Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Janin, J., Elusive affinities, Proteins: Struct. Funct. Genet., 21 (1995) 30–39.
Ajay and Murcko. M.A., computational methods to predict binding free energy in Ligand-receptor complexes J. Med. Chem., 38 (1996)4953–4967.
Böhm, H.-J. and Klebe, G., What can we from molecular recognition inprotein-ligand complexes for the design of new drugs? Angew. Chem. Int. Ed. Engl. 35 (1996) 2588–2614.
Verlinde C.L.M.J. and Hol, W.G.J., Structure-based drug design: Progress, results and challenges, Structure 2 (1994) 577–587.
Böhm, H.-J., Current computational tools for de novo ligand design. Curr, Opin. Biotech., 7 (1996) 433–436.
Clark. M., Cramer, R.D., III, Jones. D.M., Patterson, D.E. and Simeroth, P.E., comparative molecular field analysis (CoMFA): I. Effect of shape on binding of steriods to carrier proteins, J. Am. Chem. Soc., 110 (1988) 5959–5967.
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.
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 (NI), 1994, 137–149.
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 constants, Proteins: struct. Funct. Genet., 21 (1995) 22–29.
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.
Kollman. P., Free energy calculations: Applications to chemical and biochemical phenomena, Chem. Rev., 93 (1993) 2395–2417.
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.
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.
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.
Finkelstein, A.V. and Janin, J.. The price of lost freedom: Entropy of biomolecular complex formation, Protein Eng., 3 (1989) 1–3.
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.
Kuntz, I.D., Blancy, 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.
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.
Meng, E.C., Shoichet, B.K. and Kuntz, I.D., Automateddocking using grid-based energy evaluation, J. Comp. Chem., 13 (1992) 505–524.
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.
Grootenhuis, P.D.J. and van Galen, P.J.M., Correlationof binding affinitieswith non-bonded interaction energies of thrombin-inhibitor complexes. Acta Cryst., D51 (1995) 560–566.
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.
Kurinov, I.V. and Harrison, R.W., Prediction of new serine proteinase inhibitors, Nature Struct. Biol., 1 (1994) 735–743.
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.
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
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 inhibirors: Application to peptidomimetic inhibitors of the human immunodeficiency virus type 1 protease, J. Med. Chem., 39 (1996) 705–712.
Ortiz, A.R., Pisabarro, M.T., Gago, F. and Wade, R.C., Prediction of drug bindingaffinitiesby comparative binding energy analysis, J. Med. Chem., 38 (1995) 2681–2691.
Mitchell, T.J., An algorithm for the construction of ‘D-optimal’ experimental designs, Technometrics, 16 (1974) 203–210.
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.
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.
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.
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.
Zhang, T. and Koshland, D.E., Jr., Computational method for relative binding energies of enzyme-substrate complexes, Prot. Sci. 5 (1996) 348–356.
Jedrzejas, M.J., Singh, S., Brouillette, W.J., Air, G.M. and Luo, M., A strategy for theoretical binding constant, K i, calculations for neuramidase aromatic inhibitors designed on the basis ofthe active site structure of influenza virus neuramidase, Proteins: Struct. Funct. Genet. 23 (1995) 264–277.
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.
Böhm, H.-J., The development of a simple empiric scoring function to estimate the binding constant for a protein-ligandcomplex of known three-dimensional structure, J. Comput.-Aided Mol. Design, 8 (1994) 243–256.
Dougnerty, D.A. and Stauffer, D.A., Acetylcholine binding by a synthetic receptor: Implicationsfor biological recognition, Science, 250 (1990) 1558–1560.
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.
Verkhivker, G.M., Rejto, P.A., Gehlhaar, D.K. and Freer, S.T., Exploring the energy landscapes of molecular recognition by a genetic algorithm: Analysisof the requirements for robust docking of HIV-1 protease and FKBP-12 complexes, Proteins: Struct. Funct. Genet., 250 (1996) 342–353.
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.
Jain, A.N., Scoring noncovalent protein-ligand interactions: A continuous differentiable function tuned to compute binding affinites, J. Cornput.-Aided Mol. Design, 10 (1996) 427–440.
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.
Bohacek, R.S. and McMartin, C. Definitionand 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.
Eisenberg, D. and McLachlan, A.D., Solvation energy in proteinfolding and binding, Nature, 319 (1986) 199–203.
Horton, N. and Lewis, M., Calculation of the free energy of association forprotein complexes. Prot. Sci., 1(1992) 169–181.
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.
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.
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.
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.
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.
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 I binding affinity, Protein Eng. 8 (1995) 677–691
DeWitte, R.S. and Shakhnovich. E.I., SMoG: De novo design method based on simple, fast, and accurate free enerrgy estimates: I. Methodology and supporting evidence, J. Am. Chem. Soc., 118 (1996s) 11733–11744.
Moult, J.. The current state of the art in proteiin structure prediction, Curr. Opin. Biotech., 7 (1996) 322–127.
Eisenberg, D. Into the black of night, Nature Struct. Biol., 4 (1997)95–97.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 KluwerAcademic Publishers
About this chapter
Cite this chapter
Knegtel, R.M.A., Grootenhuis, P.D.J. (2002). Binding Affinities and Non-Bonded Interaction Energies. In: Kubinyi, H., Folkers, G., Martin, Y.C. (eds) 3D QSAR in Drug Design. Three-Dimensional Quantitative Structure Activity Relationships, vol 2. Springer, Dordrecht. https://doi.org/10.1007/0-306-46857-3_6
Download citation
DOI: https://doi.org/10.1007/0-306-46857-3_6
Publisher Name: Springer, Dordrecht
Print ISBN: 978-0-7923-4790-3
Online ISBN: 978-0-306-46857-5
eBook Packages: Springer Book Archive