Journal of Computer-Aided Molecular Design

, Volume 24, Issue 1, pp 17–22 | Cite as

How the energy evaluation method used in the geometry optimization step affect the quality of the subsequent QSAR/QSPR models

  • Åsmund Rinnan
  • Niels Johan Christensen
  • Søren Balling Engelsen
Article

Abstract

The quantitative influence of the choice of energy evaluation method used in the geometry optimization step prior to the calculation of molecular descriptors in QSAR and QSPR models was investigated. A total of 11 energy evaluation methods on three molecular datasets (toxicological compounds, aromatic compounds and PPARγ agonists) were studied. The methods employed were: MMFF94 s, MM3* with εr (relative dielectric constant) = 1, MM3* with εr = 80, AM1, PM3, HF/STO-3G, HF/6-31G, HF/6-31G(d,p), B3LYP/STO-3G, B3LYP/6-31G, and B3LYP/6-31G(d,p). The 3D-descriptors used in the QSAR/QSPR models were calculated with commercially available molecular descriptor programs primarily directed toward pharmaceutical research. In order to evaluate the uncertainties involved in the QSAR/QSPR predictions bootstrapping was used to validate all models using 1,000 drawings for each data set. The scale free error-term, q2, was used to compare the relative quality of the models resulting from different optimization methods on the same set of molecules. Depending on the dataset, the average 0.632 bootstrap estimated q2 varies from 0.55 to 0.57 for the toxicological compounds, from 0.58 to 0.62 for the aromatic compounds, and from 0.69 to 0.75 for the PPARγ agonists. The B3LYP/6-31G(d,p) provided the best overall results, albeit the increase in q2 was small in all cases. The results clearly indicate that the choice of the energy evaluation method has very limited impact. This study suggests that QSAR or QSPR studies might benefit from the choice of a rapid optimization method with little or no loss in model accuracy.

Keywords

QSAR QSPR Energy evaluation PLS regression Quantum mechanics Semi-empirical Molecular mechanics 

Abbreviations

QSPR

Quantitative structure property relationship

QSAR

Quantitative structure activity relationship

MM3*

Allinger’s molecular mechanics

AM1

Austin model 1

PM3

Parameterized model 3, HF, Hartree–Fock

B3LYP

The hybrid exchange–correlation functional based on work from Becke, Lee, Yang and Par

PLS

Partial least squares

RMSD

Root mean square distance

MCMM

Monte Carlo multiple minimum

Supplementary material

10822_2009_9308_MOESM1_ESM.docx (96 kb)
Supplementary material 1 (DOCX 96 kb)

References

  1. 1.
    Agüero-Chapin G, Varona-Santos J, de la Riva GA, Antunes A, Gonzáles-Villa T, Uriarte E, González-Díaz H (2009) J Proteome Res 8:2122–2128CrossRefGoogle Scholar
  2. 2.
    Pasha FA, Nez MM, Cho SJ, Ansari M, Mishra SK, Tiwari S (2009) Chem Biol Drug Des 73:537–544CrossRefGoogle Scholar
  3. 3.
    Jensen BF, Sørensen MD, Kissmeyer A-M, Björkling F, Sonne K, Engelsen SB, Nørgaard L (2003) J Comput Aid Mol Des 17:849–859CrossRefGoogle Scholar
  4. 4.
    Thorsteinson N, Ban F, Santos-Filho O, Tabaei SMH, Miguel-Queralt S, Underhill C, Cherkasov A, Hammond GL (2009) Toxicol Appl Pharm 234:47–57CrossRefGoogle Scholar
  5. 5.
    Foresman JB, Frisch A (1996) Exploring chemistry with electronic structure methods, 2nd edn. Gaussian, Pittsburgh, pp 157–158Google Scholar
  6. 6.
    Hudáky I, Hudáky I, Perczel A (2004) J Comput Chem 25:1522–1531CrossRefGoogle Scholar
  7. 7.
    Swart M, Snijders JG (2003) Theor Chem Acc 110:34–41Google Scholar
  8. 8.
    Bayari S, Saglam S, Ustundag HF (2005) J Mol Struct 726:225–232Google Scholar
  9. 9.
    Dewar MJS, Zoebisch EG, Healy EF, Stewart JJP (1985) J Am Chem Soc 107:3902–3909CrossRefGoogle Scholar
  10. 10.
    Stewart JJP (1989) J Comput Chem 10:209–220CrossRefGoogle Scholar
  11. 11.
    Roothaan CCJ (1951) Rev Mod Phys 23:69–89CrossRefGoogle Scholar
  12. 12.
    Becke AD (1993) J Chem Phys 98:5648–5652CrossRefGoogle Scholar
  13. 13.
    Lee C, Yang W, Parr RG (1988) Phys Rev B 37:785–789CrossRefGoogle Scholar
  14. 14.
    Vosko SH, Wilk L, Nusair M (1980) Can J Phys 58:1200–1211CrossRefGoogle Scholar
  15. 15.
    Stephens PJ, Devlin FJ, Chabalowski CF, Frisch MJ (1994) J Phys Chem 98:11623–11627CrossRefGoogle Scholar
  16. 16.
    Ditchfield R, Hehre WJ, Pople JA (1971) J Chem Phys 54:724–728CrossRefGoogle Scholar
  17. 17.
    Hehre WJ, Ditchfield R, Pople JA (1972) J Chem Phys 56:2257–2261CrossRefGoogle Scholar
  18. 18.
    Hariharan PC, Pople JA (1974) Mol Phys 27:209–214CrossRefGoogle Scholar
  19. 19.
    Gordon MS (1980) Chem Phys Lett 76:163–168CrossRefGoogle Scholar
  20. 20.
    Hariharan PC, Pople JA (1973) Theor Chim Acta 28:213–222CrossRefGoogle Scholar
  21. 21.
    Fletcher R, Reeves CM (1964) Computer J 7:149–154CrossRefGoogle Scholar
  22. 22.
    Stewart JPP (1989) Comput Chem 13:157–158CrossRefGoogle Scholar
  23. 23.
    Dennis JE, More JJ (1977) SIAM Rev 19:46–89CrossRefGoogle Scholar
  24. 24.
    He L, Jurs PC (2005) J Mol Graphics Modell 23:503–523CrossRefGoogle Scholar
  25. 25.
    Agantovic-Kustrin S, Beresford R, Pauzi A, Yusof M (2001) J Pharm Biomed Anal 26:241–254CrossRefGoogle Scholar
  26. 26.
    Rücker C, Scarsi M, Meringer M (2006) Bioorg Med Chem 14:5178–5195CrossRefGoogle Scholar
  27. 27.
    Dennington II R, Keith T, Milliam J, Eppinnett K, Hovell WL, Gilliland R (2003) GaussView, Version 3.09, Semichem, Inc., Shawnee Mission. http://www.gaussian.com
  28. 28.
    Schrödinger LLC (2007) http://www.schrodinger.com
  29. 29.
    Halgren TA (1999) J Comput Chem 20:720–729CrossRefGoogle Scholar
  30. 30.
    Polak E, Ribiere G (1969) Revenue Francaise Inform Rech Operationelle 16:35Google Scholar
  31. 31.
    Allinger NL, Yuh YH, Lii J-H (1989) J Am Chem Soc 111:8551–8566CrossRefGoogle Scholar
  32. 32.
    Hehre WJ, Stewart RF, Pople JA (1969) J Chem Phys 51:2657–2664CrossRefGoogle Scholar
  33. 33.
    Peng CY, Ayala PY, Schlegel HB, Frisch MJ (1996) J Comp Chem 17:49–56CrossRefGoogle Scholar
  34. 34.
    Vamp 6.5 (1997) Oxford Software LimitedGoogle Scholar
  35. 35.
    Talete srl (2009) DRAGON for Windows (Software for Molecular Descriptor Calculations) http://www.talete.mi.it
  36. 36.
    Schuur JH, Selzer P, Gasteiger J (1996) J Am Chem Soc 36:334–344Google Scholar
  37. 37.
    Todeschini R, Lasagni M (1994) J Chemom 8:263–272CrossRefGoogle Scholar
  38. 38.
    Consonni V, Todeschini R, Pavan M, Gramatica P (2002) J Chem Inf Comput Sci 42:693–705Google Scholar
  39. 39.
    Martens H, Martens M, Næs T (2001) Multivariate analysis of quality. John Wiley, Chichester, pp 111–125Google Scholar
  40. 40.
    Wehrens R, Putter H, Buydens LMC (2000) Chemom Intell Lab Syst 54:35–52CrossRefGoogle Scholar
  41. 41.
    Efron B, Gong G (1983) Am Stat 37:36–48CrossRefGoogle Scholar
  42. 42.
    Consonni V, Ballabio D, Todeschini R (2009) J Chem Inf Model 49:1669–1678CrossRefGoogle Scholar
  43. 43.
    Howell JF, Games PA (1974) Brit J Math Stat Psy 27:72–81Google Scholar
  44. 44.
    Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, Cheeseman JR, Montgomery JA, Jr VrevenT, Kudin KN, Burant JC, Millam JM, Iyengar SS, Tomasi J, Barone V, Mennucci B, Cossi M, Scalmani G, Rega N, Petersson GA, Nakatsuji H, Hada M, Ehara M, Toyota K, Fukuda R, Hasegawa J, Ishida M, Nakajima T, Honda Y, Kitao O, Nakai H, Klene M, Li X, Knox JE, Hratchian HP, Cross JB, Bakken V, Adamo C, Jaramillo J, Gomperts R, Stratmann RE, Yazyev O, Austin AJ, Cammi R, Pomelli C, Ochterski JW, Ayala PY, Morokuma K, Voth GA, Salvador P, Dannenberg JJ, Zakrzewski VG, Dapprich S, Daniels AD, Strain MC, Farkas O, Malick DK, Rabuck AD, Raghavachari K, Foresman JB, Ortiz JV, Cui Q, Baboul AG, Clifford S, Cioslowski J, Stefanov BB, Liu G, Liashenko A, Piskorz P, Komaromi I, Martin RL, Fox DJ, Keith T, Al-Laham MA, Peng CY, Nanayakkara A, Challacombe M, Gill PMW, Johnson B, Chen W, Wong MW, Gonzalez C, Pople JA (2009) Gaussian 03 revision C02. Gaussian Inc, WallingfordGoogle Scholar
  45. 45.
    The Mathworks ™ (2009) USA, http://www.mathworks.com
  46. 46.
    Puzyn T, Suzuki N, Haranczyk M, Rak J (2008) J Chem Inf Model 48:1174–1180CrossRefGoogle Scholar
  47. 47.
    Rocha GB, Freire RO, Simas AM, Stewart JJP (2006) J Comput Chem 27:1101–1111CrossRefGoogle Scholar
  48. 48.
    Stewart JJP (2007) J Mol Model 13:1173–1213CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Åsmund Rinnan
    • 1
  • Niels Johan Christensen
    • 1
  • Søren Balling Engelsen
    • 1
  1. 1.Quality and Technology, Department of Food Science, Faculty of Life SciencesUniversity of CopenhagenFrederiksberg CDenmark

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