Alpha-helical topology and tertiary structure prediction in globular proteins

Proceedings of the IEEE Conference on Decision and Control

Volumn , Issue , 2007, Pages 4551-4556

  McAllister, Scott R ^c   Floudas, Christodoulos A ^a,b  

^a PRINCETON UNIVERSITY   (United States)

^b Princeton University   (United States)

^c NONE

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CONFORMATIONS; CONSTRAINT THEORY; GLOBAL OPTIMIZATION; MICROSTRUCTURE; PROBLEM SOLVING; PROTEINS;

ALPHA-HELICAL TOPOLOGY; ATOMISTIC-LEVEL ENERGY; DISTANCE CONSTRAINTS; TERTIARY STRUCTURE;

TOPOLOGY;

EID: 62749087751     PISSN: 07431546     EISSN: 25762370     Source Type: Conference Proceeding    
DOI: 10.1109/CDC.2007.4434759     Document Type: Conference Paper

References (35)

1. H. M. Berman, J. Westbrook, Z. Feng, G. Gilliland, T. N. Bhat, H. Weissig, I. N. Shindyalov, and P. E. Bourne, "The protein data bank," Nue Acids Res, vol. 28, pp. 235-242, 2000.
2. C. Zhang, J. T. Hou, and S. H. Kim, "Fold prediction of helical proteins using torsion angle dynamics and predicted restraints," Proc. Nat. Acad. Sci. USA, vol. 99, pp. 3581-3585, 2002.
3. C. S. Adjiman, S. Dallwig, C. A. Floudas, and A. Neumaier, "A global optimization method for general twice-differentiable NLPs. i. theoretical advances," Comp. Chem. Eng., vol. 22, pp. 1137-1158, 1998b.
4. C. S. Adjiman, I. P. Androulakis, and C. A. Floudas, "A global optimization method for general twice-differentiable NLPs. ii. implementation and computational results," Comp. Chem. Eng., vol. 22, pp. 1159-1179, 1998a.
5. J. L. Klepeis and C. A. Floudas, "Astro-fold: A combinatorial and global optimization framework for ab initio prediction of three-dimensional structures of proteins from the amino acid sequence," Biophysical Journal, vol. 85, pp. 2119-2146, 2003b.
6. A. R. Ortiz, A. Kolinski, and J. Skolnick, "Fold assembly of small proteins using Monte Carlo simulations driven by restraints derived from multiple sequence alignments," J. Mol. Bio., vol. 277, pp. 419-448, 1998.
7. E. S. Huang, R. Samudrala, and J. W. Ponder, "Ab initio fold prediction of small helical proteins using distance geometry and knowledge-based scoring functions," J. Mol. Bio., vol. 290, pp. 267-281, 1999.
8. B. A. Reva, A. V. Finkelstein, and J. Skolnick, "What is the probability of a chance prediction of a protein structure with an rmsd of 6 angstrom?" Fold Des, vol. 3, pp. 141-147, 1998.
9. B. Fain and M. Levitt, "A novel method for sampling alpha-helical protein backbones," J. Mol. Bio., vol. 305, pp. 191-201, 2001.
10. C. A. Floudas, "Research challenges, opportunities and synergism in systems engineering and computational biology," AIChE J, vol. 51, pp. 1872-1884, 2005.
11. C. A. Floudas, H. K. Fung, S. R. McAllister, M. Mönnigmann, and R. Rajgaria, "Advances in protein structure prediction and de novo protein design: A review," Chem Eng Sci, vol. 61, pp. 966-988, 2006.
12. C. A. Floudas, "Computational methods in protein structure prediction," Biotechnol. Bioeng., 2007, in press.
13. B. Rost and C. Sander, "Prediction of protein structure at better than 70% accuracy," J. Mol. Bio., vol. 232, pp. 584-599, 1993.
14. D. T. Jones, "Protein secondary structure prediction based on position-specific scoring matrices," J. Mol. Bio., vol. 292, pp. 195-202, 1999.
15. B. Rost, "Review: Protein secondary structure prediction continues to rise," J Struct Biol, vol. 134, pp. 204-218, 2001.
16. J. L. Klepeis and C. A. Floudas, "Ab initio prediction of helical segments in polypeptides," J. Comput. Chem., vol. 23, pp. 245-266, 2002.
17. S. R. McAllister, B. E. Mickus, J. L. Klepeis, and C. A. Floudas, "A novel approach for alpha-helical topology prediction in globular proteins: Generation of interhelical restraints," Prot Struct Fund Bioinf, vol. 65, pp. 930-952, 2006.
18. C. A. Orengo, A. D. Michie, S. Jones, D. T. Jones, M. B. Swindells, and J. M. Thornton, "CATH - a hierarchic classification of protein domain structures," Structure, vol. 5, pp. 1093-1108, 1997.
19. U. Hobohm and C. Sander, "Enlarged representative set of protein structures," Prot. Sci., vol. 3, pp. 522-524, 1994.
20. W. L. DeLano, The PyMol Molecular Graphics System. San Carlos, CA USA: DeLano Scientific, 2002, http://www.pymol.org.
21. C. A. Floudas, Nonlinear and Mixed-integer Optimization: Fundamentals and Applications. Oxford University Press, 1995.
22. J. L. Klepeis, M. J. Pieja, and C. A. Floudas, "Hybrid global optimization algorithms for protein structure prediction: Alternating hybrids," Biophysical Journal, vol. 84, pp. 869-882, 2003a.
23. C. S. Adjiman, I. P. Androulakis, C. D. Maranas, and C. A. Floudas, "A global optimization method, aBB, for process design," Comp. Chem. Eng., vol. 20, pp. S419-S424, 1996.
24. C. S. Adjiman, I. P. Androulakis, and C. A. Floudas, "Global optimization of MINLP problems in process synthesis and design," Comp. Chem. Eng., vol. 21, pp. S445-S450, 1997.
25. I. P. Androulakis, C. D. Maranas, and C. A. Floudas, "aBB: A global optimization method for general constrained nonconvex problems," J. Glob. Opt., vol. 7, pp. 337-363, 1995.
26. J. L. Klepeis, M. J. Pieja, and C. A. Floudas, "A new class of hybrid global optimization algorithms for peptide structure prediction: Integrated hybrids," Comp. Phys. Comm., vol. 151, pp. 121-140, 2003b.
27. J. Lee, H. A. Scheraga, and S. Rackovsky, "Conformational analysis of the 20-residue membrane-bound portion of melittin by conformational space annealing," Biopolymers, vol. 46, pp. 103-115, 1998.
28. _, "New optimization method for conformational energy calculations on polypeptides: Conformational space annealing," J. Comput. Chem., vol. 18, pp. 1222-1232, 1997.
29. J. Lee and H. A. Scheraga, "Conformational space annealing by parallel computations: Extensive conformational search of met-enkephalin and the 20-residue membrane-bound portion of melittin," Int J Quantum Chem, vol. 75, pp. 255-265, 1999.
30. D. Ripoll, A. Liwo, and H. A. Scheraga, "New developments of the electrostatically driven Monte Carlo method: Tests on the membrane-bound portion of melittin," Biopolymers, vol. 46, pp. 117-126, 1998.
31. J. Lee, J. Pillardy, C. Czaplewski, Y. Arnautova, D. R. Ripoll, A. Liwo, K. D. Gibson, R. J. Wawak, and H. A. Scheraga, "Efficient parallel algorithms in global optimization of potential energy functions for peptides, proteins and crystals," Comp. Phys. Comm., vol. 128, pp. 399-411, 2000.
32. J. L. Klepeis, Y. N. Wei, M. H. Hecht, and C. A. Floudas, "Ab initio prediction of the three-dimensional structure of a de novo designed protein: A double-blind case study," Prot Struct Fund Bioinf, vol. 58, pp. 560-570, 2005.
33. P. Güntert, C. Mumenthaler, and K. Wüthrich, "Torsion angle dynamics for NMR structure calculation with the new program DYANA," J. Mol. Bio., vol. 273, pp. 283-298, 1997.
34. M. H. Hecht, A. Das, A. Go, L. H. Bradley, and Y. Wei, "De novo proteins from designed combinatorial libraries," Prot. Sci., vol. 13, pp. 1711-1723, 2004.
35. Y. Wei, T. Liu, S. L. Sazinsky, D. A. Moffet, I. Pelczer, and M. H. Hecht, "Stably folded de novo proteins from a designed combinatorial library," Prot. Sci., vol. 12, pp. 92-102, 2003.