Hostname: page-component-cc8bf7c57-hbs24 Total loading time: 0 Render date: 2024-12-12T01:46:50.826Z Has data issue: false hasContentIssue false
  • English
  • Français

Fundamentals of drug design from a biophysical viewpoint

Published online by Cambridge University Press:  17 March 2009

Wilfred F. Van Gunsteren ,
Paul M. King  and
Alan E. Mark
Wilfred F. Van Gunsteren
Affiliation:
Laboratory of Physical Chemistry, Swiss Federal Institute of Techonology Zürich, ETH Zentrum, CH-8092 Zurich, Switzerland
Alan E. Mark
Affiliation:
Laboratory of Physical Chemistry, Swiss Federal Institute of Techonology Zürich, ETH Zentrum, CH-8092 Zurich, Switzerland
Get access Rights & Permissions [Opens in a new window]

Extract

Drug design means many things to many people. Commercially the aim is the development of compounds that can be patented and meet a variety of regulatory standards. In drug design, for medical purposes, toxicity and bio-availability are major considerations.

Type
Research Article
Information
Quarterly Reviews of Biophysics , Volume 27 , Issue 4 , December 1994 , pp. 435 - 481
Copyright
Copyright © Cambridge University Press 1994

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Berendsen, H. J. C. (1991). Incomplete equilibration: A source of error in free energy calculations. In Proteins: Structure, Dynamics and Design(ed. Renugopalakrishnan, V.et al.), pp. 384–392. Leiden, NL: ESCOM Science Publishers B.V.CrossRefGoogle Scholar
Berendsen, H. J. C. (1993). Electrostatic interactions. In Computer Simulation of Biomolecular Systems: Theoretical and Experimental Applications, vol. 2 (ed. van Gunsteren, W. F. et al. ), pp. 161–181. Leiden, NL: ESCOM Science Publishers B.V.Google Scholar
Berkowitz, M. & McCammon, J. A. (1982). Molecular dynamics with stochastic boundary conditions. Chem. Phys. Lett. 90, 215–217.CrossRefGoogle Scholar
Beutler, T. C., Mark, A. E., Van Schaik, R. C., Gerber, P. R. & Van Gunsteren, W. F. (1994). Avoiding singularities and numerical instabilities in free energy calculations based on molecular simulations. Chem. Phys. Letters 222, 529–539.CrossRefGoogle Scholar
Beveridge, D. L. & Di Capua, F. M. (1989). Free energy via molecular simulation: Applications to chemical and biochemical systems. Ann. Rev. Biophys. Biophys. Chem. 18, 431–492.CrossRefGoogle Scholar
Böhm, H. J. (1992 a). The computer program LUDI: A new method for the de novo design of enzyme inhibitors. J. Comput.-Aided Mol. Design 6, 61–78.CrossRefGoogle Scholar
Böhm, H. J. (1992 b). LUDI: rule-based automatic design of new substituents for enzyme inhibition leads. J. Comput.-Aided Mol. Design 6, 593–606.CrossRefGoogle Scholar
Boobbyer, D. N. A., Goodford, P. J., McWhinnie, P. M. & Wade, R. C. (1989). New hydrogen-bond potentials for use in determining energetically favourable binding sites on molecules of known structure. J. Med. Chem. 32 1083–1094.CrossRefGoogle ScholarPubMed
Bowen-Jenkins, P. E., Cooper, D. L. & Richards, W. G. (1985). Ab initio computation of molecular similarity. J. Phys. Chem. 89 2195–2197.CrossRefGoogle Scholar
Brooks, C. L., Brünger, A. T. & Karplus, M. (1985). Active site dynamics in protein molecules: A stochastic boundary molecular-dynamics approach. Biopolymers 24 843–865.CrossRefGoogle ScholarPubMed
Brünger, A. T., Kuriyan, J. & Karplus, M. (1987). Crystallographic R factor refinement by molecular dynamics. Science 235 458–460.CrossRefGoogle ScholarPubMed
Burt, C. & Richards, W. G. (1990). Molecular similarity: the introduction of flexible fitting. J. Comput.-Aided Mol. Design 4 231–238.CrossRefGoogle ScholarPubMed
Burt, C., Richards, W. G. & Huxley, P. (1990). The application of molecular similarity calculations. J. Comput. Chem. 11 1139–1146.CrossRefGoogle Scholar
Carbó, R.Leyda, L. & Arnau, M. (1980). How similar is one molecule to another? An electron density measure of similarity between two molecular structures. Int. J. Quantum Chem. 17 1185–1189.CrossRefGoogle Scholar
Connolly, M. L. (1983). Solvent-accessible surfaces of proteins and nucleic acids. Science 221 709–713.CrossRefGoogle ScholarPubMed
Cooper, D. L. & Allen, N. L. (1989). A novel approach to molecular similarity. J. Comput.-Aided Mol. Design 3 253–259.CrossRefGoogle ScholarPubMed
Cramer, R. D. III, Patterson, D. E. & Bunce, J. D. (1988). Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. J. Am. Chem. Soc. 110 5950–5967.CrossRefGoogle ScholarPubMed
Crippen, G. M. & Havel, T. F. (1988). Distance geometry and molecular conformation. New York: Wiley.Google Scholar
Dang, L. X., Merz, K. M. & Kollman, P. A. (1989). Free energy calculations on protein stability: Thr-157 Val-157 mutation of T4 lysozyme. J. Am. Chem. Soc. 111 8505–8508.CrossRefGoogle Scholar
Dean, P. M. (1987). Molecular Foundations of drug-receptor interaction. Cambridge: Cambridge University Press.Google Scholar
Desjarlais, R. L., Sheridan, R. P., Dixon, J. S., Kuntz, I. D. & Venkataraghavan, R. (1986). Docking flexible ligands to macromolecular receptors by molecular shape. J. Med. Chem. 29 2149–2153.CrossRefGoogle ScholarPubMed
De Vlieg, J., Berendsen, H. J. C. & Van Gunsteren, W. F. (1989). An NMR based molecular dynamics simulation of the interaction of the lac repressor headpiece and its operator in aqueous solution. Proteins 6 104–127.CrossRefGoogle ScholarPubMed
Folkers, G., Merz, A. & Rogan, D. (1993). CoMFA, scope and limitations. In 3D QSAR in Drug Design: Theory, Methods and Applications, (ed. Kubinyi, H.), pp. 583–618. Leiden NL: ESCOM Science Publishers B.V.Google Scholar
Franke, R. (1984). Theoretical drug design methods. Amsterdam: Elsevier.Google Scholar
Fraternali, F. & Van Gunsteren, W. F. (1994). Conformational transitions of a dipeptide in water: Effects of imposed pathways using umbrella sampling techniques. Biopolymers 34 347–355.CrossRefGoogle Scholar
Frenkel, D. (1993). Monte Carlo simulations: A primer. In Computer Simulation of Biomolecular Systems: Theoretical and Experimental Applications, vol. 2 (ed. van Gunsteren, W. F.et al.), pp. 37–66. Leiden, NL: ESCOM Science Publishers B.V.Google Scholar
Frisch, M. J., Trucks, G. W., Head-Gordon, M., Gill, P. M. W., Wong, M. W., Foresman, J. B., Johnson, B. G., Schlegel, H. B., Robb, M. A., Replogle, E. S., Gomperts, R., Andres, J. L., Raghavachari, K., Binkley, J. S., Gonzalez, C., Martin, R. L., Fox, D. J., Defrees, D. J., Baker, J., Stewart, J. J. P. & Pople, J. A. (1992). Gaussian 92, Revision A. Pittsburgh: Gaussian Inc.Google Scholar
Fujita, T., Junkichi, I. & Hansch, C. (1964). A new substituent constant, π derived from partition coefficients. J. Am. Chem. Soc. 86 5175–5180.CrossRefGoogle Scholar
Fukui, F., Yanezawa, T. & Shingu, H. (1952). A molecular orbital theory of reactivity in aromatic hydrocarbons. J. Chem. Phys. 20 722–725.CrossRefGoogle Scholar
Gelin, B. R. (1993). Testing and comparison of empirical force fields: Techniques and problems. In Computer Simulation of Biomolecular Systems: Theoretical and Experimental Applications, vol. 2 (ed. van Gunsteren, W. F.et al.), pp. 127–146. Leiden, NL: ESCOM Science Publishers B.V.Google Scholar
Gerber, P. R., Mark, A. E. & Van Gunsteren, W. F. (1993). An approximate but efficient method to calculate free energy trends by computer simulation: Application to dihydrofolate reductase-inhibitor complexes. J. Computer-Aided Molecular Design 7 305–323.CrossRefGoogle ScholarPubMed
Ghose, A. K. & Crippen, G. M. (1985). Use of physico-chemical parameters in distance geometry and related three-dimensional quantitative structure-activity relationships: A demonstration using Escherichia coli dihydrofolate reductase inhibitors. J. Med. Chem. 28 3333–3346.CrossRefGoogle Scholar
Gilsqn, M. K. & Honig, B. (1991). The inclusion of electrostatic hydration energies in molecular mechanics calculations. J. Comp.-Aided Mol. Des. 5 5–20.Google Scholar
Good, A. C., Hodgkin, E. E. & Richards, W. G. (1992 a). Utilization of Gaussian functions for the rapid evaluation of molecular similarity. J. Comp. Inf. Comput. Sci. 32 188–191.Google Scholar
Good, A. C., Hodgkin, E. E. & Richards, W. G. (1992 b). Similarity screening of molecular data sets. J. Comput.-Aided Mol. Des. 6 513–520.CrossRefGoogle ScholarPubMed
Good, A. C., So, S.-S. & Richards, W. G. (1993). Structure activity relationships from molecular similarity matrices. J. Med. Chem. 36 433–438.CrossRefGoogle ScholarPubMed
Goodford, P. J. (1985). A computational procedure for determining energetically favourable binding sites on biologically important macromolecules. J. Med. Chem. 28 849–857.CrossRefGoogle ScholarPubMed
Goodsell, D. S. & Olson, A. J. (1990). Automated docking of substrates to proteins by simulated annealing. Proteins: Structure, Function and Genetics, 8 195–202.Google ScholarPubMed
Gros, P., Van Gunsteren, W. F. & Hol, W. G. J. (1990). Inclusion of thermal motion in crystallographic structures by restrained molecular dynamics. Science 249 1149–1152.CrossRefGoogle ScholarPubMed
Hammett, L. P. (1940). Physical Organic Chemistry. New York: McGraw-Hill.Google Scholar
Hansch, C., Muir, R. M., Fujita, T., Maloney, P. P., Geiger, F. & Streich, M. (1963). The correlation of biological activity of plant growth regulators and Chloromycetin derivatives with Hammett constants and partition coefficients. J. Am. Chem. Soc. 85 2817–2824.CrossRefGoogle Scholar
Hansch, C. & Fujita, T. (1964). ρ-σ-π Analysis. A method for the correlation of biological activity and chemical structure. J. Am. Chem. Soc. 86 1616–1626.CrossRefGoogle Scholar
Harvey, T. S. & Van Gunsteren, W. F. (1993). The application of chemical shift calculation to protein structure determination by NMR, Techniques in protein chemistry IV. pp. 615–622. New York: Academic Press.CrossRefGoogle Scholar
Hehre, W. J., Radom, L., Von Ragué Schleyer, P. & Pople, J. A. (1986). Ab initio molecular orbital theory. New York: Wiley.Google Scholar
Hodgkin, E. E. & Richards, W. G. (1987). Molecular similarity based on electrostatic potential and electric field. Int.J. Quantum Chem.: Quantum Biol. Symp. 14 105–110.CrossRefGoogle Scholar
Hodgkin, E. E., Miller, A. & Whittaker, M. (1993). A Monte Carlo pharmacophore generation procedure: Application to the human PAF receptor. J. Comp.- Aided Mol. Design 7 515–534.CrossRefGoogle Scholar
Hopfinger, A. J. & Burke, B. J. (1990). Molecular shape analysis: A formalism to quantitatively establish spatial molecular similarity. In Concepts and applications of molecular similarity (ed. Johnson, M. A.et al.), pp. 173–209. New York: Wiley.Google Scholar
Huber, T., Torda, A. E. & Van Gunsteren, W. F. (1994). Local elevation: A method for improving the searching properties of molecular dynamics simulation. J. Comp.-Aided Mol. Design, in press.CrossRefGoogle ScholarPubMed
Kang, Y. K., Gibson, K. D., Némethy, G. & Scheraga, H. A. (1988). Free energies of hydration of solute molecules. 4. Revised treatment of the hydration shell model. J. Phys. Chem. 92 4739–4742.CrossRefGoogle Scholar
Kaptein, R., Zuiderweg, E. R. P., Scheek, R. M., Boelens, R. & Van Gunsteren, W. F. (1985). A protein structure from nuclear magnetic resonance data: lac repressor headpiece. J. Mol. Biol. 182 179–182.CrossRefGoogle ScholarPubMed
Kellogg, G. E., Semus, S. F. & Abraham, D. J. (1991). HINT: A new method of empirical hydrophobic field calculation for CoMFA. J. Comp. Aided. Mol. Design 5 545–552.CrossRefGoogle ScholarPubMed
Kim, K. H. (1991). A novel method of describing hydrophobic effects directly from 3D structures in 3D-quantitative structure-activity relationship studies. Med. Chem. Res. 1 259–264.Google Scholar
Kim, H. K., Greco, G., Novellino, E., Silipo, C. & Vittoria, A. (1993). Use of the hydrogen bond potential function in a comparative molecular field analysis (CoMFA) on a set of benzodiazepines. J. Comp. Aided. Mol. Design 7 263–280.CrossRefGoogle Scholar
King, P. M. (1993). Free energy via molecular simulation: A primer. In Computer Simulation of Biomolecular Systems: Theoretical and Experimental Applications, vol. 2 (ed. van Gunsteren, W. F.et al.), pp. 267–314. Leiden, NL: ESCOM Science Publishers B.V.Google Scholar
King, P. M., Spycher, R. M. & Van Gunsteren, W. F. (1993). Structure elucidation from rotation spectra: a penalty function approach. Chem. Phys. Letters 203 88–92.CrossRefGoogle Scholar
Klebe, G. & Abraham, U. (1993). On the prediction of binding properties of drug molecules by comparative molecular field analysis. J. Med. Chem. 36 70–80.CrossRefGoogle ScholarPubMed
Kubinyi, H. (1993). QSAR: Hansch analysis and related approaches. Weinheim, Germany: VCH.CrossRefGoogle Scholar
Kuczera, K., Gao, J., Tidor, B. & Karplus, M. (1990). Free energy of sickling: A simulation analysis. Proc. Natl. Acad. Sci. 87 8481–8485.CrossRefGoogle ScholarPubMed
Kuntz, I. D. (1992). Structure-based strategies for drug design and discovery. Science 257 1078–1082.CrossRefGoogle ScholarPubMed
Kuntz, I. D., Blaney, J. M., Oatley, S. J., Langridge, R. & Ferrin, T. E. (1982). A geometric approach to macromolecular-ligand interactions. J. Mol. Biol. 161 269–288.CrossRefGoogle Scholar
Leach, A. R., Prout, K. & Dolata, D. P. (1990). The application of artificial intelligence to the conformational analysis of strained molecules. J. Comp. Chem. 11 680–693.CrossRefGoogle Scholar
Mark, A. E. & Van Gunsteren, W. F. (1994 a). Decomposition of the free energy of a system in terms of specific interactions: Implications for theoretical and experimental studies. J. Mol. Biol. 240 167–176.CrossRefGoogle ScholarPubMed
Mark, A. E. & Van Gunsteren, W. F. (1994 b). Free energy calculations in drug design: A practical guide. To appear in Perspectives in Drug Design. Proceedings of the 9th Intl. Roundtable at Turnberry, Scotland.Google Scholar
Mark, A. E., Van Gunsteren, W. F. & Berendsen, H. J. C. (1991). Calculation of relative free energy via indirect pathways. J. Chem. Phys. 94 3808–3816.CrossRefGoogle Scholar
Mark, A. E., Van Helden, S. P., Smith, P. E., Janssen, L. H. M. & Van Gunsteren, W. F. (1994). Convergence properties of free energy calculations: α-cyclodextrin complexes as a case study. J. Am. Chem. Soc., 116 6293–6302.CrossRefGoogle Scholar
Martin, Y. C. (1978). Quantitative drug design: A critical introduction. New York: Marcel Dekker.Google Scholar
Martin, Y. C. (1991). Computer-assisted rational drug design. Methods in Enzymology 203 587–613–CrossRefGoogle ScholarPubMed
Mattos, C., Rasmussen, B., Ding, X., Petsko, G. A. & Ringe, D. (1994). Analogous inhibitors of elastase do not always bind analogously. Nature: Struct. Biol. 1 55–58.Google Scholar
Miyamoto, S. & Kollman, P. A. (1993). Absolute and relative binding free energy calculations of the interaction of biotin and its analogs with streptavidin using molecular dynamics/free energy perturbation approaches. Proteins: Struct. Fund. Genet. 16 226–245.CrossRefGoogle ScholarPubMed
Moon, J. B. & Howe, J. W. (1991). Computer design of bioactive molecules: A method for receptor based de novo ligand design. Proteins: Struct. Fund. Genet. 1 314–328.CrossRefGoogle Scholar
Nishibata, Y. & Itai, A. (1991). Automatic creation of drug candidate structures based on receptor structure. Starting point for artificial lead generation. Tetrahedron 47 8985–8990.CrossRefGoogle Scholar
Ooi, W., Oobatake, M.Némethy, G. & Scheraga, H. A. (1987). Accessible surface areas as a measure of the thermodynamic parameters of hydration of peptides. Proc. Natl. Acad. Sci. USA 84 3086–3090.CrossRefGoogle ScholarPubMed
Parr, R. G. & Yang, W. (1989). Density-Functional Theory of Atoms and Molecules. Oxford: Oxford University Press.Google Scholar
Pearlman, D. A. & Murcko, M. A. (1993). Concepts: New dynamic algorithm for de novo drug suggestion. J. Comp. Chem. 14 1184–1193.CrossRefGoogle Scholar
Pickersgill, R. W. (1988). A rapid method of calculating charge-charge interaction energies in proteins. Protein Engineering 2 247–248.CrossRefGoogle ScholarPubMed
Prod'Hom, B. & Karplus, M. (1993). The nature of the ion binding interactions in EF-hand peptide analogs: free energy simulation of Asp to Asn mutations. Protein Engineering 6 585–592.CrossRefGoogle ScholarPubMed
Richards, W. G. (1983). Quantum Pharmacology 2nd edn.London: Butterworths.Google Scholar
Rotstein, S. H. & Murcko, M. A. (1993). GenStar: A method for de novo drug design. J. Comp. Aided. Mol. Design 7 23–43.CrossRefGoogle ScholarPubMed
Rusinko, A. III, Skell, J. M., Balducci, R., McGarity, C. M. & Pearlman, R. S. (1988). CONCORD, a program for the rapid generation of high quality approximate 3-dimensional molecular structures. The University of Texas and Austin and Tripos Associates, St. Louis, MO, USA.Google Scholar
Rutenber, E., Fauman, E. B., Keenam, R. J., Fong, S., Furth, P. S., Ortiz de Montellano, P. R., Meng, E., Kuntz, I. D., DE Camp, D. L., Salto, R., Rose, J. R., Craik, C. S. & Stroud, R. M. (1993). Structure of a non-peptide inhibitor complexed with HIV-i protease. J. Biol. Chem. 268 15343–15346.CrossRefGoogle Scholar
Scheek, R. M., Torda, A. E., Kemmink, J. & Van Gunsteren, W. F. (1991). Structure determination by NMR: The modelling of NMR parameters as ensemble averages. In Computational Aspects of the Study of Biological Macromolecules by Nuclear Magnetic Resonance Spectroscopy (ed. Hoch, J. C.et al.), pp. 209–217. New York: NATO ASI Series A225, Plenum Press.CrossRefGoogle Scholar
Scheraga, H. A. (1993). Searching conformational space. In Computer Simulation of Biomolecular Systems: Theoretical and Experimental Applications, vol. 2 (ed. van Gunsteren, W. F.et al.), pp. 231–248. Leiden, NL: ESCOM Science Publishers B.V.Google Scholar
Schiffer, C. A., Caldwell, J. W., Stroud, R. M. & Kollman, P. A. (1992). Inclusion of solvation free energy with molecular mechanics energy: alanyl dipeptide as a test case. Protein Science 1 396–400.CrossRefGoogle ScholarPubMed
Sharp, K. A. (1991). Incorporating solvent and ion screening into molecular dynamics using the finite-difference Poisson-Boltzmann method. J. Comput. Chem. 12 454–468.CrossRefGoogle Scholar
Sharp, K. A. (1993). Inclusion of solvent effects in molecular mechanics force fields. In Computer Simulation of Biomolecular Systems: Theoretical and Experimental Applications, vol. 2 (ed. van Gunsteren, W. F.et al.), pp. 147–160. Leiden, NL: ESCOM Science Publishers B.V.Google Scholar
Sheridan, R. P., Nilakantan, R., Dixon, J. S. & Venkataraghaven, R. (1986). The ensemble approach to distance geometry: Application to the nicotinic pharmacophore. J. Med Chem. 29 899–906.CrossRefGoogle Scholar
Shi, Y. Y., Mark, A. E., Wang, C. X., Huang, F., Berendsen, H. J. C. & Van Gunsteren, W. F. (1993). Can the stability of protein mutants be predicted by free energy calculations? Protein Engineering 6 289–295.Google ScholarPubMed
Shoichet, B. K., Bodian, D. L. & Kuntz, I. D. (1992). Molecular docking using shape descriptors. J. Comput. Chem. 13 380–397.CrossRefGoogle Scholar
Shoichet, B. K., Stroud, R. M., Santi, D. V., Kuntz, I. D. & Perry, K. M. (1993). Structure-based discovery of inhibitors of thymidylate synthase. Science 259 1445–1450.CrossRefGoogle ScholarPubMed
Silverman, R. B. (1992). The organic chemistry of drug design and drug action. San Diego, USA: Academic Press.Google Scholar
Simonson, T. & Brunger, A. T. (1992). Thermodynamics of protein-peptide interactions in the ribonuclease-S system studied by molecular dynamics and free energy calculations. Biochemistry 31 8661–8674.Google ScholarPubMed
Smith, P. E. & Van Gunsteren, W. F. (1993). Methods for the evaluation of long-range electrostatic forces in computer simulations of molecular systems. In Computer Simulation of Biomolecular Systems: Theoretical and Experimental Applications, vol. 2 (ed. van Gunsteren, W. F.et al.), pp. 182–212. Leiden, NL: ESCOM Science Publishers B.V.Google Scholar
Smith, P. E. & Van Gunsteren, W. F. (1994 a). Predictions of free energy differences from a single simulation of the initial state. J. Chem. Phys. 100 577–585.CrossRefGoogle Scholar
Smith, P. E. & Van Gunsteren, W. F. (1994 b). When are free energy components meaningful? J. Phys. Chem. (in press).CrossRefGoogle Scholar
Solmajer, T. & Mehler, E. L. (1991). Electrostatic screening in molecular dynamics simulations. Protein Engineering 4 911–917.CrossRefGoogle ScholarPubMed
Stewart, J. J. P. (1990). Mopac: A semiempirical molecular orbital program. J. Comput.-Aided Mol. Design 4 1–105.CrossRefGoogle ScholarPubMed
Still, W. C., Tempczyk, A., Hawley, R. C. & Hendrickson, T. (1990). Semianalytical treatment of solvation for molecular mechanics and dynamics. J. Am. Chem. Soc. 112 6127–6129.CrossRefGoogle Scholar
Stoddard, B. L. & Koshland, D. E. Jr (1992). Prediction of the structure of a receptor-protein complex using a binary docking method. Nature 358 774–776.CrossRefGoogle ScholarPubMed
Stouten, P. F. W., Frömmel, C., Nakamura, H. & Sander, C. (1993). An effective solvation term based on atomic occupancies for use in protein simulations. Molecular Simulation 10 97–120.CrossRefGoogle Scholar
Straatsma, T. P., Zacharias, M. & McCammon, J. A. (1992). Holonomic constraint contributions to free energy differences from thermodynamic integration molecular dynamics simulations. Chem. Phys. Lett. 196 297–302.CrossRefGoogle Scholar
Straatsma, T. P., Zacharias, M. & McCammon, J. A. (1993). Free energy difference calculations in biomolecular systems. In Computer Simulation of Biomolecular Systems: Theoretical and Experimental Applications, vol. 2 (ed. van Gunsteren, W. F.et al.), pp. 349–370. Leiden, NL: ESCOM Science Publishers B.V.Google Scholar
Suzuki, T. & Kudo, Y. (1990). Automatic log P estimation based on combined additive modelling methods. J. Comp. Aid. Molec. Design 4 155–198.CrossRefGoogle Scholar
Taft, R. W. Jr (1956). In Steric effects in organic chemistry (ed. Newman, M. S.), pp. 556. New York: Wiley.Google Scholar
Tanford, C. (1973). The hydrophobic effect: Formation of micelles and biological membranes. New York: Wiley.Google Scholar
Tidor, B. & Karplus, M. (1991). Simulation analysis of the stability mutant R96H of T4 lysozyme. Biochemistry 30 3217–3228.CrossRefGoogle ScholarPubMed
Torda, A. E., Brunne, R. M., Huber, T., Kessler, H. & Van Gunsteren, W. F. (1993). Structure refinement using time-averaged J-coupling constant restraints. J. Biomol. NMR 3 55–66.CrossRefGoogle ScholarPubMed
Torda, A. E., Scheek, R. M. & Van Gunsteren, W. F. (1989). Time-dependent distance restraints in molecular dynamics simulations. Chem. Phys. Letters 157 289–294.CrossRefGoogle Scholar
Torda, A. E., Scheek, R. M. & Van Gunsteren, W. F. (1990). Time-averaged Nuclear Overhauser Effect distance restraints applied to tendamistat. J. Mol. Biol. 214 223–235.CrossRefGoogle ScholarPubMed
Van Gunsteren, W. F. (1990). On testing theoretical models by comparison of calculated with experimental data. In Studies in Physical and Theoretical Chemistry, vol. 71 (ed. Rivail, J.-L.), pp. 463–478. Amsterdam: Elsevier.Google Scholar
Van Gunsteren, W. F. (1993). Molecular dynamics and stochastic dynamics simulation: A primer. In Computer Simulation of Biomolecular Systems: Theoretical and Experimental Applications, vol. 2 (ed. van Gunsteren, W. F.et al.), pp. 3–36. Leiden, NL: ESCOM Science Publishers B.V.Google Scholar
Van Gunsteren, W. F. & Berendsen, H. J. C. (1990). Computer simulation of molecular dynamics: Methodology, applications and perspectives in chemistry. Angew. Chem. Int. Ed. Engl. 29 992–1023.CrossRefGoogle Scholar
Van Gunsteren, W. F. & Mark, A. E. (1992 a). On the interpretation of biochemical data by molecular dynamics computer simulation. Eur. J. Biochem. 204 947–961.CrossRefGoogle ScholarPubMed
Van Gunsteren, W. F. & Mark, A. E. (1992 b). Prediction of the activity and stability effects of site-directed mutagenesis on a protein core. J. Mol. Biol. 227 389–395.CrossRefGoogle ScholarPubMed
Van Gunsteren, W. F., Beutler, T. C., Fraternali, F., King, P. M., Mark, A. E. & Smith, P. E. (1993). Computation of free energy in practice: choice of approximations and accuracy limiting factors. In Computer simulation of biomolecular systems: theoretical and experimental applications, Vol 2 (ed. van Gunsteren, W. F.et al.), pp. 315–348. Leiden, NL: ESCOM Science Publishers B.V.Google Scholar
Van Gunsteren, W. F., Brunne, R. M., Gros, P., Van Schaik, R. C., Schiffer, C. A. & Torda, A. E. (1994 a). Accounting for molecular mobility in structure determination based on NMR spectroscopic and X-ray diffraction data. Methods in Enzymology 239 619–654.CrossRefGoogle Scholar
Van Gunsteren, W. F., Luque, F. J., Timms, D. & Torda, A. E. (1994 b). Molecular mechanics in biology: From structure to function: Taking account of solvation. Ann. Rev. Biophys. Biomol. Structure 23 847–863.CrossRefGoogle ScholarPubMed
Van Schaik, R. C., Berendsen, H. J. C., Torda, A. E. & Van Gunsteren, W. F. (1993). A structure refinement method based on molecular dynamics in four spatial dimensions. J. Mol. Biol. 234 751–762.CrossRefGoogle ScholarPubMed
Van Schaik, R. C., Van Gunsteren, W. F. & Berendsen, H. J. C. (1992). Conformational search by potential energy annealing: Algorithm and application to cyclosporine A. J. of Comp.-Aided Mol. Design 6 97–112.CrossRefGoogle Scholar
Verloop, A., Hoogenstraaten, W. & Tipker, J. (1976). Development and application of new steric substituent parameters in drug design. In Drug Design, vol III (ed. Ariens, E. J.), New York: Academic Press.Google Scholar
Vila, J., Williams, R. L., Vàsquez, M. & Scheraga, H. A. (1991). Empirical salvation models can be used to differentiate native from near-native conformations of bovine pancreatic trypsin inhibitor. Proteins 10 199–218.CrossRefGoogle Scholar
Wade, R. C., Clark, K. J. & Goodford, P. J. (1993). Further development of hydrogen bond functions for use in determining energetically favourable binding sites on molecules of known structure. 1. Ligand probe groups with the ability to form two hydrogen bonds. J. Med. Chem. 36 140–147.CrossRefGoogle ScholarPubMed
Wade, R. C. & Goodford, P. J. (1993). Further development of hydrogen bond functions for use in determining energetically favourable binding sites on molecules of known structure. 2. Ligand probe groups with the ability to from more than two hydrogen bonds. J. Med. Chem. 36 148–158.CrossRefGoogle ScholarPubMed
Waller, C. L. & Marshall, G. (1993). Three-dimensional quantitative structure-activity relationship of angiotensin-converting enzyme and thermolysin inhibitors. II. A comparison of CoMFA models incorporating molecular orbital fields and desolvation free energies based on active-analog and complementary-receptor-field alignment rules. J. Med. Chem. 36 2390–2403.CrossRefGoogle Scholar
Wesson, L. & Eisenberg, D. (1992). Atomic solvation parameters applied to molecular dynamics of proteins in solution. Protein Science 1 227–235.CrossRefGoogle ScholarPubMed
Wold, S., Ruhe, A., Wold, H. & Dunn, W. J. III (1984). The collinearity problem in linear regression. The partial least squares (PLS) approach to generalized inverses. SIAM J. Sci. Stat. Comput. 5 735–743.CrossRefGoogle Scholar