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Research & Reviews: A Journal of Bioinformatics

Insilico Study Showing the Chemical Properties and Interaction between Auxin-Binding Protein and Auxin-Responsive GH3-8 Protein in Rice

  1. Pranati Swain
  2. Lambodar Behera

Abstract

Auxin plays an important role in the plant growth. There are different auxin binding and auxin responsive proteins which bind and interact with auxin hormone and helps for plant development. Two different rice proteins considered for study, one protein binding to auxin and another is the auxin responsive protein. The Nuclear magnetic resonance (NMR) crystallographic structures of both the proteins are not available at Protein Data Bank (PDB). So the tertiary structures were generated by using homology modeling method. Model visualization was performed by using PyMol and discovery studio visualiser which showed the helix, sheets and turns. The model evaluation, backbone conformation and optimization were done by using PROCHECK Saves server, Atomic Non-Local Environment Assessment (ANOLEA). The Risk Management Services (RMS) values, potential energy after and before the energy minimisation was studied by using Yet Another Scientific Artificial Reality Application (YASARA) tool and SWISS-PDB viewer. The protein-protein interaction was studied by using HEX server. The protein models which were generated showed similarity with zea-mays and vititsvinifera, respectively. Keywords: Auxin-binding protein, Auxin-responsive GH3-8 protein, homology modeling, sterio-chemical evaluation

References (19)

  1. Khakipour N., Khavazi K., Mojallali K., et al. Production of Auxin Hormone by Fluorescent Pseudomonads. Am-Euras. J. Agric. & Environ. Sci. 2008; 4(6): 687 – 692p.
  2. Elisabeth J. Chapman, Estelle M. Mechanism of Auxin -Regulated Gene Expression in Plants. Division of Biology, University of California, San Diego, La Jolla, California, 2009, 92093-0116.
  3. Magnus V., Kojic -prodic B., Auxin Structure and Activity .Verlag Ferdinand Berger & Söhne Ges.m.b.H. 1999, Available from: www.biologiezentrum.at.
  4. Altschul SF., Gish W., Miller W., et al. Basic Local Alignment Search Tool. J. Mol. Biol. 1990; 215: 403–410p.
  5. Thompson JD ., Higgins DG., Gibson TJ. CLUSTAL W: Improving the Sensitivity of Progressive Multiple Sequence Alignment through Sequence Weighting, Position-specific Gap Penalties and Weight Matrix Choice . Nucl. Acids Res . 1994; 22(22): 4673–4680p.
  6. Thompson JD., Higgins DH., Gibson TJ. CLUSTAL W: Improving the Sensitivity of Progressive Multiple Sequence Alignment through Sequence Weighting, Position-specific Gap Penalties and Weight Matrix Choice. Nucl. Acids Res . 1994; 22(22): 4673–4680p.
  7. Pais FSM., Ruy Pde C., Oliveira G., et al. Assessing the Efficiency Of multiple Sequence Alignment Programs. Algorithms Mol Biol. 2014 Mar; 69(1): 4p. doi:10.1186/1748-7188-9-4.
  8. Singh S., Kumar GS., Nishchal A., et al. Comparative Modeling Study of the 3 -D Structure of Small Delta Antigen Protein of Hepatitis Delta Virus. 2009; JCSB 3(1): 001–004. doi:10.4172/jcsb.1000047
  9. Christie SA D., Shanmugam S., Phylogenetic Analysis and Homology Modelling of Laccase Gene of Fusarium Oxysporum lcc2. IJPSR; 3(12): 571–582p.
  10. 10- Roly ZY., Hasan SMN., Ferdaus KMKB., et al. Predicted Structure Model of Bungarotoxin from Bungarus Fasciatus Snake. Bioinformation 2014; 10(10): 617– 622p.
  11. Rambabu R., Peri SR., Allam AR., Computational Analysis and Function Prediction of a Hypothetical Protein 1RW0. Int. J. Comput. Bioinfo. In Silico Model. 2012; 1(5): 58–62p. ISSN: 2320 - 0634.
  12. Kumar S., Nath O., Govil S., et al. Computational 3D Structure Prediction, Evaluation and Analysis of Pyruvate Dehydrogenase an Effective Target for Filarial Infection by Brugiapahangi Using Research & Reviews: A Journal of Bioinformatics Volume 1, Issue 3 ISSN: 2393-8722 (online) RRJoBI (2014) 24-30 © STM Journals 2014. All Rights Reserved Page 30 Homology Modeling Approach, IJPSDR 2014; 6(2): 120–123p.
  13. Singh B., Gupta A., Potukuchi SM. Comparative Modeling And analysis of 3- D Structure of Hsp 70, In Cancer Irroratus. Biol. Forum — Int. J. 2009; 1(2): 1–4p.
  14. Laskowski R A., Mac Arthur M W., Moss D S., et al. PROCHECK a Program to Check the Stereochemical Quality of Protein Structures., J. App. Cryst. 1993; 26: 283–291p.
  15. Rohini K., Srikumar PS. Insights from the Docking and Molecular Dynamics Simulation of the Phosphopantetheinyl Transferase (PptT) Structural Model from Mycobacterium Tuberculosis. Bioinformation 2013; 9(13): 685–689p.
  16. Gupta S., Saxena VL., Singh S., Homology Modeling and Docking Studies of Neuraminidase Protein of Influenza a Virus (H1N1) Virus with Select Ligand – A Computer Aided Structure Based Drug Design. IJPSI 2013; ISSN (Online): 2319– 6718p.
  17. Yaraguppi DA., Udapudi BB., Patil , et al. In- Silico Analysis for Predicting Protein Ligand Interaction for Snake Venom Protein, J. Adv. Bioinfo. Appl. Res. 2012; 3(3): ISSN 0976 -2604. Online ISSN 2278–6007.
  18. Fahham N., Ghahremani MH., Sardari S., et al. Simulation of Different Truncated p16INK4a Forms and in Silico Study of Interaction with Cdk4, Soroush Sardari, Department of Medical Biotechnology, Biotechnology Research Center, Pasteur Institute, Tehran, Iran 13164, Cancer Inform. 2009; 7: 1–11p.
  19. S. Namasivayam KR., Muthukumaran J. Prediction of Three Dimensional Model and Active Site Analysis of Inducible Serine Protease Inhibitor -2 (ISPI -2) in Galleria Mellonella. JCSB; 2008; 1.

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