Advertisement

Conformational dynamics of \(\alpha \)-conotoxin PnIB in complex solvent systems

  • Jokent T. Gaza
  • Abdul-Rashid B. SampacoIII
  • Kenee Kaiser S. Custodio
  • Ricky B. NellasEmail author
Original Article
  • 38 Downloads

Abstract

Cone snails are slow-moving animals that secure survival by injecting to their prey a concoction of highly potent and stable neurotoxic peptides called conotoxins. These small toxins (~ 10–30 AA) interact with ion channels and their diverse structures account for various variables such as the environment and the prey of preference. This study probed the conformational space of α-conotoxin PnIB from Conus pennaceus by performing all-atom molecular dynamics simulations on the conotoxin in complex solvent systems of water and octanol. Secondary structure analyses showed a uniform conformation for the pure (C100Oc, C100W) and minute (C95Oc, C5Oc) systems. In C50Oc, however, structural changes were observed. The original helices were converted to turns and were shown to happen simultaneously with the elongation of the helix and shortening of end-to-end distance. The transitions complement the orientation of the peptide at the interface. The shift to the broken helix conformation is marked by the rearrangement of solvent molecules to a framework that favors the accumulation of water molecules at residues 6–11 of the H2 region. This promotes specific protein–solvent interactions that facilitate secondary structure transitions. As PnIB has shown favorable binding toward neuronal nicotinic acetylcholine receptors, this study may provide insights on this conotoxin’s therapeutic potential.

Graphic abstract

Description: Structural changes in PnIB are accompanied by a simultaneous change in solvent density.

Keywords

Conotoxins Molecular dynamics Complex solvation Preferential solvation 

Notes

Acknowledgements

The authors acknowledge the computational support provided by the High Performance Computing (HPC) facility under the Computing and Archiving Research Environment (CoARE) of the Department of Science and Technology - Advanced Science and Technology Institute (DOST-ASTI).

Funding

This work was funded by the Office of the Vice Chancellor for Research and Development (OVCRD) of the University of the Philippines Diliman (Project: 191922 ORG).

Compliance with ethical standards

Conflict of interest

The authors declare that there is no conflicting interest with regard to the published material.

References

  1. 1.
    Lebbe E, Peigneur S, Wijesekara I, Tytgat J (2014) Conotoxins targeting nicotinic acetylcholine receptors: an overview. Mar Drugs 12(5):2970–3004.  https://doi.org/10.3390/md12052970 Google Scholar
  2. 2.
    Fry BG, Roelants K, Champagne DE, Scheib H, Tyndall JD, King GF, Nevalainen TJ, Norman JA, Lewis RJ, Norton RS, Renjifo C, de la Vega RCR (2009) The toxicogenomic multiverse: convergent recruitment of proteins into animal venoms. Annu Rev Genom Hum Genet 10(1):483–511.  https://doi.org/10.1146/annurev.genom.9.081307.164356 Google Scholar
  3. 3.
    Mouhat S, Jouirou B, Mosbah A, Waard MD, Sabatier JM (2004) Diversity of folds in animal toxins acting on ion channels. Biochem J 378(3):717–726.  https://doi.org/10.1042/bj20031860 Google Scholar
  4. 4.
    Marí F, Tytgat J (2010) Natural peptide toxins. In: Liu HWB, Mander L (eds) Comprehensive natural products II. Elsevier, Oxford, pp 511–538Google Scholar
  5. 5.
    Olivera BM, Imperial JS, Concepcion GP (2013) Chapter 61—Snail peptides. In: Kastin AJ (ed) Handbook of biologically active peptides, 2nd edn. Academic Press, Boston, pp 437–450Google Scholar
  6. 6.
    Olivera B, Rivier J, Clark C, Ramilo C, Corpuz G, Abogadie F, Mena E, Woodward HD, Cruz L (1990) Diversity of conus neuropeptides. Science 249(4966):257–263.  https://doi.org/10.1126/science.2165278 Google Scholar
  7. 7.
    Yang J, Zhang S (2011) The radular morphology of Nassariidae (Gastropoda: Caenogastropoda) from China. Chin J Oceanol Limnol 29(5):1023–1032.  https://doi.org/10.1007/s00343-011-0079-6 Google Scholar
  8. 8.
    McCleskey EW, Fox AP, Feldman DH, Cruz LJ, Olivera BM, Tsien RW, Yoshikami D (1987) Omega-conotoxin: direct and persistent blockade of specific types of calcium channels in neurons but not muscle. Proc Natl Acad Sci USA 84(12):4327–4331.  https://doi.org/10.1073/pnas.84.12.4327 Google Scholar
  9. 9.
    Mcintosh M, Yoshikami D, Mahe E, Nielsen BD, Rivier JE, Gray WR, Olivera B (1994) A nicotinic acetylcholine receptor ligand of unique specificity, \(\alpha \)-conotoxin ImI. J Biol Chem 269:16733–16739Google Scholar
  10. 10.
    McIntosh JM, Santos AD, Olivera BM (1999) Conus peptides targeted to specific nicotinic acetylcholine receptor subtypes. Annu Rev Biochem 68(1):59–88.  https://doi.org/10.1146/annurev.biochem.68.1.59 Google Scholar
  11. 11.
    Davis J, Jones A, Lewis RJ (2009) Remarkable inter- and intra-species complexity of conotoxins revealed by LC/MS. Peptides 30(7):1222–1227.  https://doi.org/10.1016/j.peptides.2009.03.019 Google Scholar
  12. 12.
    Terlau H, Olivera BM (2004) Conus venoms: a rich source of novel ion channel-targeted peptides. Physiol Rev 84(1):41–68.  https://doi.org/10.1152/physrev.00020.2003 Google Scholar
  13. 13.
    Nicke A, Wonnacott S, Lewis RJ (2004) \(\alpha \)-conotoxins as tools for the elucidation of structure and function of neuronal nicotinic acetylcholine receptor subtypes. Eur J Biochem 271(12):2305–2319.  https://doi.org/10.1111/j.1432-1033.2004.04145.x Google Scholar
  14. 14.
    Azam L, McIntosh JM (2009) Alphaconotoxins as pharmacological probes of nicotinic acetylcholine receptors. Acta Pharmacol Sin 30(6):771–783.  https://doi.org/10.1038/aps.2009.47 Google Scholar
  15. 15.
    Lindstrom J (1997) Nicotinic acetylcholine receptors in health and disease. Mol Neurobiol 15(2):193–222.  https://doi.org/10.1007/bf02740634 Google Scholar
  16. 16.
    Hurst R, Rollema H, Bertrand D (2013) Nicotinic acetylcholine receptors: from basic science to therapeutics. Pharmacol Ther 137(1):22–54.  https://doi.org/10.1016/j.pharmthera.2012.08.012 Google Scholar
  17. 17.
    Albuquerque EX, Pereira EFR, Alkondon M, Rogers SW (2009) Mammalian nicotinic acetylcholine receptors: from structure to function. Physiol Rev 89(1):73–120.  https://doi.org/10.1152/physrev.00015.2008 Google Scholar
  18. 18.
    Mir R, Karim S, Kamal MA, Wilson CM, Mirza Z (2016) Conotoxins: structure, therapeutic potential and pharmacological applications. Curr Pharm Des 22(5):582–589.  https://doi.org/10.2174/1381612822666151124234715 Google Scholar
  19. 19.
    Layer R, McIntosh J (2006) Conotoxins: therapeutic potential and application. Mar Drugs 4(3):119–142.  https://doi.org/10.3390/md403119 Google Scholar
  20. 20.
    Quiram PA, McIntosh JM, Sine SM (2000) Pairwise interactions between neuronal \(\alpha 7\) acetylcholine receptors and \(\alpha \)-conotoxin PnIB. J Biol Chem 275(7):4889–4896.  https://doi.org/10.1074/jbc.275.7.4889 Google Scholar
  21. 21.
    Hu SH, Gehrmann J, Alewood PF, Craik DJ, Martin JL (1997) Crystal structure at 1.1 Å resolution of \(\alpha \)-conotoxin PnIB: comparison with \(\alpha \)-conotoxins PnIA and GI. Biochemistry 36(38):11323–11330.  https://doi.org/10.1021/bi9713052 Google Scholar
  22. 22.
    Crisma M, Formaggio F, Moretto A, Toniolo C (2006) Peptide helices based on \(\alpha \)-amino acids. Biopolymers 84(1):3–12.  https://doi.org/10.1002/bip.20357 Google Scholar
  23. 23.
    Marechal Y (2007) The hydrogen bond and the water molecule: the physics and chemistry of water, aqueous and bio-media. Elsevier Science, AmsterdamGoogle Scholar
  24. 24.
    Smythe ML, Huston SE, Marshall GR (1995) The molten helix: effects of solvation on the \(\alpha \)- to \(3_{10}\)-helical transition. J Am Chem Soc 117(20):5445–5452.  https://doi.org/10.1021/ja00125a003 Google Scholar
  25. 25.
    Nellas RB, Johnson QR, Shen T (2013) Solvent-induced \(\alpha \)- to \(3_{10}\)-helix transition of an amphiphilic peptide. Biochemistry 52(40):7137–7144.  https://doi.org/10.1021/bi400537z Google Scholar
  26. 26.
    Lindsay RJ, Johnson QR, Evangelista W, Nellas RB, Shen T (2016) DMSO enhanced conformational switch of an interfacial enzyme. Biopolymers 105(12):864–872.  https://doi.org/10.1002/bip.22924 Google Scholar
  27. 27.
    Bellanda M, Mammi S, Geremia S, Demitri N, Randaccio L, Broxterman Q, Kaptein B, Pengo P, Pasquato L, Scrimin P (2007) Solvent polarity controls the helical conformation of short peptides rich in \(\text{ C }^{\alpha }\)-tetrasubstituted amino acids. Chem Eur J 13(2):407–416.  https://doi.org/10.1002/chem.200600719 Google Scholar
  28. 28.
    Karle IL, Flippen-Anderson JL, Gurunath R, Balaram P (1994) Facile transition between \(3_{10}\)- and \(\alpha \)-helix: structures of 8-, 9-, and 10-residue peptides containing the -(Leu-Aib-Ala)\(_{2}\)-Phe-Aib-fragment. Protein Sci 3(9):1547–1555.  https://doi.org/10.1002/pro.5560030920 Google Scholar
  29. 29.
    Dutertre S, Lewis RJ (2004) Computational approaches to understand \(\alpha \)-conotoxin interactions at neuronal nicotinic receptors. Eur J Biochem 271(12):2327–2334.  https://doi.org/10.1111/j.1432-1033.2004.04147.x Google Scholar
  30. 30.
    Maier JA, Martinez C, Kasavajhala K, Wickstrom L, Hauser KE, Simmerling C (2015) ff14SB: improving the accuracy of protein side chain and backbone parameters from ff99SB. J Chem Theory Comput 11(8):3696–3713.  https://doi.org/10.1021/acs.jctc.5b00255 Google Scholar
  31. 31.
    Jorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein ML (1983) Comparison of simple potential functions for simulating liquid water. J Chem Phys 79(2):926–935.  https://doi.org/10.1063/1.445869 Google Scholar
  32. 32.
    Wang J, Wang W, Kollman PA, Case DA (2006) Automatic atom type and bond type perception in molecular mechanical calculations. J Mol Graph 25(2):247–260.  https://doi.org/10.1016/j.jmgm.2005.12.005 Google Scholar
  33. 33.
    Wang J, Wolf RM, Caldwell JW, Kollman PA, Case DA (2004) Development and testing of a general amber force field. J Comput Chem 25(9):1157–1174.  https://doi.org/10.1002/jcc.20035 Google Scholar
  34. 34.
    Case D, Babin V, Berryman J, Betz R, Cai QDC, TE Cheatham I, Darden T, Duke R, Gohlke H, Goetz A, Gusarov S, Homeyer N, Janowski P, Kaus J, Kolossvry I, Kovalenko A, Lee T, LeGrand S, Luchko T, Luo R, Madej B, Merz K, Paesani F, Roe D, Roitberg A, Sagui C, Salomon-Ferrer R, Seabra G, Simmerling C, Smith W, Swails J, Walker R, Wang J, Wolf R, Wu X, Kollman P (2014) AMBER 14. University of California, San FranciscoGoogle Scholar
  35. 35.
    Martínez L, Andrade R, Birgin EG, Martínez JM (2009) PACKMOL: a package for building initial configurations for molecular dynamics simulations. J Comput Chem 30(13):2157–2164.  https://doi.org/10.1002/jcc.21224 Google Scholar
  36. 36.
    Martínez JM, Martínez L (2003) Packing optimization for automated generation of complex system’s initial configurations for molecular dynamics and docking. J Comput Chem 24(7):819–825.  https://doi.org/10.1002/jcc.10216 Google Scholar
  37. 37.
    Phillips JC, Braun R, Wang W, Gumbart J, Tajkhorshid E, Villa E, Chipot C, Skeel RD, Kalé L, Schulten K (2005) Scalable molecular dynamics with NAMD. J Comput Chem 26(16):1781–1802.  https://doi.org/10.1002/jcc.20289 Google Scholar
  38. 38.
    Paterlini M, Ferguson DM (1998) Constant temperature simulations using the Langevin equation with velocity Verlet integration. Chem Phys 236(1–3):243–252.  https://doi.org/10.1016/s0301-0104(98)00214-6 Google Scholar
  39. 39.
    Feller SE, Zhang Y, Pastor RW, Brooks BR (1995) Constant pressure molecular dynamics simulation: the Langevin piston method. J Chem Phys 103(11):4613–4621.  https://doi.org/10.1063/1.470648 Google Scholar
  40. 40.
    Essmann U, Perera L, Berkowitz ML, Darden T, Lee H, Pedersen LG (1995) A smooth particle mesh Ewald method. J Chem Phys 103(19):8577–8593.  https://doi.org/10.1063/1.470117 Google Scholar
  41. 41.
    Ryckaert JP, Ciccotti G, Berendsen HJ (1977) Numerical integration of the Cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes. J Comput Phys 23(3):327–341.  https://doi.org/10.1016/0021-9991(77)90098-5 Google Scholar
  42. 42.
    Roe DR, Cheatham TE (2013) PTRAJ and CPPTRAJ: software for processing and analysis of molecular dynamics trajectory data. J Chem Theory Comput 9(7):3084–3095.  https://doi.org/10.1021/ct400341p Google Scholar
  43. 43.
    Kabsch W, Sander C (1983) Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers 22(12):2577–2637.  https://doi.org/10.1002/bip.360221211 Google Scholar
  44. 44.
    Huston SE, Marshall GR (1994) \(\alpha /3_{10}\)-helix transitions in \(\alpha \)-methylalanine homopeptides: conformational transition pathway and potential of mean force. Biopolymers 34(1):75–90.  https://doi.org/10.1002/bip.360340109 Google Scholar
  45. 45.
    Ramachandran G, Ramakrishnan C, Sasisekharan V (1963) Stereochemistry of polypeptide chain configurations. J Mol Biol 7(1):95–99.  https://doi.org/10.1016/s0022-2836(63)80023-6 Google Scholar
  46. 46.
    Henchman RH, McCammon JA (2002) Extracting hydration sites around proteins from explicit water simulations. J Comput Chem 23(9):861–869.  https://doi.org/10.1002/jcc.10074 Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Jokent T. Gaza
    • 1
  • Abdul-Rashid B. SampacoIII
    • 1
  • Kenee Kaiser S. Custodio
    • 1
  • Ricky B. Nellas
    • 1
    Email author
  1. 1.Institute of Chemistry, College of ScienceUniversity of the Philippines DilimanDiliman, Quezon CityPhilippines

Personalised recommendations