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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

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Abstract

Recent evidence demonstrated that Lipocalin 2 (LCN2) is garnering interest from a wide spectrum as biomarker. Here, we present an in silico characterization of LCN2 belonging to prominent organisms focusing for their physicochemical and structural differences. We found significant variations in physicochemical properties between organisms and low sequence similarity based on their amino acid properties alone. However, we identified three main structurally distinct motif regions that are conserved among all variants. Further investigation was carried out to understand the functional insights of LCN2. We selected LCN2 sequence from Gallus gallus as an input query to identify unique scoring-framework based on computational tools and confidence scores of various putative associations. Among all ten proteins associated with LCN2; highest confidence of prediction were seen for the associations between LCN2 and metalloproteinase 9 (MMP9) and lipoprotein receptor-related protein 2 (LRP2) which play vital roles in tumor growth and iron transportation, respectively. We attempted to determine binding affinities of LCN2 with MMP9 and LRP2 through molecular modeling and docking. Selected docked models were examined for complex stability by GROMACS. Alteration of binding affinity between LCN2 with MMP9 and LRP2 proteins that we found in this study may provide new direction for future therapeutic targets.

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Acknowledgments

This study was supported by a grant from Golden Seed Project (No. PJ009927), Republic of Korea; hence the authors are thankful to this organization.

Conflict of Interests

The authors declare no conflict of interests.

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Authors and Affiliations

  1. Department of Animal Biotechnology, Faculty of Biotechnology, Jeju National University, Jeju Do, 690-756, Republic of Korea

    Mrinmoy Ghosh, Simrinder Singh Sodhi, Jeong Hyun Kim, Nam Eun Kim, Raj Kumar Mongre, Neelesh Sharma, Sung Jong Oh & Dong Kee Jeong

  2. Animal Genetic Resources Station, National Institute of Animal Science, Rural Development Administration, Namwon, Republic of Korea

    Sung-Woo Kim

  3. Centre for Bioseperation Technology, VIT University, Vellore, 632014, Tamil Nadu, India

    Krishna Kanth Pulicherla

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  1. Mrinmoy Ghosh
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  2. Simrinder Singh Sodhi
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Correspondence to Dong Kee Jeong.

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Supplementary Fig. 1

The distribution of Exon and upstream regions in the LCN2 from selected organisms. (JPEG 160 kb)

Supplementary Fig. 2

The Ramachandran Plot for quality check of the LCN2 model of Gallus gallus. Regions A, B, L as most favored (89.9 %), additional allowed regions are a, b, l, p (7.2 %), and residuals are in the disallowed regions 2.2 %. The R factor finds less than 16 %. (JPEG 144 kb)

Supplementary Fig. 3

Modeled LRP2 protein of Gallus gallus using modeler. (JPEG 94 kb)

Supplementary Fig. 4

Ramchandran plot showing different regions of modeled LRP2 sourced from Gallus gallus. (JPEG 139 kb)

Supplementary Fig. 5

Modeled MMP-9 protein of Gallus gallus using modeler. (JPEG 106 kb)

Supplementary Fig. 6

Ramchandran plot showing different regions of modeled MMP-8 sourced from Gallus gallus. (JPEG 160 kb)

Supplementary Table 1

The percentage of amino acid residues in LCN2 of the selected organisms were annotated using CLC WorkBench tool. (DOCX 22 kb)

Supplementary Table 2

In silico predication of the LCN2 secondary structural. (DOCX 20 kb)

Supplementary Table 3

Association of functional protein partners of LCN2 with their score summary calculated through STRING network tool (DOCX 16 kb)

Supplementary Table 4

QMEAN-4 global scores for homologous model of LCN2, LRP2 and MMP9 from Gallus gallus. (DOCX 16 kb)

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Ghosh, M., Sodhi, S.S., Kim, J.H. et al. 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. Appl Biochem Biotechnol 176, 712–729 (2015). https://doi.org/10.1007/s12010-015-1606-2

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