Yang X, Gezsi A, Schermann G, Erdelyi DJ, Semsei AF. HLA-DRB1*07:01-HLA-DQA1*02:01-HLA-DQB1*02:02 haplotype is associated with a high risk of asparaginase hypersensitivity in acute lymphoblastic leukemia. Haematologica. 2017 Sep;102(9):1578-86. doi: 10.3324/haematol.2017.168211, PMID 28596278.
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Copyright (c) 2023 ASEP A. PRIHANTO, HAPPY NURSYAM, RAHMI NURDIANI, HIDAYATUN MUYASYAROH, ROYANI L. HAYATI, ANIS MIFTACURROCHMAH
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