Information Technology Reference
In-Depth Information
accuracy till date. However, it is interesting to discuss that, all our predictions may
take a long time, while a cell takes only a few micro-seconds to fold a primary
sequence into fully functional global native minima structure. Hence, further
research to improve the algorithms is still needed to make the prediction close to
native state or in other words close to fold adopted by the nature.
Acknowledgments Minu Kesheri is thankful to University Grant Commission, Govt. of India,
New Delhi, for providing financial assistance in the form of research fellowship. Swarna Kanchan
is thankful to University Grant Commission, Govt. of India, New Delhi for providing the financial
support in the form of the Basic Science Research Fellowship under University Grant Commission
(New Delhi) Special Assistance Programme to Department of Biological Sciences, Birla Institute
of Technology and Science, Pilani, India.
References
Altschul, S. F., Madden, T. L., Sch
ffer, A. A., Zhang, J., Zhang, Z., Miller, W., et al. (1997).
Gapped BLAST and PSI-BLAST: A new generation of protein database search programs.
Nucleic Acids Research, 25(17), 3389
ä
3402.
Arnold, K., Kiefer, F., Kopp, J., Battey, J. N., Podvinec, M., Westbrook, J. D., et al. (2009). The
protein model portal. Journal of Structural and Functional Genomics, 10(1), 1 - 8.
Baker, D., & Sali, A. (2001). Protein structure prediction and structural genomics. Science, 294
(5540), 93 - 96.
Bates, P. A., Kelley, L. A., MacCallum, R. M., & Sternberg, M. J. E. (2001). Enhancement of
protein modeling by human intervention in applying the automatic programs 3D-JIGSAW and
3D-PSSM. Proteins: Structure, Function, and Bioinformatics, 45(5), 39 - 46.
Benkert, P., K ü nzli, M., & Schwede, T. (2009). QMEAN server for protein model quality
estimation. Nucleic Acids Research, 37(Web Server issue), W510
-
W514.
Berman, H. M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T. N., Weissig, H., et al. (2000). The
protein data bank. Nucleic Acids Research, 28(1), 235
-
242.
Bettella, F., Rasinski, D., & Knapp, E. W. (2012). Protein secondary structure prediction with
SPARROW. Journal of Chemical Information and Modeling, 52(2), 45
-
56.
Bhattacharya, D., & Cheng, J. (2013). 3Dre ne: Consistent protein structure re nement by
optimizing hydrogen bonding network and atomic-level energy minimization. Proteins:
Structure, Function, and Bioinformatics, 81(1), 119
-
131.
Boissel, J. P., Lee, W. R., Presnell, S. R., Cohen, F. E., & Bunn, H. F. (1993). Erythropoietin
structure-function relationships. Mutant proteins that test a model of tertiary structure. Journal
of Biological Chemistry, 268(21), 15983 - 15993.
Bowie, J., Luthy, R., & Eisenberg, D. (1991). A method to identify protein sequences that fold into
a known three-dimensional structure. Science, 253(5016), 164 - 170.
Bradley, P., Misura, K. M. S., & Baker, D. (2005). Toward high-resolution de novo structure
prediction for small proteins. Science, 309(5742), 1868 - 1871.
Chandonia, J.- M., & Karplus, M. (1995). Neural networks for secondary structure and structural
class predictions. Protein Science, 4(2), 275 - 285.
Cheng, J., Li, J., Wang, Z., Eickholt, J., & Deng, X. (2012). The MULTICOM toolbox for protein
structure prediction. BMC Bioinformatics, 13, 65.
Cheng, J., Randall, A. Z., Sweredoski, M. J., & Baldi, P. (2005). SCRATCH: A protein structure
and structural feature prediction server. Nucleic Acids Research, 33(Web Server issue),
W72
-
W76.
-
Search WWH ::




Custom Search