Accelerating molecular simulations of proteins using Bayesian inference on weak information

Proceedings of the National Academy of Sciences of the United States of America

Volumn 112, Issue 38, 2015, Pages 11846-11851

  Perez, Alberto ^a   MacCallum, Justin L ^b   Dill, Ken A ^a  

^a STONY BROOK UNIVERSITY   (United States)

^b UNIVERSITY OF CALGARY   (Canada)

Author keywords

Bayesian inference; Integrative structural biology; Molecular dynamics; Protein folding

Indexed keywords

AMINO ACID SEQUENCE; ARTICLE; BAYES THEOREM; CONTROLLED STUDY; MOLECULAR DYNAMICS; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN CONFORMATION; PROTEIN FOLDING; PROTEIN SECONDARY STRUCTURE; PROTEIN STRUCTURE; ALGORITHM; CHEMISTRY; THERMODYNAMICS;

PROTEIN;

ALGORITHMS; BAYES THEOREM; MOLECULAR DYNAMICS SIMULATION; PROTEIN STRUCTURE, SECONDARY; PROTEINS; THERMODYNAMICS;

EID: 84942922470     PISSN: 00278424     EISSN: 10916490     Source Type: Journal    
DOI: 10.1073/pnas.1515561112     Document Type: Article

References (30)

1. Berman HM, et al. (2000) The Protein Data Bank. Nucleic Acids Res 28(1): 235-242.
2. Moult J (2005) A decade of CASP: Progress, bottlenecks and prognosis in protein structure prediction. Curr Opin Struct Biol 15(3): 285-289.
3. Moult J, Fidelis K, Kryshtafovych A, Schwede T, Tramontano A (2014) Critical assessment of methods of protein structure prediction (CASP)-round x. Proteins 82(Suppl 2): 1-6.
4. Butterfoss GL, et al. (2012) De novo structure prediction and experimental characterization of folded peptoid oligomers. Proc Natl Acad Sci USA 109(36): 14320-14325.
5. Sali A, Blundell TL (1993) Comparative protein modelling by satisfaction of spatial restraints. J Mol Biol 234(3): 779-815.
6. Eswar N, et al. (2006) Comparative protein structure modeling using Modeller. Curr Protoc Bioinformatics Chapter 5: Unit 5.6.
7. Simons KT, Bonneau R, Ruczinski I, Baker D (1999) Ab initio protein structure prediction of CASP III targets using ROSETTA. Proteins (suppl. 3): 171-176.
8. Hirst SJ, Alexander N, McHaourab HS, Meiler J (2011) RosettaEPR: An integrated tool for protein structure determination from sparse EPR data. J Struct Biol 173(3): 506-514.
9. Shen Y, et al. (2008) Consistent blind protein structure generation from NMR chemical shift data. Proc Natl Acad Sci USA 105(12): 4685-4690.
10. Li X, Jacobson MP, Friesner RA (2004) High-resolution prediction of protein helix positions and orientations. Proteins 55(2): 368-382.
11. MacCallum JL, Perez A, Dill KA (2015) Determining protein structures by combining semireliable data with atomistic physical models by Bayesian inference. Proc Natl Acad Sci USA 112(22): 6985-6990.
12. Roe DR, Cheatham TE, III (2013) PTRAJ and CPPTRAJ: Software for processing and analysis of molecular dynamics trajectory data. J Chem Theory Comput 9(7): 3084-3095.
13. Shao J, Tanner SW, Thompson N, Cheatham TE (2007) Clustering molecular dynamics trajectories: 1. Characterizing the performance of different clustering algorithms. J Chem Theory Comput 3(6): 2312-2334.
14. Lindorff-Larsen K, Piana S, Dror RO, Shaw DE (2011) How fast-folding proteins fold. Science 334(6055): 517-520.
15. Daura X, Gademann K, Jaun B (1999) Peptide folding: When simulation meets experiment. Angew Chem Int Ed 38(1/2): 236-240.
16. Wu GA, Coutsias EA, Dill KA (2008) Iterative assembly of helical proteins by optimal hydrophobic packing. Structure 16(8): 1257-1266.
17. Marks DS, et al. (2011) Protein 3D structure computed from evolutionary sequence variation. PLoS One 6(12): e28766.
18. Flory PJ (1942) Thermodynamics of high polymer solutions. J Chem Phys 10(1): 51-61.
19. Huggins ML (1943) Thermodynamic properties of solutions of high polymers: The empirical constant in the activity equation. Ann N Y Acad Sci 44(4): 431-443.
20. Beauchamp KA, et al. (2011) MSMBuilder2: Modeling Conformational Dynamics at the Picosecond to Millisecond Scale. J Chem Theory Comput 7(10): 3412-3419.
21. Cronkite-Ratcliff B, Pande V (2013) MSMExplorer: Visualizing Markov state models for biomolecule folding simulations. Bioinformatics 29(7): 950-952.
22. Nguyen H, Maier J, Huang H, Perrone V, Simmerling C (2014) Folding simulations for proteins with diverse topologies are accessible in days with a physics-based force field and implicit solvent. J Am Chem Soc 136(40): 13959-13962.
23. Nguyen H, Roe DR, Simmerling C (2013) Improved Generalized Born Solvent Model Parameters for Protein Simulations. J Chem Theory Comput 9(4): 2020-2034.
24. Voelz VA, Dill KA (2007) Exploring zipping and assembly as a protein folding principle. Proteins 66(4): 877-888.
25. Capraro DT, Roy M, Onuchic JN, Jennings PA (2008) Backtracking on the folding landscape of the beta-trefoil protein interleukin-1beta? Proc Natl Acad Sci USA 105(39): 14844-14848.
26. Wu J, Watson JT (1997) A novel methodology for assignment of disulfide bond pairings in proteins. Protein Sci 6(2): 391-398.
27. Onufriev A, Bashford D, Case DA (2004) Exploring protein native states and largescale conformational changes with a modified generalized born model. Proteins 55(2): 383-394.
28. Case DA, et al. (2012) Amber12 (University of California, San Francisco).
29. Mackerell AD, Jr, Feig M, Brooks CL, 3rd (2004) Extending the treatment of backbone energetics in protein force fields: Limitations of gas-phase quantum mechanics in reproducing protein conformational distributions in molecular dynamics simulations. J Comput Chem 25(11): 1400-1415.
30. Eastman P, et al. (2013) OpenMM 4: A Reusable, Extensible, Hardware Independent Library for High Performance Molecular Simulation. J Chem Theory Comput 9(1): 461-469.