Reviews in Computational Chemistry Volume 18

References 77
12. P. Burkhard, U. Hommel, M. Sanner, and M. D. Walkinshaw, J. Mol. Biol., 287, 853 (1999).
The Discovery of Steroids and Other Novel FKBP Inhibitors Using a Molecular Docking
Program.
13. J. H. Toney, P. M. D. Fitzgerald, N. Grover-Sharma, S. H. Olson, W. J. May, J. G. Sundelof,
D. E. Vanderwall, K. A. Cleary, S. K. Grant, J. K. Wu, J. W. Kozarich, D. L. Pompliano, and
G. G. Hammond, Chem. Biol., 5, 185 (1998). Antibiotic Sensitation Using Biphenyl
Tetrazoles as Potent Inhibitors of Bacteroides fragilis Metallo-b-Lactamase.
14. H.-J. Boehm, M. Boehringer, D. Bur, H. Gmuender, W. Huber, W. Klaus, D. Kostrewa, H.
Kuehne, T. Luebbers, N. Meunier-Keller, and F. Mueller, J. Med. Chem., 43, 2664 (2000).
Novel Inhibitors of DNA Gyrase: 3D Structure-Based Needle Screening, Hit Validation by
Biophysical Methods, and 3D Guided Optimization. A Promising Alternative to Random
Screening.
15. S. Grueneberg, B. Wendt, and G. Klebe, Angew. Chem. Int. Ed., 40, 389 (2001). Subnanomolar
Inhibitors From Computer Screening: A Model Study Using Human Carbonic
Anhydrase II.
16. M. A. Murcko, in Reviews in Computational Chemistry, K. B. Lipkowitz and D. B. Boyd,
Eds., Wiley-VCH, New York, 1997, Vol. 11, pp. 1–66. Recent Advances in Ligand Design
Methods.
17. D. E. Clark, C. W. Murray, and J. Li, in Reviews in Computational Chemistry, K. B. Lipkowitz
and D. B. Boyd, Eds., Wiley-VCH, New York, 1997, Vol. 11, pp. 67–125. Current Issues in
De Novo Molecular Design.
18. I. Muegge and M. Rarey, in Reviews in Computational Chemistry, K. B. Lipkowitz and
D. B. Boyd, Eds., Wiley-VCH, New York, 2001, Vol. 17, pp. 1–60. Small Molecule Docking
and Scoring.
19. P. J. Goodford, J. Med. Chem., 28, 849 (1985). A Computational Procedure for Determining
Energetically Favored Binding Sites on Biologically Important Macromolecules.
20. H.-J. Boehm, J. Comput.-Aided Mol. Design, 6, 61 (1992). The Computer Program LUDI: A
New Method for the De Novo Design of Enzyme Inhibitors.
21. H.-J. Boehm, J. Comput.-Aided Mol. Design, 6, 593 (1992). LUDI: Rule-Based Automatic
Design of New Substituents for Enzyme Inhibitor Leads.
22. C. A. Lipinski, F. Lombardo, B. W. Dominy, and P. J. Feeney, Adv. Drug Delivery Rev., 23, 3
(1997). Experimental and Computational Approaches to Estimate Solubility and Permeability
in Drug Discovery and Development Settings.
23. D. E. Clark and S. D. Pickett, Drug Discovery Today, 5, 49 (2000). Computational Methods
for the Prediction of ‘‘Drug-Likeness.’’
24. H.-J. Boehm and G. Klebe, Angew. Chem. Int. Ed., 35, 2588 (1996). What Can We Learn
from Molecular Recognition in Protein–Ligand Complexes for the Design of New Drugs?
25. O. Roche, R. Kiyama, and C. L. Brooks III, J. Med. Chem., 44, 3592 (2001). Ligand–Protein
Database: Linking Protein–Ligand Complex Structures to Binding Data.
26. I. K. McDonald and J. M. Thornton, J. Mol. Biol., 238, 777 (1994). Satisfying Hydrogen
Bonding Potential in Proteins.
27. M. H. Parker, D. F. Ortwine, P. M. O’Brien, E. A. Lunney, C. A. Banotai, W. T. Mueller,
P. McConnell, and C. G. Brouillette, Bioorg. Med. Chem. Lett., 10, 2427 (2000). Stereoselective
Binding of an Enantiomeric Pair of Stromelysin-1 Inhibitors Caused by Conformational
Entropy Factors.
28. J. D. Dunitz, Chem. Biol., 2, 709 (1995). Win Some, Lose Some: Enthalpy–Entropy
Compensation in Weak Molecular Interactions.
29. P. Gilli, V. Ferretti, G. Gilli, and P. A. Brea, J. Phys. Chem., 98, 1515 (1994). Enthalpy–
Entropy Compensation in Drug-Receptor Binding.
30. D. H. Williams, D. P. O’Brien, and B. Bardsley, J. Am. Chem. Soc., 123, 737 (2001). Enthalpy/
Entropy Compensation as a Competition Between Dynamics and Bonding: The Relevance to
Melting of Crystals and Biological Aggregates.