Insilico structural analysis of parasporin 2 protein sequences of non-toxic bacillus thuringiensis
ABSTRACT
The unusual and remarkable property of parasporin 2 of non-insecticidal Bacillus thuringiensis is specifically recognizing and selectively targeting human leukemic cell lines. The 37-kDa inactive nascent protein is proteolytically cleaved to the 30-kDa active form that loses both the N-terminal and the C-terminal segments. Accumulated cytological and biochemical observations on parasporin-2 imply that the protein is a pore-forming toxin. To confirm the hypothesis, insilico analysis was performed using homology modeling. The resulting model of parasporin 2 protein is unusually elongated and mainly comprises long β-strands aligned with its long axis. It is similar to aerolysin-type β-pore-forming toxins, which strongly reinforce the pore-forming hypothesis. The molecule can be divided into three domains. Domain 1, comprising a small β-sheet sandwiched by short α-helices, is probably the target-binding module. Two other domains are both β-sandwiches and thought to be involved in oligomerization and pore formation. Domain 2 has a putative channel-forming β-hairpin characteristic of aerolysin-type toxins. The surface of the protein has an extensive track of exposed side chains of serine and threonine residues. The track might orient the molecule on the cell membrane when domain 1 binds to the target until oligomerization and pore formation are initiated. The β-hairpin has such a tight structure that it seems unlikely to reform as postulated in a recent model of pore formation developed for aerolysin-type toxins. Parasporin 2 (Accession no: BAD35170) protein sequence analysis indicated two different domains namely, aerolysin toxin and clostridium toxin domain based on different database searches (CDD and Pfam). It showed a close similarity with the available PDB template (PDB id: 2ZTB) of parasporin which has cytocidal activity against MOLT-4, HL60 and Jurkat cell lines. Based on the PSI Blast analysis, 3D structures of the domains were predicted by using Swiss model server. Accuracy of the prediction of 3D structure of different domains of parasporin protein was further validated by Ramachandran plot and PROCHECK (G-value). The structure is dominated by β-strands (67%, S1-12), most of which are remarkably extensive, running all or most of the longer axis of the molecule. This study helped to elucidate the 3D structure of parasporin 2 (Acc. No. BAD35170) which might enable to probe further its specific mechanism of action. Though the similarity is observed in the domain architecture, there is variation in the regions of the domains even among the same group of parasporin 2. Docking of this model structure and experimental structure with specific receptors of the cancer cells will facilitate to explore mechanism of parasporin 2 action and also provide information about its evolutionary relationship with toxic Cry proteins.
The unusual and remarkable property of parasporin 2 of non-insecticidal Bacillus thuringiensis is specifically recognizing and selectively targeting human leukemic cell lines. The 37-kDa inactive nascent protein is proteolytically cleaved to the 30-kDa active form that loses both the N-terminal and the C-terminal segments. Accumulated cytological and biochemical observations on parasporin-2 imply that the protein is a pore-forming toxin. To confirm the hypothesis, insilico analysis was performed using homology modeling. The resulting model of parasporin 2 protein is unusually elongated and mainly comprises long β-strands aligned with its long axis. It is similar to aerolysin-type β-pore-forming toxins, which strongly reinforce the pore-forming hypothesis. The molecule can be divided into three domains. Domain 1, comprising a small β-sheet sandwiched by short α-helices, is probably the target-binding module. Two other domains are both β-sandwiches and thought to be involved in oligomerization and pore formation. Domain 2 has a putative channel-forming β-hairpin characteristic of aerolysin-type toxins. The surface of the protein has an extensive track of exposed side chains of serine and threonine residues. The track might orient the molecule on the cell membrane when domain 1 binds to the target until oligomerization and pore formation are initiated. The β-hairpin has such a tight structure that it seems unlikely to reform as postulated in a recent model of pore formation developed for aerolysin-type toxins. Parasporin 2 (Accession no: BAD35170) protein sequence analysis indicated two different domains namely, aerolysin toxin and clostridium toxin domain based on different database searches (CDD and Pfam). It showed a close similarity with the available PDB template (PDB id: 2ZTB) of parasporin which has cytocidal activity against MOLT-4, HL60 and Jurkat cell lines. Based on the PSI Blast analysis, 3D structures of the domains were predicted by using Swiss model server. Accuracy of the prediction of 3D structure of different domains of parasporin protein was further validated by Ramachandran plot and PROCHECK (G-value). The structure is dominated by β-strands (67%, S1-12), most of which are remarkably extensive, running all or most of the longer axis of the molecule. This study helped to elucidate the 3D structure of parasporin 2 (Acc. No. BAD35170) which might enable to probe further its specific mechanism of action. Though the similarity is observed in the domain architecture, there is variation in the regions of the domains even among the same group of parasporin 2. Docking of this model structure and experimental structure with specific receptors of the cancer cells will facilitate to explore mechanism of parasporin 2 action and also provide information about its evolutionary relationship with toxic Cry proteins.
Cite this paper
nullMahalakshmi, A. and Shenbagarathai, R. (2010) Insilico structural analysis of parasporin 2 protein sequences of non-toxic bacillus thuringiensis. Journal of Biomedical Science and Engineering, 3, 415-421. doi: 10.4236/jbise.2010.34057.
nullMahalakshmi, A. and Shenbagarathai, R. (2010) Insilico structural analysis of parasporin 2 protein sequences of non-toxic bacillus thuringiensis. Journal of Biomedical Science and Engineering, 3, 415-421. doi: 10.4236/jbise.2010.34057.
References
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[6] Godzik, A. (2003) Fold recognition methods. Methods of Biochemical Analysis, 44, 525-546. [7] Kurowski, M.A., Bujnicki, J.M. (2003) GeneSilico protein structure prediction meta-server. Nucleic Acids Research, 31, 3305-3307. [8] Akiba, T., Abe, Y., Kitada, S., Kusaka, Y., Ito, A., Ichimatsu, T., Katayama, H., Akao, T., Higuchi, K., Mizuki, E., Ohba, M., Kanai, R. and Harata, K. (2009) Crystal structure of the parasporin-2 of Bacillus thuringiensis toxin that recognizes cancer cells. Journal of Molecular Biology, 386, 121-133. [9] Lundstrom, J., Rychlewski, L., Bujnicki, J.M. and Elofsson, A. (2001) Pcons: A neural-network-based consensus predictor that improves fold recognition. Protein Science, 10, 2354-2362. [10] Laskowski, R.A., MacArthur, M.W., Moss, D.S. and Thornton, J.M. (1993) PROCHECK: A program to check the stereochemical quality of protein structures. J Appl Cryst, 26, 283-291. [11] Hooft, R.W.W., Vriend, G., Sander, C. and Abola, E.E. 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(1994) CLUSTAL W: Improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Research, 22, 4673-4680. [23] Sasin, M. and Bujnicki, J.M. (2004) COLORADO3D, a web server for the visual analysis of protein structures. Nucleic Acids Research, 32, 586-589. [24] Guex, N. and Peitsch, M.C. (1997) SWISS-MODEL and the Swiss-PdbViewer: An environment for comparative protein modeling. Electrophoresis, 18, 2714-2723. [25] Altschul, S.F, Madden, T.L., Schäffer, A.A., Zhang, J., Zhang, Z., Miller, W. and Lipman, D.J. (1997) Gapped blast and PSI-blast: A new generation of protein database search programs. Nucleic Acids Research, 25(17), 3389-3402. [26] van Gunsteren, W.F., Billeter, S.R., Eising, A.A., Hünen- berger, P.H., Krüger, P., Mark, A.E., Scott, W.R.P. and Tironi, I.G. (1996) Biomolecular simulation. The GRO- MOS96 Manual and User Guide, Zürich, Groningen. [27] Hooft, R.W.W., Vriend, G., Sander, C. and Abola, E.E. (1996) Errors in protein structures. Nature, 381, 272-272. [28] Eisenberg, D., Lüthy, R. and Bowie, J.U. (1997) VERIFY3D: Assessment of protein models with three-dimensional profiles. Methods Enzymol, 277, 396-404.
[1] Mizuki, E., Ohba, M., Akao, T., Yamashita, S., Saitoh, H. and Park, Y.S. (1999) Unique activity associated with non-insecticidal Bacillus thuringiensis parasporal inclusions: In vitro cell-killing action on human cancer cells. Journal of Applied Microbiology, 86, 477-86. [2] Katayama, H., Yokota, H., Akao, T., Nakamura, O., Ohba, M., Mekada, E. and Mizuki, E. (2005) Parasporin-1, a novel cytotoxic protein to human cells from non-insecticidal parasporal inclusions of Bacillus thuringiensis. Biochemistry, 137, 17-25. [3] Abe, Y., Shimada, H. and Kitada, S. (2008) Raft-targeting and oligomerization of parasporin-2, a Bacillus thuringiensis crystal protein with Anti-Tumour activity. Biochemistry, 143(2), 269-275. [4] Murray, D. and Honig, B. (2002) Electrostatic control of the membrane targeting of C2 domains. Molecular Cell, 9, 145-154. [5] Copley, R.R., Doerks, T., Letunic, I. and Bork, P. (2002) Protein domain analysis in the era of complete genomes. FEBS Letters, 20, 129-134. [6] Godzik, A. (2003) Fold recognition methods. Methods of Biochemical Analysis, 44, 525-546. [7] Kurowski, M.A., Bujnicki, J.M. (2003) GeneSilico protein structure prediction meta-server. Nucleic Acids Research, 31, 3305-3307. [8] Akiba, T., Abe, Y., Kitada, S., Kusaka, Y., Ito, A., Ichimatsu, T., Katayama, H., Akao, T., Higuchi, K., Mizuki, E., Ohba, M., Kanai, R. and Harata, K. (2009) Crystal structure of the parasporin-2 of Bacillus thuringiensis toxin that recognizes cancer cells. Journal of Molecular Biology, 386, 121-133. [9] Lundstrom, J., Rychlewski, L., Bujnicki, J.M. and Elofsson, A. (2001) Pcons: A neural-network-based consensus predictor that improves fold recognition. Protein Science, 10, 2354-2362. [10] Laskowski, R.A., MacArthur, M.W., Moss, D.S. and Thornton, J.M. (1993) PROCHECK: A program to check the stereochemical quality of protein structures. J Appl Cryst, 26, 283-291. [11] Hooft, R.W.W., Vriend, G., Sander, C. and Abola, E.E. (1996) Errors in protein structures. Nature, 381, 272-272. [12] Sippl, J. (1993) Recognition of errors in three dimensional structures of proteins. Proteins, 17, 355-362. [13] Lüthy, R., Bowie, J.U. and Eisenberg, D. (1992) Assessment of protein models with three-dimensional profiles. Nature, 5, 83-5. [14] Brenner, S.E. (2001) A tour of structural genomics. Nature Reviews Genetics, 2, 801-809. [15] Berman, H.M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T.N., Weissig, H., Shindyalov, I.N. and Bourne, P.E. (2000) The protein data bank. Nucleic Acids Research, 28, 235-242. [16] Andreeva, A., Howorth, D., Brenner, S.E., Hubbard, T.J., Chothia, C. and Murzin A.G. (2004) SCOP database in 2004: Refinements integrate structure and sequence family data. Nucleic Acids Research, 32, 226-229. [17] Altschul, S.F., Madden, T.L., Schaffer, A.A., Zhang, J., Zhang, Z., Miller, W. and Lipman, D.J. (1997) Gapped BLAST and PSI-BLAST: A new generation of protein database search programs. Nucleic Acids Research, 25, 3389-3402. [18] Shi, J., Blundell, T.L. and Mizuguchi, K. (2001) FUGUE: sequence-structure homology recognition using environment- specific substitution tables and structure-dependent gap penalties. Journal of Molecular Biology, 29, 243-57. [19] Kelley, L.A., MacCallum, R.M., Sternberg, M.J.E. (2000) Enhanced genome annotation using structural profiles in the program 3D-PSSM. Journal of Molecular Biology, 299, 499-520. [20] Karplus, K., Karchin, R., Draper, J., Casper, J., Mandel- Gutfreund, Y., Diekhans, M. and Hughey, R. (2003) Combining local-structure, fold-recognition, and new fold methods for protein structure prediction. Proteins, 53, 491-496. [21] Kurowski, M.A. and Bujnicki, J.M. (2003) GeneSilico protein structure prediction meta-server. Nucleic Acids Research, 31, 3305-3307. [22] Thompson, J.D., Higgins, D.G. and Gibson, T.J. (1994) CLUSTAL W: Improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Research, 22, 4673-4680. [23] Sasin, M. and Bujnicki, J.M. (2004) COLORADO3D, a web server for the visual analysis of protein structures. Nucleic Acids Research, 32, 586-589. [24] Guex, N. and Peitsch, M.C. (1997) SWISS-MODEL and the Swiss-PdbViewer: An environment for comparative protein modeling. Electrophoresis, 18, 2714-2723. [25] Altschul, S.F, Madden, T.L., Schäffer, A.A., Zhang, J., Zhang, Z., Miller, W. and Lipman, D.J. (1997) Gapped blast and PSI-blast: A new generation of protein database search programs. Nucleic Acids Research, 25(17), 3389-3402. [26] van Gunsteren, W.F., Billeter, S.R., Eising, A.A., Hünen- berger, P.H., Krüger, P., Mark, A.E., Scott, W.R.P. and Tironi, I.G. (1996) Biomolecular simulation. The GRO- MOS96 Manual and User Guide, Zürich, Groningen. [27] Hooft, R.W.W., Vriend, G., Sander, C. and Abola, E.E. (1996) Errors in protein structures. Nature, 381, 272-272. [28] Eisenberg, D., Lüthy, R. and Bowie, J.U. (1997) VERIFY3D: Assessment of protein models with three-dimensional profiles. Methods Enzymol, 277, 396-404.