An Integrated In Silico Approach for the Structural and Functional Exploration of Lipocalin 2 and its Functional Insights with Metalloproteinase 9 and Lipoprotein Receptor-Related Protein 2

Applied Biochemistry and Biotechnology

Volumn 176, Issue 3, 2015, Pages 712-729

  Ghosh, Mrinmoy ^a   Sodhi, Simrinder Singh ^a   Kim, Jeong Hyun ^a   Kim, Nam Eun ^a   Mongre, Raj Kumar ^a   Sharma, Neelesh ^a   Kim, Sung Woo ^b   Oh, Sung Jong ^a   Pulicherla, Krishna Kanth ^c   Jeong, Dong Kee ^a  

^a Jeju National University   (South Korea)

^b National Institute of Animal Science   (South Korea)

^c VIT UNIVERSITY   (India)

Author keywords

Docking; Lipocalin 2; Lipoprotein receptor related protein 2; Matrix metalloproteinase 9; Physicochemical characterization; Protein protein association

Indexed keywords

AMINO ACIDS; BINDING ENERGY; DOCKING; LIPOPROTEINS;

LIPOCALIN 2; LIPOPROTEIN RECEPTOR-RELATED PROTEINS; MATRIX METALLOPROTEINASE-9; PHYSICO-CHEMICAL CHARACTERIZATION; PROTEIN ASSOCIATIONS;

PROTEINS;

GELATINASE B; MEGALIN; NEUTROPHIL GELATINASE ASSOCIATED LIPOCALIN; LIGAND; LIPOCALIN;

ALPHA HELIX; AMINO ACID SUBSTITUTION; ANAS PLATYRHYNCHOS; ARTICLE; BETA TURN; BINDING AFFINITY; BUDGERIGAR; CELL MEMBRANE; CELL NUCLEUS; CELLULAR DISTRIBUTION; COLUMBA LIVIA; COMPUTER MODEL; COTURNIX COTURNIX; CYTOPLASM; ESCHERICHIA COLI; GALLUS GALLUS; HUMAN; HYDROGEN BOND; HYDROPHOBICITY; KLEBSIELLA PNEUMONIAE; MITOCHONDRION; MOLECULAR DOCKING; MOLECULAR DYNAMICS; MOLECULAR MODEL; MUS MUSCULUS; NONHUMAN; PHYLOGENETIC TREE; PHYSICAL CHEMISTRY; PROTEIN FUNCTION; PROTEIN PROTEIN INTERACTION; PROTEIN SECONDARY STRUCTURE; PROTEIN STRUCTURE; RATTUS NORVEGICUS; SEQUENCE ALIGNMENT; TAENIOPYGIA GUTTATA; TUMOR GROWTH; ANIMAL; CHEMISTRY; CHICKEN; COMPUTER SIMULATION; CONSERVED SEQUENCE; METABOLISM; PHYLOGENY; PROTEIN ANALYSIS; PROTEIN MOTIF; PROTEIN STABILITY; PROTEIN TERTIARY STRUCTURE; SEQUENCE HOMOLOGY;

GALLUS GALLUS;

AMINO ACID MOTIFS; ANIMALS; CHICKENS; COMPUTER SIMULATION; CONSERVED SEQUENCE; HUMANS; LIGANDS; LIPOCALINS; LOW DENSITY LIPOPROTEIN RECEPTOR-RELATED PROTEIN-2; MATRIX METALLOPROTEINASE 9; MOLECULAR DOCKING SIMULATION; MOLECULAR DYNAMICS SIMULATION; PHYLOGENY; PROTEIN INTERACTION MAPPING; PROTEIN STABILITY; PROTEIN STRUCTURE, TERTIARY; SEQUENCE ALIGNMENT; SEQUENCE HOMOLOGY, AMINO ACID;

EID: 84937812996     PISSN: 02732289     EISSN: 15590291     Source Type: Journal    
DOI: 10.1007/s12010-015-1606-2     Document Type: Article

References (78)

1. Flower, D. R., North, A. C., & Sansom, C. E. (2000). The lipocalin protein family: structural and sequence overview. Biochimica et Biophysica Acta, 1482, 9–24.
2. Akerstrom, B., & Logdeberg, L. (2006). In B. Akerstrom, N. Borregaard, D. A. Flower, & J. S. Salier (Eds.), Lipocalins (pp. 110–120). Georgetown: Landes Bioscience.
3. Ganfornina, M. D., Gutierrez, G., Bastiani, M., & Sanchez, D. (2000). A phylogenetic analysis of the lipocalin protein family. Molecular Biology Evolution, 17, 114–126.
4. Pervais, S., & Brew, K. (1985). Homology of beta-lactoglobulin, serum retinol-binding protein and protein HC. Science, 228, 335–337.
5. Igarashi, M., Nagata, A., Toh, H., Urade, H. I., & Hayaishi, M. (1992). Human brain prostaglandin D synthase has been evolutionarily differentiated from lipophilic-ligand carrier proteins. Proceedings of the National Academy of Sciences USA, 89, 5376–5380.
6. Flower, D. R., North, A. C. T., & Attwood, T. K. (1993). Structural and sequence relationships in the lipocalin and related proteins. Protein Sciences, 2, 753–761.
7. Flower, D. R. (1996). The lipocalin protein family: structure and function. Biochemistry Journal, 318, 1–14.
8. Bishop, R. E. (2000). The bacterial lipocalin. Biochimica et Biophysica Acta, 1482, 73–83.
9. Flo, T. H., Smith, K. D., Sato, S., Rodriguez, D. J., Holmes, M. A., Strong, R. K., Akira, S., & Aderem, A. (2004). Lipocalin 2 mediates an innate immune response to bacterial infection by sequestrating iron. Nature, 432, 917–921.
10. Goetz, D. H., Holmes, M. A., Borregaard, N., Bluhm, M. E., Raymond, K. N., & Strong, R. K. (2002). The neutrophil lipocalin NGAL is a bacteriostatic agent that interferes with siderophore-mediated iron acquisition. Molecular Cell, 10, 1033–1043.
11. Fluckinger, M., Haas, H., Merschak, P., Glasgow, B. J., & Redl, B. (2004). Human tear lipocalin exhibits antimicrobial activity by scavenging microbial siderophores. Antimicrobial Agents Chemotherapy, 48, 3367–3372.
12. Bratt, T. (2000). Lipocalins and cancer. Biochimica et Biophysica Acta, 1482, 318–326.
13. Rodvold, J. J., Mahadevan, N. R., & Zanetti, M. (2012). Lipocalin 2 in cancer: when good immunity goes bad. Cancer Letter, 316, 132–138.
14. Pauli, I., Timmers, L. F. S. M., Caceres, R. A., Botelho, M., Soares, P., & De Azevedo, W. F., Jr. (2008). In silico and in vitro: identifying new drugs. Current Drug Targets, 9, 1054–1061.
15. Yan, L., Borregaard, N., Kjeldsen, L., & Moses, M. A. (2001). The high molecular weight urinary matrix metalloproteinase (MMP) activity is a complex of gelatinase B/MMP-9 and neutrophil gelatinase-associated lipocalin (NGAL), modulation of MMP-9 activity by NGAL. Journal of Biological Chemistry, 276, 37258–37265.
16. Gupta, K., Shukla, M., Cowland, J. B., Malemud, C. J., & Haqqi, T. M. (2007). Neutrophil gelatinase-associated lipocalin is expressed in osteoarthritis and forms a complex with matrix metalloproteinase 9. Arthritis and Rheumatism, 56, 3326–3335.
17. Berger, T., Cheung, C.C., Elia, A.J., & Mak, T.W. (2010). Disruption of the Lcn2 gene in mice suppresses primary mammary tumor formation but does not decrease lung metastasis. Proceedings of the National Academy of Sciences, U.S.A., 1–6. doi:10.1073/pnas.1000101107.
18. Lin, C. W., Tseng, S. W., Yang, S. F., Ko, C. P., Lin, C. H., Wei, L. H., Chien, M. H., & Haieh, Y. S. (2012). Role of lipocalin 2 and its complex with matrix metalloproteinase-9 in oral cancer. Oral Diseases, 18, 734–740.
19. Stockwell, B. R. (2004). Exploring biology with small organic molecules. Nature, 432, 846–854.
20. Hall, S. E. (2006). Chemoproteomics-driven drug discovery: addressing high attrition rates. Drug Discovery Today, 11, 495–502.
21. Chue, J., & Smith, C. A. (2011). Sex determination and sexual differentiation in the avian model. FEBS Journal, 278, 1027–1034.
22. Saitou, N., & Nei, M. (1987). The neighbor-joining method: a new method for reconstructing phylogenetic trees. Molecular Biology Evolution, 4, 406–425.
23. Nei, M., & Zhang, J. (2006). Evolutionary distance: estimation. Encyclopaedia Life Science, 1–3. doi:10.1038/npg.els.0005108.
24. Guo, A. Y., Zhu, Q. H., Chen, X., & Luo, J. C. (2007). GSDS: a gene structure display server. Yi Chuan, 29, 1023–1026.
25. Gasteiger, E. (2005). Protein identification and analysis tools on the ExPASy server. In J. M. Walker (Ed.), The proteomics protocols handbook (pp. 571–607). Totowa: Humana.
26. Guruprasad, K., Reddy, B. V. B., & Pandit, M. W. (1990). Correlation between stability of a protein and its dipeptide composition: a novel approach for predicting in vivo stability of a protein from its primary sequence. Protein Engineering, 4, 155–161.
27. Ikai, A. J. (1980). Thermostability and aliphatic index of globular proteins. Journal of Biochemistry, 88, 1895–1898.
28. Sahay, A., & Shakya, M. (2010). In silico analysis and homology modelling of antioxidant proteins of spinach. Journal of Proteomics and Bioinformatics, 3, 148–154.
29. Buchan, D.W.A., Ward, S. M., Lobley, A. E., Nugent, T.C.O., Bryson, K., & Jones, D.T. (2010). Protein annotation and modelling servers at University College London. Nucleic Acids Research, 1–6. doi:10.1093/nar/gkq427.
30. Geourjon, C., & Deleage, G. (1995). SOPMA: significant improvements in protein secondary structure prediction by consensus prediction from multiple alignments. Computer Applications in the Biosciences, 11, 681–684.
31. Yu, C. S., Chen, Y. C., Lu, C. H., & Hwang, J. K. (2006). Predication of protein subcellular localization. Protein Structure Function and Bioinformatices, 64, 643–651.
32. Petersen, T. N., Brunak, S., Von Heijne, G., & Nielsen, H. (2011). SignalP 4.0: discriminating signal peptides from transmembrane regions. Nature Methods, 8, 785–786.
33. Eswar, N., Marti-Renom, M. A., Webb, B., Madhusudhan, M. S., Eramian, D., Shen, M., Pieper, U., & Sali, A. (2006). Comparative protein structure modeling with MODELLER. Current protocols in bioinformatics. Current Protocols in Bioinformatics, 15, 5.6.1–5.6.30.
34. Helen, B. M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T. N., Weissig, H., Shindyalov, I. N., & Bourne, P. E. (1997). The protein data bank. Nucleic Acids Research, 8, 235–242.
35. McGinnis, S., & Madden, L. T. (2004). BLAST: at the core of a powerful and diverse set of sequence analysis tools. Nucleic Acids Research, 32, W20–W25.
36. Laskowski, R. A., Rullmannn, J. A., MacArthur, M. W., Kaptein, R., & Thornton, J. M. (1996). AQUA and PROCHECK-NMR: programs for checking the quality of protein structures solved by NMR. Journal of Biomolecular NMR, 8, 477–486.
37. Shen, M. Y., & Sali, A. (2006). Statistical potential for assessment and prediction of protein structures. Protein Sciences, 15, 2507–2524.
38. Vriend, G. (1990). What if: a molecular modeling and drug design program. Journal of Molecular Graph, 8, 52–56.
39. Morris, G. M., Goodsell, D. S., Halliday, R. S., Huey, R., Hart, W. E., Belew, R. K., & Olson, A. J. (1998). Automated docking using a lamarckian genetic algorithm and empirical binding free energy. Function Journal of Computational Chemistry, 19, 1639–1662.
40. Hetenyi, C., & Spoel, V. D. (2002). Efficient docking of peptides to proteins without prior knowledge of the binding site. Protein Sciences, 11, 1729–1737.
41. Sousa, S. F., Fernandes, P. A., & Ramos, M. J. (2006). Protein-ligand docking: current status and future challenges. Proteins, 65, 15–26.
42. Huey, R., Morris, G. M., Olson, A. J., & Goodsell, D. S. (2007). A semi empirical free energy force field with charge-based desolvation. Journal of Computer Chemistry, 28, 145–152.
43. Dutta, A., Katarkar, A., & Chaudhuri, K. (2013). In-silico structural and functional characterization of a V. cholerae O395 hypothetical protein containing a PDZ1 and an uncommon protease domain. PLoS ONE, 8, 1–12.
44. Schuttelkopf, A. W., & Aalten, D. M. F. V. (2004). PRODRG: a tool for high-throughput crystallography of protein-ligand complexes. Acta Crystallography, 60, 1355–1363.
45. Berendsen, H. J. C., Van der Spoel, R. D., & Drunen, V. (1995). GROMACS: A message-passing parallel molecular dynamics implementation. Computer Physics Communications, 91, 43–56.
46. Spoel, V. D., Lindahl, E., Hess, B., Groenhof, G., Mark, A. E., & Berendsen, H. J. (2005). GROMACS: fast, flexible, and free. Journal of Computational Chemistry, 26, 1701–1718.
47. Fan, H., & Mark, A. E. (2003). Refinement of homology-based protein structures by molecular dynamics simulation techniques. Protein Sciences, 13, 211–220.
48. Newman, J., Peat, T. S., Richard, R., Kan, L., Swanson, P. E., Affholter, J. A., Holmes, I. H., Schindler, J. F., Unkefer, C. J., & Terwilliger, T. C. (1999). Haloalkane dehalogenase: structure of a Rhodococcus enzyme. Biochemistry, 38, 16105–16114.
49. George, P. D. C., & Nagasundaram, N. (2014). Molecular docking and molecular dynamics study on the effect of ERCC1 deleterious polymorphismsin ERCC1-XPF heterodimer. Applied Biochemistry and Biotechnology, 172, 1265–1281.
50. Morris, A. L., MacArthur, M. W., Hutchinson, E. G., & Thornton, J. M. (1992). Stereochemical quality of protein structure coordinates. Proteins, 12, 345–364.
51. Rokas, A., & Holland, P. W. (2000). Rare genomic changes as a tool for phylogenetics. Trends in Ecology & Evolution, 15, 454–459.
52. Krem, M. M., & Di Cera, E. (2001). Molecular markers of serine protease evolution. EMBO Journal, 20, 3036–3045.
53. Sanchez, D., Ganfornina, M. D., Gutierrez, G., Christine, A., & Marin, A. (2003). Exon-intron structure and evolution of the lipocalin gene family. Molecular Biology Evolution, 20, 775–783.
54. Singh, R., & Saha, M. (2003). Identifying structural motifs in proteins. Pacific Symposium on Biocomputing, 228–239.
55. North, A. C. T. (1989). Three-dimensional arrangement of conserved amino acid residues in a superfamily of specific ligand-binding proteins. International Journal of Biological Macromolecules, 11, 56–58.
56. Redl, B. (2000). Human tear lipocalin. Biochimica et Biophysica Acta, 1482, 241–248.
57. Mamathambika, B. S., & Bardwell, J. C. (2008). Disulfide linked protein folding pathways. Annual Review of Cell Development Biology, 28, 211–235.
58. Sivakumar, K., Balaji, S., & Gangaradhakrishnan. (2007). In-silico characterization of antifreeze proteins using computational tools and servers. Journal of Chemical Sciences, 119, 571–579.
59. Roy, S., Maheshwari, N., Chauhan, R., Sen, N. K., & Sharma, A. (2011). Structure prediction and functional characterization of secondary metabolite proteins of Ocimum. Bioinformation, 6, 315–319.
60. Prabu, G., Thirugnanasambantham, K., & Mandal, A. K. A. (2012). Structural and docking studies of a nucleoside diphosphate kinase 1 (CsNDPK1) from tea [Camellia sinensis (L.) O. Kuntze]. Applied Biochemistry and Biotechnology, 168, 1907–1916.
61. Johnson, K. A. (2009). The standard of perfection: thoughts about the laying hen model of ovarian cancer. Cancer Prevention Research, 2, 97–99.
62. Choi, S., & Myers, J. N. (2008). Molecular pathogenesis of oral squamous cell carcinoma: implications for therapy. Journal of Dental Research, 87, 14–32.
63. Choi, J. W., Ahn, S. E., Rengaraj, D., Seo, H. W., Lim, W., Song, G., & Han, J. Y. (2011). Matrix metalloproteinase 3 is a stromal marker for chicken ovarian cancer. Oncology Letters, 2, 1047–1051.
64. Hakim, A. A., Barry, C. P., Barnes, H. J., Anderson, K. E., Petitte, J., Whitaker, R., Lancaster, J. M., Wenham, R. M., & Carver, D. K. (2009). Ovarian adenocarcinomas in the laying hen and women share similar alterations in p53, ras and HER-2/neu. Cancer Prevention Research, 2, 114–121.
65. Lim, R., Ahmed, N., Borregaard, N., Riley, C., Wafai, R., Thompson, E. W., Quinn, M. A., & Rice, G. E. (2007). Neutrophil gelatinase-associated lipocalin (NGAL) an early-screening biomarker for ovarian cancer: NGAL is associated with epidermal growth factor-induced epithelio-mesenchymal transition. International Journal of Cancer, 120, 2426–2434.
66. Moniaux, N., Chakraborty, S., Yalniz, M., Gonzalez, J., Shostrom, V. K., Standop, J., Lele, S. M., Ouellette, M., et al. (2008). Early diagnosis of pancreatic cancer: neutrophil gelatinase-associated lipocalin as a marker of pancreatic intraepithelial neoplasia. Brazilian Journal of Cancer, 98, 1540–1547.
67. Sia, A. K., Allred, B. E., & Raymond, K. N. (2012). Customized siderocalins for host defense and beyond. Current Opinion in Chemical Biology, 17, 150–157.
68. Zheng, G. (1994). Organ distribution in rats of two members of the low-density lipoprotein receptor gene family, gp330 and LRP/alpha 2MR, and the receptor-associated protein (RAP). Journal of Histochemistry & Cytochemistry, 42, 531–542.
69. Yochem, J., & Greenwald, I. A. (1993). Proceedings of the National Academy of Sciences USA, 90, 4572–4576.
70. Yochem, J., Tuck, S., Greenwald, I., & Han, M. (1999). A gp330/megalin-related protein is required in the major epidermis of Caenorhabditis elegans for completion of molting. Development, 126, 597–606.
71. Hermann, M., Seif, F., Schneider, W. J., & Ivessa, N. E. (1997). Estrogen dependence of synthesis and secretion of apolipoprotein B-containing lipoproteins in the chicken hepatoma cell line, LMH-2A. Journal of Lipid Research, 38, 1308–1317.
72. Hvidberga, V., Jacobsena, C., Strongb, R. K., Cowlandc, J. B., Moestrupa, S. K., & Borregaardc, N. (2005). The endocytic receptor megalin binds the iron transporting neutrophil-gelatinase-associated lipocalin with high affinity and mediates its cellular uptake. FEBS Letters, 579, 773–777.
73. Plieschnig, A., Gensberger, E. T., Bajari, T. M., Schneider, W. J., & Hermanna, M. (2012). Renal LRP2 expression in man and chicken is estrogen-responsive. Gene, 508, 49–59.
74. Gerlt, J. A., Kreevoy, M. M., Cleland, W. W., & Frey, P. A. (1997). Understanding enzymic catalysis: the importance of short, strong hydrogen bonds. Chemistry and Biology, 4, 259–267.
75. Ruiz, D. G., & Gohlke, H. (2006). Targeting protein–protein interactions with small molecules: challenges and perspectives for computational binding epitope detection and ligand finding. Current Medicinal Chemistry, 13, 2607–2625.
76. Torti, S. V., & Torti, F. M. (2013). Iron and cancer: more ore to be mined. Nature Reviews Cancer, 13, 342–355.
77. Lipinski, C., & Hopkins, A. (2004). Navigating chemical space for biology and medicine. Nature, 432, 855–861.
78. Harris, C. J., & Stevens, A. P. (2006). Chemogenomics: structuring the drug discovery process to gene families. Drug Discovery Today, 11, 880–888.