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Tautomers and reference 3D-structures: the orphans of in silico drug design

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Abstract

The importance of calculating not only the correct tautomer, but also the correct protonation state and conformation in 3D modeling applications is emphasized. Above all, identifying and characterizing the most stable form of a ligand under physiological conditions is seen to be the key to successful 3D modeling. Modeling strategies that make use of the performance of modern hardware can employ physically more appropriate models than most currently in use and still be easily applicable to large numbers of compounds. Because the performance of quantitative structure–property relationships is likely to be limited by the available training and validation data, we must either find new sources of such data or resort to explicit modeling, which can partly be parameterized using definitive ab initio calculations for reference data such as gas-phase proton affinities.

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References

  1. Pospisil P, Ballmer P, Scapozza L, Folkers G (2003) Tautomerism in computer-aided drug design. J Recept Signal Transduct Res 23:361–371

    Article  CAS  Google Scholar 

  2. Elgueor J, Marzin C, Katritzky AR, Lind P (1975) The tautomerism of heterocycles. Adv Heterocycl Chem Suppl 1:1–656

    Google Scholar 

  3. Beak P (1997) Energies and alkylations of tautomeric hetericyclic compounds: old problems—new answers. Acc Chem Res 10:186–192

    Article  Google Scholar 

  4. Oellien F, Cramer J, Bayer C, Ihlenfeldt WD, Selzer PM (2006) The impact of tautomer forms on pharmacophore-based virtual screening. J Chem Inf Model 46:2342–2354

    Article  CAS  Google Scholar 

  5. Seidel T, Wolber G, Langer T (2008) Tautomerism in structure-based 3D pharmacophore modeling. Chem Cent J 2(suppl):11

    Article  Google Scholar 

  6. Milletti F, Storchi L, Sforna G, Cross S, Cruciani G (2009) Tautomer enumeration and stability prediction for virtual screening on large chemical databases. J Chem Inf Model 49:68–75

    Article  CAS  Google Scholar 

  7. Marvin C (2010) http://www.chemaxon.com/product/tautomer.html. Accessed 13 Jan 2010

  8. SPARC (2010) http://sparc.chem.uga.edu/sparc/. Accessed 15 March 2010

  9. Watson JD (1980) In: Stent GS (ed) The double helix; a personal account of the discovery of the structure of DNA, a norton critical edition. W. W. Norton, New York

    Google Scholar 

  10. Othersen OG, Waibel R, Lanig H, Gmeiner P, Clark T (2006) An SCRF-DFT and NMR comparison of tetracycline and 5a, 6-anhydrotetracycline in solution. J Phys Chem B 110:24766–24774

    Article  CAS  Google Scholar 

  11. Milletti F, Storchi L, Sforna G, Cruciani G (2007) J Chem Inf Model 47:2172–2181

    Article  CAS  Google Scholar 

  12. Kramer C, Beck B, Clark T (2010) Insolubility classification with accurate prediction probabilities using a MetaClassifier. J Chem Inf Model 50:404–414

    Article  CAS  Google Scholar 

  13. Clark T (2003) Modelling the chemistry: time to break the mould? In: Ford M, Livingstone D, Dearden J, van der Waterbeemd H (eds) EuroQSAR 2002: designing drugs and crop protectants. Blackwell, Oxford, pp 111–121

    Google Scholar 

  14. Kramer C, Beck B, Clark T (2010) A surface-integral model for logPOW. J Chem Inf Model 50:429–436. doi:10.1021/ci900377e

    Article  CAS  Google Scholar 

  15. Kramer C, Heinisch T, Fligge T, Beck B, Clark T (2009) A consistent kinetic solubility dataset for early-phase drug discovery. ChemMedChem 4:1529–1536

    Article  CAS  Google Scholar 

  16. Ho J, Coote ML (2010) A universal approach for continuum solvent pKa calculations: are we there yet? Theor Chem Acc 125:3–21

    Article  CAS  Google Scholar 

  17. Curtiss LA, Raghavachari K, Trucks GW, Pople JA (1991) Gaussian-2 theory for molecular energies of first- and second-row compounds. J Chem Phys 94:7221–7230

    Article  CAS  Google Scholar 

  18. Curtiss LA, Raghavachari K, Pople JA (1993) Gaussian-2 theory using reduced Møller–Plesset orders. J Chem Phys 98:1293–1298

    Article  CAS  Google Scholar 

  19. Curtiss LA, Raghavachari K, Pople JA (1993) The accurate determination of enthalpies of formation. Chem Phys Lett 214:183–185

    Article  CAS  Google Scholar 

  20. Curtiss LA, Raghavachari K, Redfern PC, Rassolov V, Pople JA (1998) Gaussian-3 (G3) theory for molecules containing first and second-row atoms. J Chem Phys 109:7764–7776

    Article  CAS  Google Scholar 

  21. Curtiss LA, Redfern PC, Raghavachari K, Rassolov V, Pople JA (1999) Gaussian-3 theory using reduced Møller–Plesset order. J Chem Phys 110:4703–4709

    Article  CAS  Google Scholar 

  22. Baboul AG, Curtiss LA, Redfern PC, Raghavachari K (1999) Gaussian-3 theory using density functional geometries and zero-point energies. J Chem Phys 110:7650–7657

    Article  CAS  Google Scholar 

  23. Curtiss LA, Redfern PC, Raghavachari K (2007) Approximating correlation effects in multiconfigurational self-consistent field calculations of spin–spin coupling constants. J Chem Phys 126:084108

    Article  Google Scholar 

  24. Curtiss LA, Redfern PC, Raghavachari K (2007) Gaussian-4 theory using reduced order perturbation theory. J Chem Phys 127:124105

    Article  Google Scholar 

  25. Martin JML (2005) Computational thermochemistry: a brief overview of quantum mechanical approaches. Ann Rep Comput Chem 1:31–43

    Article  CAS  Google Scholar 

  26. Danikiewicz W (2009) How reliable are gas-phase proton affinity values of small carbanions? A comparison of experimental data with values calculated using Gaussian-3 and CBS compound methods. Int J Mass Spectr 285:86–94

    Article  CAS  Google Scholar 

  27. Dixon DA, Lias SG (1987) Absolute values of gas proton affinities and basicities of molecules: a comparison between theory and experiment. Mol Struct Energ 2:269–314

    CAS  Google Scholar 

  28. Burkert U, Allinger NL (1982) Molecular mechanics, ACS Monograph 177. American Chemical Society, Washington, DC

    Google Scholar 

  29. Allinger NL, Chen K, Lii J-H (1996) An improved force field (MM4) for saturated hydrocarbons. J Comput Chem 17:642–668

    Article  CAS  Google Scholar 

  30. Nevins N, Chen K, Allinger NL (1996) Molecular mechanics (MM4) calculations on alkenes. J Comput Chem 17:669–694

    CAS  Google Scholar 

  31. Nevins N, Lii JH, Allinger NL (1996) Molecular mechanics (MM4) calculations on conjugated hydrocarbons. J Comput Chem 17:695–729

    CAS  Google Scholar 

  32. Allinger NL, Chen K, Katzenellenbogen JA, Wilson SR, Anstead GM (1996) J Comput Chem 17:747–755

    Article  CAS  Google Scholar 

  33. Reindl B, Clark T, Schleyer PVR (1996) A new method for empirical force field calculations on localized and delocalized carbocations. J Comput Chem 17:1406–1430

    Article  CAS  Google Scholar 

  34. Reindl B, Clark T, Schleyer PVR (1996) Empirical force-field and ab initio calculations on delocalized open chain cations. J Comput Chem 18:28–44

    Article  Google Scholar 

  35. Reindl B, Clark T, Schleyer PVR (1998) Empirical force field and ab initio calculations on allyl cations. J Comput Chem 18:533–551

    Article  Google Scholar 

  36. Reindl B, Clark T, Schleyer PVR (1998) Modern molecular mechanics and ab initio calculations on benzylic and cyclic delocalized cations. J Phys Chem A 102:8953–8963

    Article  CAS  Google Scholar 

  37. Sprague JT, Tai JC, Yuh Y, Allinger NL (1987) The MMP2 calculational method. J Comput Chem 8:581–603

    Article  CAS  Google Scholar 

  38. Warshel A, Kato M, Pisliakov AV (2007) Polarizable force fields: history, test cases, and prospects. J Chem Theor Comput 3:2034–2045

    Article  CAS  Google Scholar 

  39. Patel S, Brooks CL III (2006) Fluctuating charge force fields: recent developments and applications from small molecules to macromolecular biological systems. Mol Sim 32:231–249

    Article  CAS  Google Scholar 

  40. Halgren TA, Damm W (2001) Polarizable force fields. Curr Opin Struct Biol 2001(11):236–242

    Article  Google Scholar 

  41. Devereux M, Plattner N, Meuwly M (2009) Application of multipolar charge models and molecular dynamics simulations to study stark shifts in inhomogeneous electric fields. J Phys Chem A 113:13199–13209

    Article  CAS  Google Scholar 

  42. Plattner N, Bandi T, Doll JD, Freeman DL, Meuwly M (2008) MD simulations using distributed multipole electrostatics: structural and spectroscopic properties of CO- and methane-containing clathrates. Mol Phys 106:1675–1684

    Article  CAS  Google Scholar 

  43. Halgren TA (1996) Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94. J Comput Chem 17:490–519

    Article  CAS  Google Scholar 

  44. Halgren TA (1996) Merck molecular force field. II. MMFF94 van der Waals and electrostatic parameters for intermolecular interactions. J Comput Chem 17:520–552

    Article  CAS  Google Scholar 

  45. Halgren TA (1996) Merck molecular force field. III. Molecular geometries and vibrational frequencies for MMFF94. J Comput Chem 17:553–586

    Article  CAS  Google Scholar 

  46. Halgren TA, Nachbar RB (1996) Merck molecular force field. IV. conformational energies and geometries for MMFF94. J Comput Chem 17:587–615

    CAS  Google Scholar 

  47. Halgren TA (1996) Merck molecular force field. V. Extension of MMFF94 using experimental data, additional computational data, and empirical rules. J Comput Chem 17:616–641

    Article  CAS  Google Scholar 

  48. Tomasi J, Persico M (1994) Molecular interactions in solution: an overview of methods based on continuous distributions of the solvent. Chem Rev 94:2027–2094

    Article  CAS  Google Scholar 

  49. Kelly CP, Cramer CJ, Truhlar DG (2005) SM6: a density functional theory continuum solvation model for calculating aqueous solvation free energies of neutrals, ions, and solute–water clusters. J Chem Theor Comput 1:1133–1152

    Article  CAS  Google Scholar 

  50. Thompson JD, Cramer CJ, Truhlar DG (2005) Density-functional theory and hybrid density-functional theory continuum solvation models for aqueous and organic solvents: universal SM5.43 and SM5.43R solvation models for any fraction of Hartree-Fock exchange. Theor Chem Acc 113:107–131

    Article  CAS  Google Scholar 

  51. Giesen DJ, Hawkins GD, Liotard DA, Cramer CJ, Truhlar DG (1997) A universal model for the quantum mechanical calculation of free energies of solvation in non-aqueous solvents. Theor Chem Acc 98:85–109

    CAS  Google Scholar 

  52. Tomasi J, Mennucci B, Cammi R (2005) Quantum mechanical continuum solvation models. Chem Rev 105:2999–3094

    Article  CAS  Google Scholar 

  53. Viswanadhan VN, Ghose AK, Wendoloski JJ (2000) Estimating aqueous solvation and lipophilicity of small organic molecules: a comparative overview of atom/group contribution methods. Perspect Drug Discov Design 19:85–98

    Article  CAS  Google Scholar 

  54. Klamt A, Schüürmann G (1993) COSMO: a new approach to dielectric screening in solvents with explicit expressions for the screening energy and its gradient. J Chem Soc Perkin Trans 2:799–805

    Google Scholar 

  55. Soteras I, Curutchet C, Bidon-Chanal A, Orozco M, Luque FJ (2005) Extension of the MST model to the IEF formalism: HF and B3LYP parametrizations. J Mol Struct (THEOCHEM) 727:29–40

    Article  CAS  Google Scholar 

  56. Curutchet C, Orozco M, Luque FJ (2001) Solvation in octanol: parametrization of the continuum MST model. J Comput Chem 22:1180–1193

    Article  CAS  Google Scholar 

  57. Pierotti RA (1976) A scaled particle theory of aqueous and nonaqueous solutions. Chem Rev 76:717–726

    Article  CAS  Google Scholar 

  58. Hansen-Goos H, Roth R, Mecke K, Dietrich S (2007) Solvation of proteins: linking thermodynamics to geometry. Phys Rev Lett 99:128101

    Article  Google Scholar 

  59. Hansen-Goos H, Mecke K (2009) Fundamental measure theory for inhomogeneous fluids of nonspherical hard particles. Phys Rev Lett 102:018302

    Article  Google Scholar 

  60. Marenich AV, Cramer CJ, Truhlar DJ (2009) Universal solvation model based on solute electron density and on a continuum model of the solvent defined by the bulk dielectric constant and atomic surface tensions. J Phys Chem B 113:6378–6396

    Article  CAS  Google Scholar 

  61. Cramer CJ, Truhlar DJ (2008) A universal approach to solvation modeling. Acc Chem Res 41:760–768

    Article  CAS  Google Scholar 

  62. Torrie G, Valleau J (1974) Monte Carlo free energy estimates using non-Boltzmann sampling: application to the sub-critical Lennard-Jones fluid. Chem Phys Lett 28:578–581

    Article  CAS  Google Scholar 

  63. Cheng A, Best SA, Merz KM, Reynolds CH (2000) GB/SA water model for the Merck molecular force field (MMFF). J Mol Graph Model 18:273–282

    Article  CAS  Google Scholar 

  64. Wang J, Wolf RM, Caldwell JW, Kollman PA, Case DA (2004) Development and testing of a general amber force field. J Comput Chem 25:1157–1174

    Article  CAS  Google Scholar 

  65. Reulecke I, Lange G, Albrecht J, Klein R, Rarey M (2008) Towards an integrated description of hydrogen bonding and dehydration: decreasing false positives in virtual screening with the HYDE scoring function. ChemMedChem 3:885–897

    Article  CAS  Google Scholar 

  66. Politzer P, Murray JS, Concha MC (2008) σ-hole bonding between like atoms; a fallacy of atomic charges. J Mol Model 14:659–665

    Article  CAS  Google Scholar 

  67. Clark T, Hennemann M, Murray JS, Politzer P (2007) Halogen bonding: the σ-hole. J Mol Model 13:291–296

    Article  CAS  Google Scholar 

  68. Wesolowski TA, Warshel A (1993) Frozen density functional approach for ab initio calculations of solvated molecules. J Phys Chem 97:8050–8053

    Article  CAS  Google Scholar 

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  1. Computer-Chemie-Centrum, Friedrich-Alexander-Universität Erlangen-Nürnberg, Nägelsbachstraße 25, 91052, Erlangen, Germany

    Timothy Clark

  2. Centre for Molecular Design, University of Portsmouth, Mercantile House, Hampshire Avenue, Portsmouth, PO1 2EG, UK

    Timothy Clark

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Clark, T. Tautomers and reference 3D-structures: the orphans of in silico drug design. J Comput Aided Mol Des 24, 605–611 (2010). https://doi.org/10.1007/s10822-010-9342-8

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  • DOI: https://doi.org/10.1007/s10822-010-9342-8

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