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Functional and structural identification of iron-binding proteins on tomato (Solanum lycopersicum L.) proteome via in silico approaches

Yıl 2023, Cilt: 4 Sayı: 1, 17 - 29, 26.06.2023

Yiğit Küçükçobanoğlu Lale Aktaş

https://doi.org/10.51539/biotech.1262979

Öz

Iron-plant interactions have crucial roles in crop production growth and development. In this study, we have analyzed the whole proteome of tomato (Solanum lycopersicum L.) plants for iron-binding proteins. A total of 213 iron-binding protein candidates were identified in the study. Out of these 213 proteins, 45 were selected for modeling and validated with a high confidence level by using different computational analyses. Results showed that Glu, Cys, Asp, and His amino acid residues were indicators of iron-binding proteins. Besides, mechanistic insights of iron-binding proteins were analyzed by molecular dynamics simulations. Simulation results proved the conformational stabilization of proteins. Validated proteins were further analyzed for subcellular localization, clustered for molecular functions and biological processes. According to the results, iron-binding proteins were mostly located in the chloroplast. Also, these proteins are involved in different molecular and biological roles ranging from oxidation-reduction processes and electron transport chain to protein repair mechanisms. This report provides structural and functional properties of iron-binding proteins for tomato proteome. The study may assist in future research on plant physiology, protein engineering, or bioengineering.

Anahtar Kelimeler

iron - binding proteins tomato structural bioinformatics functional analysis three - dimensional modeling

Kaynakça

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Yıl 2023, Cilt: 4 Sayı: 1, 17 - 29, 26.06.2023

Yiğit Küçükçobanoğlu Lale Aktaş

https://doi.org/10.51539/biotech.1262979

Öz

Kaynakça

  • Allen JF (2004) Cytochrome b6f: structure for signalling and vectorial metabolism. Trends Plant Sci 9:130–137.
  • Andreini C, Cavallaro G, Lorenzini S, Rosato A (2012) MetalPDB: a database of metal sites in biological macromolecular structures. Nucleic Acids Res 41:D312–D319.
  • Andreini C, Cavallaro G, Rosato A, Valasatava Y (2013) MetalS2: a tool for the structural alignment of minimal functional sites in metal-binding proteins and nucleic acids. J Chem Inf Model 53:3064–3075.
  • Andreini C, Rosato A, Banci L (2017) The relationship between environmental dioxygen and iron-sulfur proteins explored at the genome level. PLoS One 12:e0171279.
  • Bechaieb R, Lakhdar ZB, Gérard H (2018) DFT and TD-DFT studies of Mg-substitution in chlorophyll by Cr (II), Fe (II) and Ni (II). Chemistry Africa 1:79–86.
  • Bernacchioni C, Pozzi C, di Pisa F, Mangani S, Turano P (2016) Ferroxidase Activity in Eukaryotic Ferritin is Controlled by Accessory-Iron-Binding Sites in the Catalytic Cavity. Chemistry–A European Journal 22:16213–16219.
  • Bertsova Y v, Kostyrko VA, Baykov AA, Bogachev A v (2014) Localization-controlled specificity of FAD: threonine flavin transferases in Klebsiella pneumoniae and its implications for the mechanism of Na+-translocating NADH: quinone oxidoreductase. Biochimica et Biophysica Acta (BBA)-Bioenergetics 1837:1122–1129.
  • Blum M, Chang H-Y, Chuguransky S, Grego T, Kandasaamy S, Mitchell A, Nuka G, Paysan-Lafosse T, Qureshi M, Raj S (2021) The InterPro protein families and domains database: 20 years on. Nucleic Acids Res 49:D344–D354.
  • Borukhov S, Nudler E (2008) RNA polymerase: the vehicle of transcription. Trends Microbiol 16:126–134.
  • Braymer JJ, Lill R (2017) Iron–sulfur cluster biogenesis and trafficking in mitochondria. Journal of Biological Chemistry 292:12754–12763.
  • Briat J-F, Curie C, Gaymard F (2007) Iron utilization and metabolism in plants. Curr Opin Plant Biol 10:276–282.
  • Briat J-F, Fobis-Loisy I, Grignon N, Lobréaux S, Pascal N, Savino G, Thoiron S, von Wirén N, van Wuytswinkel O (1995) Cellular and molecular aspects of iron metabolism in plants. Biol Cell 84:69–81.
  • Caetano-Silva ME, Bertoldo-Pacheco MT, Paes-Leme AF, Netto FM (2015) Iron-binding peptides from whey protein hydrolysates: Evaluation, isolation and sequencing by LC–MS/MS. Food Research International 71:132–139.
  • Chang Y-Y, Li H, Sun H (2017) Immobilized metal affinity chromatography (IMAC) for metalloproteomics and phosphoproteomics In: Inorganic and Organometallic Transition Metal Complexes with Biological Molecules and Living Cells , pp 329–353. Elsevier.
  • Chaud M v, Izumi C, Nahaal Z, Shuhama T, Bianchi M de LP, Freitas O de (2002) Iron derivatives from casein hydrolysates as a potential source in the treatment of iron deficiency. J Agric Food Chem 50:871–877.
  • Chen LX, Lee PL, Gosztola D, Svec WA, Montano PA, Wasielewski MR (1999) Time-resolved X-ray absorption determination of structural changes following photoinduced electron transfer within Bis-porphyrin Heme protein models. J Phys Chem B 103:3270–3274.
  • Chi S-M, Nam D (2012) WegoLoc: accurate prediction of protein subcellular localization using weighted Gene Ontology terms. Bioinformatics 28:1028–1030.
  • Ciofi-Baffoni S, Nasta V, Banci L (2018) Protein networks in the maturation of human iron–sulfur proteins. Metallomics 10:49–72.
  • DeFraia CT, Wang Y, Yao J, Mou Z (2013) Elongator subunit 3 positively regulates plant immunity through its histone acetyltransferase and radical S-adenosylmethionine domains. BMC Plant Biol 13:1–13.
  • Dong J, Lai R, Nielsen K, Fekete CA, Qiu H, Hinnebusch AG (2004) The Essential ATP-binding Cassette Protein RLI1 Functions in Translation by Promoting Preinitiation Complex Assembly*♦. Journal of Biological Chemistry 279:42157–42168.
  • Dutta S, Teresinski HJ, Smith MD (2014) A split-ubiquitin yeast two-hybrid screen to examine the substrate specificity of atToc159 and atToc132, two Arabidopsis chloroplast preprotein import receptors. PLoS One 9:e95026.
  • FAO F (2020) FAOSTAT statistical database. Rome: Food and Agriculture Organisation of the United Nations. Freedman RB, Hirst TR, Tuite MF (1994) Protein disulphide isomerase: building bridges in protein folding. Trends Biochem Sci 19:331–336.
  • Garcia JS, de Magalhães CS, Arruda MAZ (2006) Trends in metal-binding and metalloprotein analysis. Talanta 69:1–15.
  • Giles NM, Watts AB, Giles GI, Fry FH, Littlechild JA, Jacob C (2003) Metal and redox modulation of cysteine protein function. Chem Biol 10:677–693.
  • Gillespie RJ (1992) The VSEPR model revisited. Chem Soc Rev 21:59–69.
  • Gueguen V, Macherel D, Jaquinod M, Douce R, Bourguignon J (2000) Fatty acid and lipoic acid biosynthesis in higher plant mitochondria. Journal of Biological Chemistry 275:5016–5025.
  • Hase T, Schürmann P, Knaff DB (2006) The interaction of ferredoxin with ferredoxin-dependent enzymes In: Photosystem I , pp 477–498. Springer.
  • Hospital A, Andrio P, Fenollosa C, Cicin-Sain D, Orozco M, Gelpí JL (2012) MDWeb and MDMoby: an integrated web-based platform for molecular dynamics simulations. Bioinformatics 28:1278–1279.
  • Houston NL, Fan C, Xiang Q-Y, Schulze J-M, Jung R, Boston RS (2005) Phylogenetic analyses identify 10 classes of the protein disulfide isomerase family in plants, including single-domain protein disulfide isomerase-related proteins. Plant Physiol 137:762–778.
  • Hu X, Dong Q, Yang J, Zhang Y (2016) Recognizing metal and acid radical ion-binding sites by integrating ab initio modeling with template-based transferals. Bioinformatics 32:3260–3269.
  • Hu X, Shelver WH (2003) Docking studies of matrix metalloproteinase inhibitors: zinc parameter optimization to improve the binding free energy prediction. J Mol Graph Model 22:115–126.
  • Jahns P, Graf M, Munekage Y, Shikanai T (2002) Single point mutation in the Rieske iron–sulfur subunit of cytochrome b6/f leads to an altered pH dependence of plastoquinol oxidation in Arabidopsis. FEBS Lett 519:99–102.
  • Jin S, Hu Y, Fu H, Jiang S, Xiong Y, Qiao H, Zhang W, Gong Y, Wu Y (2021) Identification and characterization of the succinate dehydrogenase complex iron sulfur subunit B gene in the Oriental River Prawn, Macrobrachium nipponense. Front Genet 12.
  • Johnson DC, Dean DR, Smith AD, Johnson MK (2005) Structure, function, and formation of biological iron-sulfur clusters. Annu Rev Biochem 74:247.
  • Kannan L, Wheeler WC (2012) Maximum parsimony on phylogenetic networks. Algorithms for Molecular Biology 7:1–10.
  • Kelley LA, Mezulis S, Yates CM, Wass MN, Sternberg MJE (2015) The Phyre2 web portal for protein modeling, prediction and analysis. Nat Protoc 10:845–858.
  • Kolaczkowski B, Thornton JW (2004) Performance of maximum parsimony and likelihood phylogenetics when evolution is heterogeneous. Nature 431:980–984.
  • Kumar S, Stecher G, Li M, Knyaz C, Tamura K (2018) MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol 35:1547.
  • Kurisu G, Kusunoki M, Katoh E, Yamazaki T, Teshima K, Onda Y, Kimata-Ariga Y, Hase T (2001) Structure of the electron transfer complex between ferredoxin and ferredoxin-NADP+ reductase. Nat Struct Biol 8:117–121.
  • Li Q, Li Y, Li X, Chen S (2021) Identification of Genes Involved in Fe–S Cluster Biosynthesis of Nitrogenase in Paenibacillus polymyxa WLY78. Int J Mol Sci 22:3771.
  • Lin Y-F, Cheng C-W, Shih C-S, Hwang J-K, Yu C-S, Lu C-H (2016) MIB: metal ion-binding site prediction and docking server. J Chem Inf Model 56:2287–2291.
  • Litomska A, Ishida K, Dunbar KL, Boettger M, Coyne S, Hertweck C (2018) Enzymatic thioamide formation in a bacterial antimetabolite pathway. Angewandte Chemie International Edition 57:11574–11578.
  • Lu Y, Chakraborty S, Miner KD, Wilson TD, Mukherjee A, Yu Y, Liu J, Marshall NM (2013) Metalloprotein design In: Comprehensive Inorganic Chemistry II (Second Edition): From Elements to Applications , pp 565–593. Elsevier Ltd.
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Toplam 88 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yapısal Biyoloji
Bölüm Research Articles
Yazarlar

Yiğit Küçükçobanoğlu 0000-0002-9856-5506

Lale Aktaş 0000-0003-0815-8470

Yayımlanma Tarihi 26 Haziran 2023
Kabul Tarihi 9 Haziran 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 4 Sayı: 1

Kaynak Göster

APA Küçükçobanoğlu, Y., & Aktaş, L. (2023). Functional and structural identification of iron-binding proteins on tomato (Solanum lycopersicum L.) proteome via in silico approaches. Bulletin of Biotechnology, 4(1), 17-29. https://doi.org/10.51539/biotech.1262979
AMA Küçükçobanoğlu Y, Aktaş L. Functional and structural identification of iron-binding proteins on tomato (Solanum lycopersicum L.) proteome via in silico approaches. Bull. Biotechnol. Haziran 2023;4(1):17-29. doi:10.51539/biotech.1262979
Chicago Küçükçobanoğlu, Yiğit, ve Lale Aktaş. “Functional and Structural Identification of Iron-Binding Proteins on Tomato (Solanum Lycopersicum L.) Proteome via in Silico Approaches”. Bulletin of Biotechnology 4, sy. 1 (Haziran 2023): 17-29. https://doi.org/10.51539/biotech.1262979.
EndNote Küçükçobanoğlu Y, Aktaş L (01 Haziran 2023) Functional and structural identification of iron-binding proteins on tomato (Solanum lycopersicum L.) proteome via in silico approaches. Bulletin of Biotechnology 4 1 17–29.
IEEE Y. Küçükçobanoğlu ve L. Aktaş, “Functional and structural identification of iron-binding proteins on tomato (Solanum lycopersicum L.) proteome via in silico approaches”, Bull. Biotechnol., c. 4, sy. 1, ss. 17–29, 2023, doi: 10.51539/biotech.1262979.
ISNAD Küçükçobanoğlu, Yiğit - Aktaş, Lale. “Functional and Structural Identification of Iron-Binding Proteins on Tomato (Solanum Lycopersicum L.) Proteome via in Silico Approaches”. Bulletin of Biotechnology 4/1 (Haziran 2023), 17-29. https://doi.org/10.51539/biotech.1262979.
JAMA Küçükçobanoğlu Y, Aktaş L. Functional and structural identification of iron-binding proteins on tomato (Solanum lycopersicum L.) proteome via in silico approaches. Bull. Biotechnol. 2023;4:17–29.
MLA Küçükçobanoğlu, Yiğit ve Lale Aktaş. “Functional and Structural Identification of Iron-Binding Proteins on Tomato (Solanum Lycopersicum L.) Proteome via in Silico Approaches”. Bulletin of Biotechnology, c. 4, sy. 1, 2023, ss. 17-29, doi:10.51539/biotech.1262979.
Vancouver Küçükçobanoğlu Y, Aktaş L. Functional and structural identification of iron-binding proteins on tomato (Solanum lycopersicum L.) proteome via in silico approaches. Bull. Biotechnol. 2023;4(1):17-29.
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