Dynamics in sequence space for RNA secondary structure design

Journal of Chemical Theory and Computation

Volumn 8, Issue 10, 2012, Pages 3663-3670

  Matthies, Marco C ^a   Bienert, Stefan ^a,b   Torda, Andrew E ^a  

^a UNIVERSITY OF HAMBURG   (Germany)

^b UNIVERSITY OF BASEL   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84867350994     PISSN: 15499618     EISSN: 15499626     Source Type: Journal    
DOI: 10.1021/ct300267j     Document Type: Article

References (46)

1. Mathews, D. H.; Turner, D. H. Prediction of RNA secondary structure by free energy minimization Curr. Opin. Struct. Biol. 2006, 16, 270-278
2. Floudas, C. A.; Fung, H. K.; McAllister, S. R.; Mönnigmann, M.; Rajgaria, R. Advances in protein structure prediction and de novo protein design: A review Chem. Eng. Sci. 2006, 61, 966-988
3. Samish, I.; MacDermaid, C. M.; Perez-Aguilar, J. M.; Saven, J. G. Theoretical and Computational Protein Design Annu. Rev. Phys. Chem. 2011, 62, 129-149
4. Metropolis, N.; Rosenbluth, A. W.; Rosenbluth, M. N.; Teller, A. H.; Teller, E. Equation of State Calculations by Fast Computing Machines J. Chem. Phys. 1953, 21, 1087
5. Hellinga, H. W.; Richards, F. M. Optimal sequence selection in proteins of known structure by simulated evolution Proc. Natl. Acad. Sci. U.S.A. 1994, 91, 5803-5807
6. Dantas, G.; Kuhlman, B.; Callender, D.; Wong, M.; Baker, D. A Large Scale Test of Computational Protein Design: Folding and Stability of Nine Completely Redesigned Globular Proteins J. Mol. Biol. 2003, 332, 449-460
7. Kuhlman, B.; Dantas, G.; Ireton, G. C.; Varani, G.; Stoddard, B. L.; Baker, D. Design of a Novel Globular Protein Fold with Atomic-Level Accuracy Science 2003, 302, 1364-1368
8. Kirkpatrick, S.; Gelatt, C. D., Jr.; Vecchi, M. P. Optimization by Simulated Annealing Science 1983, 220, 671-680
9. Cootes, A. P.; Curmi, P. M. G.; Torda, A. E. Biased Monte Carlo optimization of protein sequences J. Chem. Phys. 2000, 113, 2489-2496
10. Zou, J.; Saven, J. G. Using self-consistent fields to bias Monte Carlo methods with applications to designing and sampling protein sequences J. Chem. Phys. 2003, 118, 3843-3854
11. Yang, X.; Saven, J. G. Computational methods for protein design and protein sequence variability: biased Monte Carlo and replica exchange Chem. Phys. Lett. 2005, 401, 205-210
12. Hofacker, I. L.; Fontana, W.; Stadler, P. F.; Bonhoeffer, L. S.; Tacker, M.; Schuster, P. Fast folding and comparison of RNA secondary structures Monatsh. Chem. 1994, 125, 167-188
13. Andronescu, M.; Fejes, A. P.; Hutter, F.; Hoos, H. H.; Condon, A. A New Algorithm for RNA Secondary Structure Design J. Mol. Biol. 2003, 336, 607-624
14. Busch, A.; Backofen, R. INFO-RNA - a fast approach to inverse RNA folding Bioinformatics 2006, 22, 1823-1831
15. Zadeh, J. N.; Wolfe, B. R.; Pierce, N. A. Nucleic acid sequence design via efficient ensemble defect optimization J. Comput. Chem. 2011, 32, 439-452
16. Desmet, J.; de Maeyer, M.; Hazes, B.; Lasters, I. The dead-end elimination theorem and its use in protein side-chain positioning Nature 1992, 356, 539-542
17. Desmet, J.; Spriet, J.; Lasters, I. Fast and accurate side-chain topology and energy refinement (FASTER) as a new method for protein structure optimization Proteins 2002, 48, 31-43
18. Allen, B. D.; Mayo, S. L. Dramatic performance enhancements for the FASTER optimization algorithm J. Comput. Chem. 2006, 27, 1071-1075
19. Dahiyat, B. I.; Mayo, S. L. De Novo Protein Design: Fully Automated Sequence Selection Science 1997, 278, 82-87
20. Koehl, P.; Levitt, M. De novo protein design. I. In search of stability and specificity J. Mol. Biol. 1999, 293, 1161-1181
21. Voigt, C. A.; Gordon, D. B.; Mayo, S. L. Trading accuracy for speed: a quantitative comparison of search algorithms in protein sequence design J. Mol. Biol. 2000, 299, 789-803
22. Lafontaine, I.; Lavery, R. Optimization of Nucleic Acid Sequences Biophys. J. 2000, 79, 680-685
23. Hu, X.; Hu, H.; Beratan, D. N.; Yang, W. A gradient-directed Monte Carlo approach for protein design J. Comput. Chem. 2010, 31, 2164-2168
24. Tidor, B. Simulated annealing on free energy surfaces by a combined molecular dynamics and Monte Carlo approach J. Phys. Chem. 1993, 97, 1069-1073
25. Kong, X.; Brooks, C. L. λ-dynamics: A new approach to free energy calculations J. Chem. Phys. 1996, 105, 2414
26. Godzik, A. In search of the ideal protein sequence Protein Eng. 1995, 8, 409-416
27. Torda, A. E. Protein Sequence Optimization-Theory, Practice, and Fundamental Impossibility Soft Mater. 2004, 2, 1-10
28. Jones, D. T. De novo protein design using pairwise potentials and a genetic algorithm Protein Sci. 1994, 3, 567-574
29. Shakhnovich, E. I.; Gutin, A. M. A new approach to the design of stable proteins Protein Eng. 1993, 6, 793-800
30. Hom, G. K.; Mayo, S. L. A search algorithm for fixed-composition protein design J. Comput. Chem. 2006, 27, 375-378
31. Seno, F.; Vendruscolo, M.; Maritan, A.; Banavar, J. R. Optimal Protein Design Procedure Phys. Rev. Lett. 1996, 77, 1901-1904
32. Bhattacherjee, A.; Biswas, P. Statistical Theory of Protein Sequence Design by Random Mutation J. Phys. Chem. B 2009, 113, 5520-5527
33. Chiu, T. L.; Goldstein, R. A. Optimizing potentials for the inverse protein folding problem Protein Eng. 1998, 11, 749-752
34. Knight, J. L.; Brooks, C. L., III. λ-Dynamics Free Energy Simulation Methods J. Comput. Chem. 2009, 30, 1692-1700
35. Darty, K.; Denise, A.; Ponty, Y. VARNA: Interactive drawing and editing of the RNA secondary structure Bioinformatics 2009, 25, 1974-1975
36. Hockney, R. W.; Eastwood, J. W. Computer Simulation Using Particles; McGraw-Hill: New York, 1988; p 94.
37. Harvey, S. C.; Tan, R. K.-Z.; Cheatham, T. E., III. The Flying Ice Cube: Velocity Rescaling in Molecular Dynamics Leads to Violation of Energy Equipartition J. Comput. Chem. 1998, 19, 726-740
38. José, J. V.; Saletan, E. J. Classical Dynamics: A Contemporary Approach; Cambridge University Press: Cambridge, U. K., 1998; p 251.
39. McCaskill, J. S. The equilibrium partition function and base pair binding probabilities for RNA secondary structure Biopolymers 1990, 29, 1105-1119
40. Dirks, R. M.; Lin, M.; Winfree, E.; Pierce, N. A. Paradigms for computational nucleic acid design Nucleic Acids Res. 2004, 32, 1392-1403
41. Nussinov, R.; Pieczenik, G.; Griggs, J. R.; Kleitman, D. J. Algorithms for Loop Matchings SIAM J. Appl. Math. 1978, 35, 68-82
42. Mathews, D. H.; Sabina, J.; Zuker, M.; Turner, D. H. Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure J. Mol. Biol. 1999, 288, 911-940
43. Dill, K. A. Additivity Principles in Biochemistry J. Biol. Chem. 1997, 272, 701-704
44. Giegerich, R.; Voß, B.; Rehmsmeier, M. Abstract shapes of RNA Nucleic Acids Res. 2004, 32, 4843-4851
45. Knight, J. L.; Brooks, C. L., III. Applying efficient implicit nongeometric constraints in alchemical free energy simulations J. Comput. Chem. 2011, 32, 3423-3432
46. Flamm, C.; Hofacker, I. L. Beyond energy minimization: approaches to the kinetic folding of RNA Monatsh. Chem. 2008, 139, 447-457