Considering usage of different force-fields for molecular dynamic studies of the ionic peptides and their dimers

A. V. Danilkovich ; D. A. Tikhonov ; E. V. Sobolev ; T. E. Shadrina ; I. P. Udovichenko

Matematičeskaâ biologiâ i bioinformatika, Tome 6 (2011) no. 1, pp. 53-62.

Résumé

The paper presents comparative data on the impact of force-fields AMBER (ff03, ff99SB, and ff96) on the results of molecular dynamics experiments with dimeric molecules formed by ion-peptide $\mathrm{NH_2\text-(RADA)_4\text-COOH}$ in the $\beta$-conformation at two temperatures (300 K and 320 K). It is shown that an MD simulation in explicit water environment is the most informative approach. The use of different force-fields has a significant influence on the stability of the initial molecular conformation of the peptide over time. Finally, the simulation in ff99SB environment provides significant stability of antiparallel $\beta$-structure of the dimer at 300 K, while ff96 not only ensures the highest stability of the initial b-peptide conformation at higher temperatures, but also enhances the retention of antiparallel $\beta$-conformation, which determines the ability of $\mathrm{NH_2\text-(RADA)_4\text-COOH}$ peptides to self-organization.

Bibliographie

[1] Van Gunsteren W. F., Dolenc J., Mark A. E., “Molecular simulation as an aid to experimentalists”, Current Opinions in Structural Biology, 18 (2008), 149–153 | DOI

[2] Mackerell A. D., “Empirical force fields for biological macromolecules: overview and issues”, Journal of Computational Chemistry, 25 (2004), 1584–1604 | DOI

[3] Jorgensen W. L., Tirado-Rives J., “Potential energy functions for atomic-level simulations of water and organic and biomolecular systems”, Proceedings of National Academy of Sciences of the USA, 102 (2005), 6665–6670 | DOI

[4] Van Gunsteren W. F., Bakowies D., Baron R., et al., “Biomolecular modeling: goals, problems, perspectives”, Angewandte Chemie International Edition, 45 (2006), 4064–4092 | DOI

[5] Sorin E. J., Rhee Y. M., Shirts M. R., Pande V. S., “The solvation interface is a determining factor in peptide conformational preferences”, Journal of Molecular Biology, 356 (2006), 248–256 | DOI

[6] Hess B., van der Vegt N. F. A., “Hydration thermodynamic properties of amino acid analogues: a systematic comparison of biomolecular force fields and water models”, Journal of Physical Chemistry B, 110 (2006), 17616–17626 | DOI

[7] Reif M. M., Krutler V., Kastenholz M. A., et al., “Molecular dynamics simulations of a reversibly folding $\beta$-heptapeptide in methanol: influence of the treatment of long-range electrostatic interactions”, Journal of Physical Chemistry B, 113 (2009), 3112–3128 | DOI

[8] Duan Y., Wu C., Chowdhury S., et al., “A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations”, Journal of Computational Chemistry, 24 (2003), 1999–2012 | DOI

[9] Hornak V., Abel R., Okur A., et al., “Comparison of multiple AMBER force fields and development of improved protein backbone parameters”, Proteins, 65 (2006), 712–725 | DOI

[10] Feig M., MacKerell A., Brooks C., “Force field influence on the observation of $pi$-helical protein structures in molecular dynamics simulations”, Journal of Computational Chemistry B, 107 (2003), 2831–2836

[11] Oostenbrink C., Villa A., Mark A. E., Gunsteren W. F. V., “A biomolecular force field based on the free enthalpy of hydration and solvation: the GROMOS force-field parameter sets 53A5 and 53A6”, Journal of Computational Chemistry, 25 (2004), 1656–1676 | DOI

[12] Kaminski G., Friesner R., Tirado-Rives J., Jorgensen W., “Evaluation and reparametrization of the OPLS-AA force field for proteins via comparison with accurate quantum chemical calculations on peptides”, Journal of Physical Chemistry B, 105 (2001), 6474–6487 | DOI

[13] Rueda M., Ferrer-Costa C., Meyer T., et al., “A consensus view of protein dynamics”, Proceedings of National Academy of Sciences of the USA, 104 (2007), 796–801 | DOI

[14] Ferrara P., Apostolakis J., Caflisch A., “Thermodynamics and kinetics of folding of two model peptides investigated by molecular dynamics simulations”, Journal of Physical Chemistry B, 104 (2000), 5000–5010 | DOI

[15] Fersht A. R., Daggett V., “Protein folding and unfolding at atomic resolution”, Cell., 108 (2002), 573–582 | DOI

[16] Simmerling C., Strockbine B., Roitberg A. E., “All-atom structure prediction and folding simulations of a stable protein”, Journal of American Chemical Society, 124 (2002), 11258–11259 | DOI

[17] Snow C. D., Nguyen H., Pande V. S., Gruebele M., “Absolute comparison of simulated and experimental protein-folding dynamics molecular dynamics simulations”, Nature, 420 (2002), 102–106 | DOI

[18] Snow C. D., Zagrovic B., Pande V. S., “The Trp cage folding kinetics and unfolded state topology via molecular dynamics simulations”, Journal of American Chemical Society, 124 (2002), 14548–14549 | DOI

[19] Wu X., Brooks B. R., “$\beta$-hairpin folding mechanism of a nineresidue peptide revealed from molecular dynamics simulations in explicit water”, Biophysical Journal, 86 (2002), 1946–1958

[20] Gnanakaran S., Nymeyer H., Portman J., et. al., “Peptide folding simulations”, Current Opinions in Structural Biology, 13 (2003), 168–174 | DOI

[21] Zhang S., “Fabrication of novel biomaterials through molecular self-assembly”, Nature Biotechnology, 21 (2003), 1171–1178 | DOI

[22] Munoz V., Serrano L., “Elucidating the folding problem of helical peptides using empirical parameters”, Nature Structural and Molecular Biology, 1 (1994), 399–409 | DOI

[23] Macindoe G., Mavridis L., Venkatraman V., et. al., “HexServer: an FFT-based protein docking server powered by graphics processors”, Nucleic Acids Research, 38 (2010), 445–449 | DOI

[24] Tovchigrechko A., Vakser I. A., “Development and testing of an automated approach to protein docking”, Proteins, 60:2 (2005), 296–301 | DOI

[25] HyperChem$^\circledR$ Computational Chemistry. Practical Guide – Theory and Method, HC 70-00-04-00, Hypercube Inc, Gainesville, 2002, 350 pp.

[26] Case D. A., Cheatham T. E. III, Darden T., et. al., “The Amber biomolecular simulation programs”, Journal of Computational Chemistry, 26 (2005), 1668–1688 | DOI

[27] Jorgensen W. L., Chandrasekhar J., Madura J. D., et. al., “Comparison of simple potential functions for simulating liquid water”, Journal of Chemical Physics, 79 (1983), 926–935 | DOI

[28] Kollman P. A., Dixon R., Cornell W., et. al., “The development/application of a “minimalist” organic/biochemical molecular mechanic force field using a combination of ab initio calculations and experimental data”, Computer Simulation of Biomolecular Systems, v. 3, eds. van Gunsteren W. F., Weiner P. K., Wilkinson A. J., KLUWER/ESCOM, Dordrecht, 1997, 83–96

[29] Lee M. C., Duan Y., “Distinguish protein decoys by using a scoring function based on a new Amber force field, short molecular dynamics simulations, and the generalized Born solvent model”, Proteins, 55 (2004), 620–634 | DOI

[30] Kabsch W., Sander C., “Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features”, Biopolymers, 12 (1983), 2577–2637 | DOI

[31] Onufriev A., Bashford D., Case D. A., “Modification of the Generalized Born Model Suitable for Macromolecules”, Journal of Physical Chemistry B, 104:15 (2000), 3712–3720 | DOI