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In Silico Analysis of nsSNPs of Carp TLR22 Gene Affecting its Binding Ability with Poly I:C

  • Vemulawada Chakrapani
  • Kiran D. Rasal
  • Sunil Kumar
  • Shibani D. Mohapatra
  • Jitendra K. Sundaray
  • Pallipuram Jayasankar
  • Hirak K. Barman
Original Research Article

Abstract

Immune response mediated by toll-like receptor 22 (TLR22), only found in teleost/amphibians, is triggered by double-stranded RNA binding to its LRR (leucine-rich repeats) ecto-domain. Accumulated evidences suggested that missense mutations in TLR genes affect its function. However, information on mutation linked pathogen recognition for TLR22 was lacking. The present study was commenced for predicting the effect of non-synonymous single-nucleotide polymorphisms (nsSNPs) on the pathogen recognizable LRR domain of TLR22 of farmed carp, Labeo rohita. The sequence-based algorithms (SIFT, PROVEAN and I-Mutant2.0) indicated that three SNPs (out of 27) such as p.L159F (rs76759876) and p.L529P (rs749355507) of LRR, and p.I836M (rs750758397) of intracellular motifs could potentially disrupt protein function. The 3D structure was generated using MODELLER 9.13 and further validated by SAVEs server. The simulated molecular docking of native TLR22 and mutants with poly I:C ligand indicated that mutations positioned at p.L159F and p.L529P of the LRR region affects the binding affinity significantly. This is the first kind of study of predicting nsSNPs of teleost TLR22 with disturbed ligand binding affinity with its extra-cellular LRR domain and thereby likely hindrance in subsequent signal transduction. This study serves as a guide for in vivo evaluation of impact of mutation on immune response mediated by teleost TLR22 gene.

Keywords

TLR22 nsSNPs Protein modelling Docking simulation 

Abbreviations

SIFT

Sorting intolerant from tolerant

SNP

Single-nucleotide polymorphism

nsSNPs

Non-synonymous single-nucleotide polymorphisms

AASs

Amino acid substitutions

PROVEAN

Protein variation effect analyzer

PDB

Protein data bank

SAVES

Structural analysis and verification server

Notes

Acknowledgements

This work was supported by a grant from the National Agricultural Science Fund (NASF), Indian Council of Agricultural Research, Union Ministry of Agriculture, Government of India. Thanks to the Director of this Institute for providing required facilities to carry out this research.

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Vemulawada Chakrapani
    • 1
  • Kiran D. Rasal
    • 1
  • Sunil Kumar
    • 2
  • Shibani D. Mohapatra
    • 1
  • Jitendra K. Sundaray
    • 1
  • Pallipuram Jayasankar
    • 1
  • Hirak K. Barman
    • 1
  1. 1.Fish Genetics and Biotechnology DivisionICAR, Central Institute of Freshwater AquacultureBhubaneswarIndia
  2. 2.ICAR, National Bureau of Agriculturally Important MicroorganismsMauIndia

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