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parth vavadia

  1. 1. By Komal Vavadiya TY BIOTECHNOLOGY
  2. 2. In- silico prediction of vp40 matrix protein of Ebola virus through homology modelling  Abstract  Ebola virus (EBOV), formerly designated Zaire Ebola virus is one of five known viruses within the genus Ebolavirus. Four of the five known Ebola viruses, including EBOV, cause a severe and often fatal hemorrhagic fever in humans and other mammals , known as Ebola virus disease.Ebola virus has caused the majority of human deaths from EVD, and is the cause of the 2013–2015.The negative-sense RNA that encodes seven viral proteins out of which Matrix protein Vp40 of Ebola virus plays a vital role in virus assembly and budding. The 3D structure of this protein is not available yet. So, I have done homology modeling which was performed to generate good quality models. The assessment of generated three dimensional structure against structure verification tools PHYRE, PSIPRED, PROCHECK, showed that model generated by Swiss Model was more acceptable to that by GENO 3D. The predicted model can be used in structure based drug designing and vaccine development. Keywords: Vp40 matrix protein , PHYRE ,PROCHECK, GENO -3D , PSIPRED
  3. 3. Introduction :-  Ebola is xoonotic virus.  It is negatively charge single stranded RNA  It causes the hazardous fatal effect like hemorrhagic fever  It originates from bats and fruit bats . Group Negative strand ss RNA Family Filoviridae Oder Mononegavirale genus Ebola virus
  4. 4. Figure 1 structure of Ebola virus
  5. 5. Material and methods:-  1) Retrieval of target sequence:-  The amino acid sequence of the matrix protein of Ebola virus was obtained from the sequence database of NCBI (http://www.ncbi.nlm.nih.gov/protein/Vp40s protein)  >gi|465460|sp|Q05128.1|VP40_EBOZM RecName: Full=Matrix protein VP40; Alt Name: Full=Membrane-associated proteinVP40MRRVILPTAPPEYMEAIYPVRSNSTIARGGNSNTGFLTPESVNGDTPSNPLRPIA DDTIDHASHTPGSVSSAFILEAMVNVISGPKVLMKQIPIWLPLGVADQKTYSFDSTTAAIMLA SYTITHFGKATNPLVRVNRLGPGIPDHPLRLLRIGNQAFLQEFVLPPVQLPQYFTFDLTALKLI TQPLPAATWTDDTPTGSNGALRPGISFHPKLRPILLPNKSGKKGNSADLTSPEKIQAIMTSLQ DFKIVPIDPTKNIMGIEVPETLVHKLTGKKVTSKNGQPIIPVLLPKYIGLDPVAPGDLTMVITQ DCDTCHSPASLPAVIEK.
  6. 6. Conti…….  2) Physico-chemical characterization:-  The values of theoretical isoelectric point (pI), molecular weight, total number of positive and negative, using the Expasy’s ProtParam server (http://us.expasy.org/tools/protparam.html). residues, extinction coefficient , instability index, aliphatic index and grand average hydropathy (GRAVY) were computed. For Physico-chemical characterization The results were shown in Table 1.
  7. 7. Continue………….. Sr. no Property Value 1 No. of amino acid 288 2 Molecular weight 32520.8 3 Theoritical PI 8.40 4 Total no. of negative charge residues (asp+glu) 37 5 Total no. of positively charge residues (arg+lys) 40 6 Extinction coefficient 28460 7 Extinction coefficient 27960 8 Instability index 52.08 9 Aliphatic index 78.26 10 Grand average of hydropathicity -0.607 Table 1-Parameters computed using Expasy’s ProtParam tool
  8. 8.  3) Secondary structure prediction:-  I have predicted secondary structure of Ebola virus by using Pspired software (http://www.sbg.bio.ic.ac.uk/pspired) software where the FASTA format of the sequence was given as input. Figure -2 secondary structure of Ebola virus
  9. 9. 4. Model building and quality assessment:-  The modeling of the three dimensional structure of the protein was done using homology modelling programs Geno 3D.  The overall stereochemical property of the protein was assessed by Ramchandran plot analysis.  The evaluation of structure models obtained from the software tools was performed by using PROCHECK.
  10. 10. 3D structure of Ebola virus by using Geno-3D
  11. 11. Figure 3 results of PROCHECK of Vp40 protein
  12. 12. Figure:-5 Ramachandran plot of Matrix protein of Ebola virus generated using Procheck software
  13. 13. Residue in most favored region 163 72.1% Residue in additional allowed region 57 25.2% Residue in generously allowed region 5 2.2% Residue in disallowed region 1 0.4% Total no of residue is 272
  14. 14. Conclusion:-  On the basis of various structural and physiochemical parameters assessment, it can be concluded that the predicted three dimensional structure of matrix protein of Ebola virus is stable.  Since no effective therapeutic or vaccine is available for Ebola virus structure information of this model can be effectively used and can be further implemented in future drug designing.
  15. 15. References:- 1. Arnold K, Bordoli L, Kopp J, Schwede T (2006) The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling. Bioinformatics 22: 195-201. 2. Combet C, Jambon M, Deleage G, Geourjon C (2002) Geno3D: Automatic comparative molecular modelling of protein. Bioinformatics 18: 213-214. 3. Gasteiger E (2005) Protein Identifi cation and Analysis Tools on the ExPASy Server. In: John M. Walker, The Proteomics Protocols Handbook, Humana Press 571-607. 4. Geourjon C, Deléage G (1995) SOPMA: significant improvements in protein secondary structure prediction by consensus prediction from multiple alignments. Computer Application Bioscience 11: 681-684. 5. Ikai AJ (1980) Thermo stability and aliphatic index of globular proteins. J Biochem 88: 1895- 1898. 6. Laskowski RA, Rullmannn JA, MacArthur MW, Kaptein R, Thornton JM (1996) AQUA and PROCHECK-NMR: programs for checking the quality of protein structures solved by NMR. J Biomol NMR 8: 477-486.
  16. 16. 7. Ramamchandran GN, Ramakrishnan C, Sasisekhran V (1963) Stereochemistry of polypeptide chain configurations. J Mo l Biol 7: 95-99. 8. Kyte J, Doolottle RF (1982) A simple method for displaying the hydropathicity character of a protein. J Mol Biol 157: 105- 132. 9. Gill SC, Von Hippel PH (1989) Extinction coefficient. Anal Biochem 182: 319-328. 10.Guruprasad K, Reddy BVP, Pandit MW (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. Prot Eng 4: 155-164

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