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The SAMPL3 blind prediction challenge: transfer energy overview

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Abstract

Prediction of the free energy of solvation of a small molecule, or its transfer energy, is a necessary step along the path towards calculating the interactions between molecules that occur in an aqueous environment. A set of these transfer energies were gathered from the literature for series of chlorinated molecules with varying numbers of chlorines based on ethane, biphenyl, and dibenzo-p-dioxin. This focused set of molecules were then provided as a blinded challenge to assess the ability of current computational solvation methods to accurately model the interactions between water and increasingly chlorinated compounds. This was presented as part of the SAMPL3 challenge, which represented the fourth iterative blind prediction challenge involving transfer energies. The results of this exercise demonstrate that the field in general has difficulty predicting the transfer energies of more highly chlorinated compounds, and that methods seem to be erring in the same direction.

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References

  1. Dominy BN (2008) Curr Pharm Biotechnol 9:87–95

    Article  CAS  Google Scholar 

  2. Raha K, Merz K (2005) Annu Rep Comput Chem 1:113–130

    Article  CAS  Google Scholar 

  3. Shirts MR, Mobley DL, Chodera JD (2007) Annu Rep Comput Chem 3:41–59

    Article  CAS  Google Scholar 

  4. Moult J (2005) Curr Opin Struct Biol 15:285–289

    Article  CAS  Google Scholar 

  5. Battey JND, Kop J, Bordoli L, Read RJ, Clarke ND, Schwede T (2007) Proteins 69(Suppl 8):68–82

    Article  CAS  Google Scholar 

  6. Geballe MT, Skillman AG, Nicholls A, Guthrie JP, Taylor PJ (2010) The SAMPL2 blind prediction challenge: introduction and overview. J Comput Aided Mol Des 24(4):259–279

    Article  CAS  Google Scholar 

  7. Guthrie JP (2009) A blind challenge for computational solvation free energies: introduction and overview. J Phys Chem B 113(14):4501–4507

    Article  CAS  Google Scholar 

  8. Nicholls A, Mobley DL, Guthrie JP, Chodera JD, Bayly CI, Cooper MD, Pande VS (2008) Predicting small-molecule solvation free energies: an informal blind test for computational chemistry. J Med Chem 51(4):769–779

    Article  CAS  Google Scholar 

  9. Bevington PR (1969) Data reduction and error analysis for the physical sciences. McGraw-Hill, New York, p 73

    Google Scholar 

  10. Bevington PR (1969) Data reduction and error analysis for the physical sciences. McGraw-Hill: New York (Chapter 4)

  11. Guthrie JP (2011) In preparation

  12. Bowman MC, Acree F, Corbett MK (1960) J Agric Food Chem 8:406–408

    Article  CAS  Google Scholar 

  13. Biggar JW, Dutt GR, Riggs RL (1967) Bull Environ Contam Toxicol 2:90–100

    Article  CAS  Google Scholar 

  14. Miller MM, Ghodbane S, Wasik SP, Tewari YB, Martire DE (1984) J Chem Eng Data 29:184–190

    Article  CAS  Google Scholar 

  15. Weil L, Dure G, Quentin K (1974) Zeitschrift fuer Wasser und Abwasser Forschung 7:169–175

    CAS  Google Scholar 

  16. Webster GRB, Friesen KJ, Sarna LP, Muir DCG (1985) Chemosphere 14:609–622

    Article  CAS  Google Scholar 

  17. Friesen KJ, Sarna LP, Webster GRB (1985) Chemosphere 14:1267–1274

    Article  CAS  Google Scholar 

  18. Guthrie JP (1972) Chem. Commun 897–899

  19. Guthrie JP (1973) Can J Chem 51:3494–3498

    Article  CAS  Google Scholar 

  20. Brunner S, Hornung E, Santl H, Wolff E, Piringer OG (1990) Environ Sci Technol 24:1751–1754

    Article  CAS  Google Scholar 

  21. Fang F, Chu S, Hong CS (2006) Anal Chem 78:5412–5418

    Article  CAS  Google Scholar 

  22. Murphy TJ, Mullin MD, Meyer JA (1987) Environ Sci Technol 21:155–162

    Article  CAS  Google Scholar 

  23. Dunnivant FM, Coates JT, Eizerman AW (1988) Environ Sci Technol 22:448–453

    Article  CAS  Google Scholar 

  24. ten Hulscher TEM, van der Velde LE, Bruggeman WA (1992) Environ Toxicol Chem 11:1595–1603

    Article  Google Scholar 

Download references

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Correspondence to Matthew T. Geballe.

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Geballe, M.T., Guthrie, J.P. The SAMPL3 blind prediction challenge: transfer energy overview. J Comput Aided Mol Des 26, 489–496 (2012). https://doi.org/10.1007/s10822-012-9568-8

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  • DOI: https://doi.org/10.1007/s10822-012-9568-8

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