Binding affinities and non-bonded interaction energies

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References

  1. 1.

    Janin, J., Elusive affinities, Proteins: Struct. Funct. Genet., 21 (1995) 30–39.

    Google Scholar 

  2. 2.

    Ajay and Murcko, M.A., Computational methods to predict binding free energy in ligand-receptor complexes, J. Med. Chem., 38 (1996) 4953–4967.

    Google Scholar 

  3. 3.

    Böhm, H.-J. and Klebe, G., What can we learn from molecular recognition in protein-ligand complexes for the design of new drugs?, Angew. Chem. Int. Ed. Engl. 35 (1996) 2588–2614.

    Google Scholar 

  4. 4.

    Verlinde, C.L.M.J. and Hol, W.G.J., Structure-based drug design: Progress, results and challenges, Structure, 2 (1994) 577–587.

    Google Scholar 

  5. 5.

    Böhm, H.-J., Current computational tools for de novo ligand design, Curr. Opin. Biotech., 7 (1996) 433–436.

    Google Scholar 

  6. 6.

    Clark, M., Cramer, R.D., III, Jones, D.M., Patterson, D.E. and Simeroth, P.E., Comparative molecular field analysis (CoMFA): 1. Effect of shape on binding of steroids to carrier proteins, J. Am. Chem. Soc., 110 (1988) 5959–5967.

    Google Scholar 

  7. 7.

    Clark, M., Cramer, R.D., III, Jones, D.M., Patterson, D.E. and Simeroth, P.E., Comparative molecular field analysis (CoMFA): 2. Towards its use with 3D-structural databases, Tetrahedron Comput. Methodol., 3 (1990) 47–59.

    Google Scholar 

  8. 8.

    Grootenhuis, P.D.J. and van Helden, S.P., Rational approaches towards protease inhibition: Predicting the binding of thrombin inhibitors, In Wipff, G. (Ed.) Computational approaches in supramolecular chemistry, Kluwer Academic Publishers, Dordrecht (N1), 1994, 137–149.

    Google Scholar 

  9. 9.

    Perakyla, M. and Pakkanen, T.A., Model assembly study of the ligand binding by p-hydroxybenzoate hydroxylase: Correlation between the calculated binding energies and the experimental dissociation con-stants, Proteins: Struct. Funct. Genet., 21 (1995) 22–29.

    Google Scholar 

  10. 10.

    Cramer, C.J. and Truhlar, D.G., Continuum solvation models: Classical and quantum mechanical implementations, In Lipkowitz, K.B. and Boyd, D.B. (Eds.) Reviews in computational chemistry, 6, VCH Publishers Inc., New York, 1995, pp. 1–72.

    Google Scholar 

  11. 11.

    Kollman, P., Free energy calculations: Applications to chemical and biochemical phenomena, Chem. Rev., 93 (1993) 2395–2417.

    Google Scholar 

  12. 12.

    Rao, B.G., Tilton, R.F. and Singh, U.C., Free energy perturbation studies on inhibitor binding to HIV-1 proteinase, J. Am. Chem. Soc., 114 (1992) 4447–4452.

    Google Scholar 

  13. 13.

    Aqvist, J. and Mowbray, S.L., Sugar recognition by a glucose/galactose receptor: Evaluation of binding energetics from molecular dynamics simulations, J. Biol. Chem., 270 (1995) 9978–9981.

    Google Scholar 

  14. 14.

    Liu, H.Y., Mark, A.E. and van Gunsteren, W.F., Estimating the relative free energy of different molecular stawtes with respect to a single reference state, J. Phys. Chem., 100 (1996) 9485–9494.

    Google Scholar 

  15. 15.

    Finkelstein, A.V. and Janin, J., The price of lost freedom: Entropy of biomolecular complex formation, Protein Eng., 3 (1989) 1–3.

    Google Scholar 

  16. 16.

    Weiner, S.J., Kollman, P.A., Case, D.A., Singh, U.C., Ghio, C., Alagona, G., Profeta, S. and Weiner, P.K. A new force field for molecular mechanics simulation, J. Am. Chem. Soc., 106 (1984) 765–784.

    Google Scholar 

  17. 17.

    Kuntz, I.D., Blaney, J.M., Oatley, S.J., Langridge, R. and Ferrin, T.E., A geometric approach to macro-molecule- ligand interactions, J. Mol. Biol., 161 (1982) 269–288.

    Google Scholar 

  18. 18.

    DesJarlais, R.L., Sheridan, R.P., Seibel, G.L., Dixon, J.S., Kuntz, I.D. and Venkataraghavan, R., Using shape complementarily as an initial screen in designing ligands for a receptor binding site of known three-dimensional structure, J. Med. Chem. 31 (1988) 722–729.

    Google Scholar 

  19. 19.

    Meng, E.C., Shoichet, B.K. and Kuntz, I.D., Automated docking using grid-based energy evaluation, J. Comp. Chem., 13 (1992) 505–524.

    Google Scholar 

  20. 20.

    Ring, C.S., Sun, E., McKerrow, J.H., Lee, G.K., Rosenthal, P.J., Kuntz, I.D. and Cohen, F.E., Structure-based inhibitor design by using protein models for the development of antiparasitic agents, Proc. Natl. Acad. Sci. USA, 90 (1993) 3583–3587.

    Google Scholar 

  21. 21.

    Grootenhuis, P.D.J. and van Galen, P.J.M., Correlation of binding affinities with non-bonded interaction energies of thrombin-inhibitor complexes, Acta Cryst., D51 (1995) 560–566.

  22. 22.

    Brooks, B., Bruccoleri, R., Olafson, B., States, D., Swaninathan, S. and Karplus, M., Charmm: A program for macromolecular energy minimization and molecular dynamics calculations, J. Comp. Chem., 4 (1983) 187–217.

    Google Scholar 

  23. 23.

    Kurinov, I.V. and Harrison, R.W., Prediction of new serine proteinase inhibitors, Nature Struct. Biol., 1 (1994) 735–743.

    Google Scholar 

  24. 24.

    Rappé, A.K., Casewit, C.J., Colwell, K.S., Goddard, W.A.I. and Skiff, W.M., UFF, a full periodic table force field for molecular mechanics and molecular dynamics simulations, J. Am. Chem. Soc., 114 (1992) 10024–10046.

    Google Scholar 

  25. 25.

    Luty, B.A., Wasserman, Z.R., Stouten, P.F.W., Hodge, C.N., Zacharias, M. and McCammon, J.A., A molecular mechanics/grid method for evaluation of ligand-receptor interactions, J. Comp. Chem., 16 (1995) 454–464

    Google Scholar 

  26. 26.

    Viswanadhan, V.N., Reddy, M.R., Wlodawer, A., Varney, M.D. and Weinstein, J.N., An approach to rapid estimation of relative binding affinities of enzyme inhibitors: Application to peptidomimetic inhibitors of the human immunodeficiency virus type 1 protease, J. Med. Chem., 39 (1996) 705–712.

    Google Scholar 

  27. 27.

    Ortiz, A.R., Pisabarro, M.T., Gago, F. and Wade, R.C., Prediction of drug binding affinities by com-parative binding energy analysis, J. Med. Chem., 38 (1995) 2681–2691.

    Google Scholar 

  28. 28.

    Mitchell, T.J., An algorithm for the construction of ‘D-optimal’ experimental designs, Technometrics, 16 (1974) 203–210.

    Google Scholar 

  29. 29.

    Holloway, K.M., Wai, J.M., Halgren, T., Fitzegerald, P.M.D., Vacca, J.P., Dorsey, B.D., Levin, R.B., Thompson, W.J., Chen, L.J., deSolms, S.J., Gaffin, N., Ghosh, A.K., Giuliani, E.A., Graham, S.L., Guare, J.P., Hungate, R.W., Lyle, T.A., Sanders, W.M., Tucker, T.J., Wiggins, M., Wiscount, C.M., Woltersdorf, O.W., Young, S.D., Darke, P.L. and Zugay, J.A., A priori prediction of activity for HIV-1 protease inhibitors employing energy minimization in the active site, J. Med. Chem., 38 (1995) 305–317.

    Google Scholar 

  30. 30.

    Babu, Y.S., Ealick, S.E., Bugg, C.E., Erion, M.D., Guida, W.C., Montgomery, J.A. and Secrist, J.A., III, Structure-based design of inhibitors of purine nucleoside phosphorylase, Acta Cryst., D51 (1995) 529–535.

  31. 31.

    Jetten, M., Peters, C.A.M., Visser, A., Grootenhuis, P.D.J., van Nispen, J.W. and Ottenheijm, H.C.J., Peptide-derived transition state analogue inhibitors of thrombin; Synthesis, activity and selectivity, Bioorg. Med. Chem., 3 (1995) 1099–1114.

    Google Scholar 

  32. 32.

    Shen, J. and Wendoloski, J., Electrostatic binding energy calculation using the finite difference solution to the linearized Poisson-Boltzmann equation: Assessment of its accuracy, J. Comp. Chem., 17 (1996) 350–357.

    Google Scholar 

  33. 33.

    Zhang, T. and Koshland, D.E., Jr., Computational method for relative binding energies of enzyme- substrate complexes, Prot. Sci. 5 (1996) 348–356.

  34. 34.

    Jedrzejas, M.J., Singh, S., Brouillette, W.J., Air, G.M. and Luo, M., A strategy for theoretical binding constant, Ki, calculations for neuramidase aromatic inhibitors designed on the basis of the active site structure of influenza virus neuramidase, Proteins: Struct. Funct. Genet. 23 (1995) 264–277.

    Google Scholar 

  35. 35.

    Zacharias, M., Luty, B.A., Davis, M.E. and McCammon, J.A., Combined conformational search and finite-difference Poisson-Boltzmann approach for flexible docking: Application to an operator mutation in the lambda repressor-operator complex, J. Mol. Biol., 238 (1994) 455–465.

    Google Scholar 

  36. 36.

    Böhm, H.-J., The development of a simple empiric scoring function to estimate the binding constant for a protein-ligand complex of known three-dimensional structure, J. Comput.-Aided Mol. Design, 8 (1994) 243–256.

    Google Scholar 

  37. 37.

    Dougnerty, D.A. and Stauffer, D.A., Acetylcholine binding by a synthetic receptor: Implications for bio-logical recognition, Science, 250 (1990) 1558–1560.

    Google Scholar 

  38. 38.

    Head, R.D., Smythe, M.L., Oprea, T.I., Waller, C.L., Green, S.M. and Marshall, G.R., VALIDATE: A new method for the receptor-based prediction of binding affinities of novel ligands, J. Am. Chem. Soc., 118 (1996) 3959–3969.

    Google Scholar 

  39. 39.

    Verkhivker, G.M., Rejto, P.A., Gehlhaar, D.K. and Freer, S.T., Exploring the energy landscapes of molecular recognition by a genetic algorithm: Analysis of the requirements for robust docking of HIV-1 protease and FKBP-12 complexes, Proteins: Struct. Funct. Genet., 250 (1996) 342–353.

    Google Scholar 

  40. 40.

    Knegtel, R.M.A., Rullman, J.A.C., Boelens, R. and Kaptein, R., MONTY: A Monte Carlo approach to protein-DNA recognition, J. Mol. Biol., 235 (1994) 318–324.

    Google Scholar 

  41. 41.

    Jain, A.N., Scoring noncovalent protein-ligand interactions: A continuous differentiable function tuned to compute binding affinities, J. Comput.-Aided Mol. Design, 10 (1996) 427–440.

    Google Scholar 

  42. 42.

    Novotny, J., Bruccoleri, R.E. and Saul, F.A., On the attribution of binding energy in antigen-antibody complex MCPC 603.D1.3 and Hyhel-5,Biochemistry, 28 (1989) 4735–4749.

    Google Scholar 

  43. 43.

    Bohacek, R.S. and McMartin, C. Definition and display of steric, hydrophobic and hydrogen-bonding properties of ligand binding sites in proteins using Lee and Richards' accessible surface: Validation of a high-resolution graphical tool for drug design, J. Med. Chem., 35 (1992) 1671–1684.

    Google Scholar 

  44. 44.

    Eisenberg, D. and McLachlan, A.D., Solvation energy in protein folding and binding, Nature, 319 (1986) 199–203.

    Google Scholar 

  45. 45.

    Horton, N. and Lewis, M., Calculation of the free energy of association for protein complexes, Prot. Sci., 1 (1992) 169–181.

    Google Scholar 

  46. 46.

    Krystek, S., Stouch, T. and Novotny, J., Affinity and specificity of serine endopeptidase-protein inhibitor interactions: Empirical free energy calculations based on crystallographic studies, J. Mol. Biol., 234 (1993) 661–679.

    Google Scholar 

  47. 47.

    Vajda, S., Weng, Z., Rosenfeld, R. and DeLisi, C., Effect of conformational flexibility and solvation on receptor-ligand binding free energies, Biochemistry, 33 (1994) 13977–13988.

    Google Scholar 

  48. 48.

    Wallqvist, A., Jernigan, R.L. and Covell, D.G., A preference-based free energy parameterization of enzyme-inhibitor binding: Applications to HIV-1 protease inhibitor design, Prot. Sci., 4 (1995) 1881–1903.

    Google Scholar 

  49. 49.

    Wallqvist, A. and Covell, D.G., Docking enzyme-inhibitor complexes using a preference-based free energy surface, Proteins: Struct. Funct. Genet. 25 (1996) 403–419.

    Google Scholar 

  50. 50.

    Laskowski, R.A., Thornton, J.M., Humblet, C. and Singh, J., X-SITE: Use of empirically derived atom packing preferences to identify favorable interaction regions in the binding sites of proteins, J. Mol. Biol. 259 (1996) 175–201.

    Google Scholar 

  51. 51.

    Verkhivker, G., Appelt, K., Freer, S.T. and Villafranca, J.E., Empirical free energy calculations of ligand-protein crystallographic complexes: 1. Knowledge-based ligand-protein interaction potentials applied to the prediction of human immunodeficiency virus protease 1 binding affinity, Protein Eng. 8 (1995) 677–691.

    Google Scholar 

  52. 52.

    DeWitte, R.S. and Shakhnovich, E.I., SMoG: De novo design method based on simple, fast, and accurate free energy estimates: 1. Methodology and supporting evidence, J. Am. Chem. Soc., 118 (1996) 11733–11744.

    Google Scholar 

  53. 53.

    Moult, J., The current state of the art in protein structure prediction, Curr. Opin. Biotech., 7 (1996) 422–427.

    Google Scholar 

  54. 54.

    Eisenberg, D. Into the black of night, Nature Struct. Biol., 4 (1997) 95–97.

    Google Scholar 

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Knegtel, R.M., Grootenhuis, P.D. Binding affinities and non-bonded interaction energies. Perspectives in Drug Discovery and Design 9, 99–114 (1998). https://doi.org/10.1023/A:1027255820725

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Keywords

  • Polymer
  • Binding Affinity
  • Interaction Energy