Three-dimensional structure database searches

Reviews in Computational Chemistry

Volumn 7, Issue , 1996, Pages 67-117

  Good, Andrew C ^a,b   Mason, Jonathan S ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b SANOFI   (France)

Author keywords

[No Author keywords available]

Indexed keywords

INFORMATION RETRIEVAL; SEARCH ENGINES;

CONFORMATIONAL COMPLEXITY; DATABASE SEARCHES; DATABASE SEARCHING; QUERY CONSTRUCTION; THREE DIMENSIONAL (3D) STRUCTURES; THREE-DIMENSIONAL STRUCTURE;

QUERY PROCESSING;

EID: 0030534012     PISSN: 10693599     EISSN: None     Source Type: Book Series    
DOI: None     Document Type: Article

References (137)

1. Y. C. Martin, M. G. Bures, and P. Willett, in Reviews in Computational Chemistry, Vol. 1, K. B. Lipkowitz and D. B. Boyd, Eds., VCH Publishers, New York, 1990, pp. 213-263. Searching Databases of Three-Dimensional Structures.
2. Y. C. Martin, J. Med. Chem., 35, 2145 (1992). 3D Database Searching in Drug Design.
3. I. D. Kuntz, Science, 257, 1078 (1992). Structure-Based Strategies for Drug Design and Discovery.
4. P. Gund, in Progress in Molecular and Subcellular Biology, Vol. 5, F. E. Hahn, Ed., Springer-Verlag, Berlin, 1977, pp. 117-143. Three-Dimensional Pharmacophore Pattern Searching.
5. A. Rusinko III, J. M. Skell, R. Balducci, C. M. McGarity, and R. S. Pearlman, University of Texas, Austin. CONCORD, A Program for the Rapid Generation of High Quality Approximate 3D Molecular Structures. Distributed by Tripos Associates, St. Louis, MO.
6. A. R. Leach and K. Prout, J. Comput. Chem., 11, 1193 (1990). Automated Conformational Analysis: Directed Conformational Search Using the A* Approach. Program known as COBRA, distributed by Oxford Molecular Ltd., Oxford, U.K.
7. Chem/Model, developed and distributed as part of the Chem-X modeling package by Chemical Design Ltd., Chipping Norton, Oxon, U.K.
8. Converter, developed and distributed by BIOSYM Technologies, San Diego, CA.
9. D. Weininger, J. Chem. Inf. Comput. Sci., 28, 31 (1988). SMILES, a Chemical Language and Information System. 1. Introduction to Methodology and Encoding Rules.
10. D. Weininger, A. Weininger, and J. L. Weininger, J. Chem. Inf. Comput. Sci. 29, 97 (1989). Algorithm for Generation of Unique SMILES Notation.
11. J. Elks and C. R. Ganellin, Chapman and Hall Dictionary of Drugs 3D. Chemical Data, Structure and Bibliography. Cambridge University Press, 1990. Distributed by Chemical Design Ltd., Chipping Norton, Oxon, U.K.
12. Available Chemicals Directory, developed and distributed by MDL Information Systems, San Leandro, CA. Formerly distributed as the Fine Chemicals Directory (FCD), which was smaller.
13. CAST 3D, developed and distributed by Chemical Abstracts Service, Columbus, OH.
14. J. H. Van Drie, D. Weininger, and Y. C. Martin, J. Comput.-Aided Mol. Design, 3, 225 (1989). ALADDIN: An Integrated Tool for Computer-Assisted Drug Design and Pharmacophore Recognition from Geometric, Steric and Substructure Searching of 3D Molecular Structures. Distributed by Daylight Chemical Information Systems, Inc., Sante Fe, NM.
15. R. P. Sheridan, A. Rusinko III, R. Nilakantan, and R. Venkataraghavan, Proc. Natl. Acad. Sci. USA, 86, 8165 (1989). Searching for Pharmacophores in Large Co-Ordinate Databases and Its Use in Drug Design.
16. R. P. Sheridan, R. Nilakantan, A. Rusinko III, N. Bauman, K. S. Haraki, and R. Venkataraghavan, J. Chem. Inf. Comput. Sci., 29, 255 (1989). 3DSEARCH, a System for Three-Dimensional Substructure Searching.
17. J. B. Moon and W. J. Howe, Tetrahedron Comput. Methodol., 3, 697 (1990). 3D Database Searching and De Novo Construction Methods in Molecular Design.
18. O. F. Guner, D. W. Hughes, and L. M. Dumont, J. Chem. Inf. Comput. Sci., 31, 408 (1991). An Integrated Approach to 3D Information Management with MACCS-3D.
19. MACCS (Molecular ACCess System), developed and distributed by MDL Information Systems, San Leandro, CA. This older system is being augmented with ISIS (Ref. 23).
20. ChemDBS-3D, developed and distributed as part of the Chem-X modeling package by Chemical Design Ltd., Chipping Norton, Oxon, U.K.
21. UNITY, developed and distributed by Tripos Associates, St. Louis, MO.
22. P. W. Sprague, in Recent Advances in Chemical Information - Proceedings of the 1991 Chemical Information Conference, H. Collier, Ed., Royal Society of Chemistry, Cambridge, U.K., 1992, pp. 107-111. Catalyst: A Computer Aided Drug Design System Specifically Designed for Medicinal Chemists. Catalyst, developed by BioCAD and now distributed by Molecular Simulations Inc., Burlington, MA.
23. ISIS/3D, developed and distributed by MDL Information Systems, San Leandro, CA.
24. N. W. Murrall and E. K. Davies, J. Chem. Inf. Comput. Sci. 30, 312 (1990). Conformational Freedom in 3D Databases. 1. Techniques.
25. T. Hurst, J. Chem. Inf. Comput. Sci., 34, 190 (1994). Flexible 3D Searching: The Directed Tweak Technique.
26. T. E. Moock, D. R. Henry, A. G. Ozkabak, and M. Alamgir, J. Chem. Inf. Comput. Sci., 34, 184 (1994). Conformational Searching in ISIS/3D Databases.
27. A. Smellie, S. L. Teig, and P. Towbin, J. Comput. Chem., 16, 171 (1995). Poling: Promoting Conformational Variation.
28. R. P. Sheridan, R. Nilakantan, J. S. Dixon, and R. Venkataraghavan, J. Med. Chem., 29, 899 (1986). The Ensemble Approach to Distance Geometry: Application to the Nicotinic Pharmacophore.
29. U. Cosentino, G. Moro, D. Pitea, S. Scolastico, R. Todeschini, and C. Scolastico, J. Comput.-Aided Mol. Design, 6, 47 (1992). Pharmacophore Identification by Molecular Modeling and Chemometrics: The Case of HMG-CoA Reductase Inhibitors.
30. Y. C. Martin, M. G. Bures, E. A. Danaher, J. DeLazzer, I. Lico, and P. A. Pavlik, J. Comput.-Aided Mol. Design, 7, 83 (1993). A Fast New Approach to Pharmacophore Mapping and Its Application to Dopaminergic and Benzodiazepine Agonists. (The program known as DISCO is distributed by Tripos Associates, St. Louis, MO.)
31. E. E. Hodgkin, A. Miller, and M. Whittaker, J. Comput.-Aided Mol. Design, 7, 515 (1993). A Monte Carlo Pharmacophore Generation Procedure: Application to the Human PAF Receptor.
32. J. Greene, S. Kahn, H. Savoj, P. Sprague, and S. L. Teig, J. Chem. Inf. Comput. Sci., submitted. Chemical Function Queries for 3D Database Search.
33. B. B. Masek, A. Merchant, and J. B. Matthew, J. Med. Chem., 36, 1230 (1993). Molecular Shape Comparison of Angiotensin II Receptor Antagonists.
34. R. D. Cramer III, D. E. Patterson, and J. D. Bunce, J. Am. Chem. Soc., 110, 5959 (1988). Comparative Molecular Field Analysis (CoMFA). Effect of Shape on Binding of Steroids to Carrier Proteins.
35. A. C. Good, S. J. Peterson, and W. G. Richards, J. Med. Chem., 36, 2928 (1993). QSARs from Similarity Matrices. Technique Validation and Application in the Comparison of Different Similarity Evaluation Methods.
36. A. N. Jain, K. Koile, and D. Chapman, J. Med Chem., 37, 2315 (1994). COMPASS - Predicting Biological Activities from Molecular Surface Properties - Performance Comparisons on a Steroid Benchmark.
37. N. C. Perry and V. J. van Geerestein, J. Chem. Inf. Comput. Sci., 32, 607 (1992). Database Searching on the Basis of Three-Dimensional Molecular Similarity Using the SPERM Program.
38. C. A. Pepperrell and P. Willett, J. Comput.-Aided Mol. Design, 5, 455 (1991). Techniques for the Calculation of Three-Dimensional Structural Similarity Using Inter-Atomic Distances.
39. W. Fisanick, K. P. Cross, and A. Rusinko III, J. Chem. Inf. Comput. Sci., 32, 664 (1992). Similarity Searching on CAS Registry Substances. 1. Global Molecular Properties and Generic Atom Triangle Searching.
40. W. Fisanick, K. P. Cross, and A. Rusinko III, J. Chem. Inf. Comput. Sci., 33, 548 (1993). Experimental System for Similarity and 3D Searching of CAS Registry Substances. 1. 3D Substructure Searching.
41. G. W. Bemis and I. D. Kuntz, J. Comput.-Aided Mol. Design, 6, 607 (1992). A Fast and Efficient Method for 2D and 3D Molecular Shape Description.
42. R. Nilakantan, N. Bauman, and R. Venkataraghavan, J. Chem. Inf. Comput. Sci., 33, 79 (1993). New Method for Rapid Characterization of Molecular Shapes: Application in Drug Design.
43. A. C. Good, T. J. A. Ewing, D. A. Gschwend, and I. D. Kuntz. J. Comput.-Aided Mol. Design, 9, 1 (1995). New Molecular Shape Descriptors: Application in Database Searching.
44. M. A. Gallop, R. W. Barrett, W. J. Dower, S. P. A. Foder, and E. M. Gordon, J. Med. Chem., 37, 1233 (1994). Application of Combinatorial Technologies to Drug Discovery. 1. Background and Peptide Combinatorial Libraries.
45. D. J. Keenan, D. E. Tsai, and J. D. Keene, T.I.B.S., 19, 57 (1994). Exploring Molecular Diversity with Combinatorial Shape Libraries.
46. I. D. Kuntz, J. M. Blaney, S. J. Oatley, R. Langridge, and T. E. Ferrin, J. Mol. Biol., 161, 269 (1982). A Geometric Approach to Macromolecule-Ligand Interactions.
47. R. L. Desjarlais, R. P. Sheridan, G. L. Seibel, J. S. Dixon, I. D. Kuntz, and R. Venkataraghavan, J. Med. Chem., 31, 722 (1988). Using Shape Complementarity as an Initial Screen in Designing Ligands for a Receptor Binding Site of Known 3D Structure.
48. R. L. Dejarlais, G. L. Seibel, I. D. Kuntz, P. S. Furth, J. C. Alvarez, P. R. Ortiz de Montellano, D. L. DeCamp, L. M. Babé, and C. S. Craik, Proc. Natl. Acad. Sci. USA, 87, 6644 (1990). Structure-Based Design of Nonpeptide Inhibitors Specific for HIV-1 Protease.
49. A. S. Smellie, G. M. Crippen, and W. G. Richards, J. Chem. Inf. Comput. Sci., 31, 386 1991). Fast Drug Receptor Mapping by Site Directed Distances.
50. M. C. Lawrence and P. C. Davis, Proteins, 12, 31 (1992). CLIX: A Search Algorithm for Finding Novel Ligands Capable of Binding to Proteins of Known 3D Structure.
51. B. K. Shoichet, D. L. Bodian, and I. D. Kuntz, J. Comput. Chem., 13, 380 (1992). Molecular Docking Using Shape Descriptors.
52. E. C. Meng, B. K. Shoichet, and I. D. Kuntz, J. Comput. Chem., 13, 505 (1992). Automated Docking with Grid Based Energy Evaluation.
53. B. K. Shoichet and I. D. Kuntz, Protein Eng., 6, 723 (1993). Matching Chemistry and Shape in Molecular Docking.
54. B. K. Shoichet, R. M. Stroud, D. V. Santi, I. D. Kuntz, and K. M. Perry, Science, 259, 1445 (1993). Structure-Based Discovery of Inhibitors of Thymidylate Synthase.
55. C. S. Ring, E. Sun, J. H. McKerrow, G. K. Lee, P. J. Rosenthal, I. D. Kuntz, and F. E. Cohen. Proc. Natl. Acad. Sci. U.S.A., 90, 3853 (1993). Structure-Based Design by Using Protein Models for the Development of Antiparasitic Agents.
56. D. L. Bodian, R. B. Yamasaki, R. L. Buswell, J. F. Stearns, J. M. White, and I. D. Kuntz, Biochemistry, 32, 2967 (1993). Inhibition of the Fusion-Inducing Conformational Change of Influenza Hemagglutinin by Benzoquinones and Hydroquinones.
57. E. C. Meng, D. A. Gschwend, J. M. Blaney, and I. D. Kuntz, Proteins, 17, 266 (1993). Orientational Sampling and Rigid Body Minimization in Molecular Docking.
58. M. D. Miller, S. K. Kearsley, D. J. Underwood, and R. P. Sheridan, J. Comput.-Aided Mol. Design, 8, 153 (1994). FLOG: A System to Select "Quasi-Flexible" Ligands Complementary to a Receptor of Known 3D Structure.
59. R. L. Desjarlais and J. S. Dixon, J. Comput.-Aided Mol. Design, 8, 231 (1994). A Shape and Chemistry Based Docking Method and Its Use in the Design of HIV-1 Protease Inhibitors.
60. I. D. Kuntz, E. C. Meng, and B. K. Shoichet, Acc. Chem. Res., 27, 117 (1994). Structure-Based Molecular Design.
61. K. Appelt, R. J. Baquet, C. A. Bartlett, C. L. J. Booth, S. T. Freer, M. A. N. Fuhry, M. R. Gehring, S. M. Herrmann, E. F. Howland, C. A. Janson, T. R. Jones, C.-C. Kan, V. Kathardekar, K. K. Lewis, G. P. Marzoni, D. A. Matthews, C. Mohr, E. W. Moomaw, C. A. Morse, S. J. Oatley, R. C. Ogden, M. R. Reddy, S. H. Reich, W. S. Schoettlin, W. W. Smith, M. D. Varney, J. E. Villafranca, R. W. Ward, S. Webber, S. E. Webber, K. M. Welsh, and J. White. J. Med. Chem., 34, 1925 (1991). Design of Enzyme Inhibitors Using Iterative Protein Crystallographic Analysis.
62. J. Greer, J. W. Erikson, J. J. Baldwin, and M. D. Varney, J. Med. Chem., 37, 1035 (1994). Application of the Three-Dimensional Structures of Protein Target Molecules in Structure-Based Drug Design.
63. T. Havel, Progr. Mol. Biol. Biophys., 56, 43 (1991). An Evaluation of Computational Strategies for Use in the Determination of Protein Structure from Distance Constraints by NMR.
64. For a tutorial on distance geometry, see J. M. Blaney and J. S. Dixon, in Reviews in Computational Chemistry, Vol. 5, K. B. Lipkowitz and D. B. Boyd, Eds., VCH Publishers, New York, 1994, pp. 299-335. Distance Geometry in Molecular Modeling.
65. E. M. Ricketts, J. Bradshaw, M. Hann, F. Hayes, N. Tanna, and D. M. Ricketts, J. Chem. Inf. Comput. Sci. 33, 905 (1993). Comparison of Conformations of Small Molecule Structures from the Protein Data Bank with Those Generated by CONCORD, COBRA, ChemDBS-3D, and CONVERTOR and Those Extracted from the Cambridge Database.
66. M. C. Nicklaus, G. W. A. Milne, and D. Zaharevitz, J. Chem. Inf. Comput. Sci., 33, 639 (1993). Chem-X and CAMBRIDGE. Comparison of Computer Generated Chemical Structures with X-ray Crystallographic Data.
67. J. Sadowski, J. Gasteiger, and G. Klebe, J. Chem. Inf. Comput. Sci., 34, 1000 (1994). Comparison of Automatic Three-Dimensional Model Builders Using X-ray Structures.
68. F. H. Allen, S. Bellard, M. D. Brice, B. A. Cartwright, A. Doubleday, H. Higgs, T. Hummelink, B. G. Hummelink-Peters, O. Kennard, W. D. S. Motherwell, J. R. Rodgers, and D. G. Watson, J. Chem. Inf. Comput. Sci., 31, 187 (1992). The Development of Versions 3 and 4 of the Cambridge Structural Database System.
69. F. C. Bernstein, T. F. Koetzle, G. J. B. Williams, E. F. Meyer Jr., M. D. Brice, J. R. Rodgers, O. Kennard, T. Shimanouchi, and M. Tasumi, J. Mol. Biol., 112, 535 (1977). The Protein Data Bank: A Computer Based Archival File for Macromolecular Structures.
70. W. L. Jorgenson, Science, 254, 954 (1991). Rusting of the Lock and Key Model for Protein Ligand Binding.
71. J. Sadowski and J. Gasteiger, Chem. Rev., 93, 2567 (1993). From Atoms and Bonds to Three-Dimensional Atomic Co-Ordinates: Automatic Model Builders.
72. O. F. Guner, D. R. Henry, and R. S. Pearlman, J. Chem. Inf. Comput. Sci., 32, 101 (1992). Use of Flexible Queries for Searching Conformationally Flexible Molecules in Databases of 3D Structures.
73. M. Saunders, J. Am. Chem. Soc., 109, 3051 (1987). Stochastic Exploration of Molecular Mechanics Energy: Hunting for the Global Minimum.
74. J. A. McCammon and S. C. Harvey, Dynamics of Proteins and Nucleic Acids, Cambridge University Press, Cambridge, U.K., 1987.
75. N. Gō and H. A. Scheraga, Macromolecules, 11, 552 (1978). Calculation of the Conformation of Cyclo-Hexaglycil.
76. H. C. Romesburg, Cluster Analysis for Researchers, Lifetime Learning Pub., Wadsworth Inc., Belmont, CA, 1984.
77. P. D. Dolata, A. R. Leach, and K. Prout, J. Comput.-Aided Mol. Design, 1, 73 (1987). AI in Conformational Analysis.
78. S. E. Jakes and P. Willett, J. Mol. Graphics, 4, 12 (1986). Pharmacophore Pattern Matching in Files of 3D Chemical Structures: Selection of Inter-Atomic Distance Screens.
79. C. R. Ganellin, in Pharmacology of Histamine Receptors, C. R. Ganellin and M. E. Parsons, Eds., Wright-PSG, London, 1982, pp. 21-77. Chemistry and Structure Activity Relationships of Drugs Acting at Histamine Receptors.
80. D. R. Ferro and J. A. Hermans, Acta Crystallogr., A33, 345 (1977). A Difference Based Rigid Body Molecular Fit Routine.
81. J. S. Mason, in Trends in QSAR and Molecular Modelling 92, C. G. Wermuth, Ed., ESCOM, Leiden, 1992, pp. 252-255. Experiences with Conformationally Flexible Databases.
82. K. Kato, S. Ohkawa, S. Terao, Z. Terashita, and K. Nishikawa, J. Med. Chem., 28, 287 (1985). Thromboxane Synthetase Inhibitors (TXSI). Design, Synthesis and Evaluation of a Novel Series of ω-Pyridylalkenoic Acids.
83. J. A. Neider and R. Mead, Comput. J., 7, 308 (1965). A Simplex Method for Function Optimization.
84. W. H. Press, B. P. Flannery, S. A. Teukolsky, and W. T. Vetterling, Numerical Recipes - Fortran Version, Cambridge University Press, Cambridge, U.K., 1989.
85. T. Schlick, in Reviews in Computational Chemistry, K. B. Lipkowitz and D. B. Boyd, Eds., VCH Publishers, New York, 1992, pp. 1-30. Optimization Methods in Computational Chemistry.
86. D. E. Clark, G. Jones, and P. Willett, J. Chem. Inf. Comput. Sci., 34, 197 (1994). Pharmacophoric Pattern Matching in Files of Three-Dimensional Chemical Structures: Comparison of Conformational Searching Algorithms for Flexible Searching.
87. J. S. Mason, in Trends in Drug Research: Proceedings of the 9th Noordwijkhout-Camerino Symposium, Noordwijkhout, The Netherlands, 23-28th May 1993, Series title: Pharmacochemistry Library, 20, V. Claassen, Ed., Elsevier, Amsterdam, 1994, pp. 147-156. Drug Design Using Conformationally Flexible Molecules in 3D Databases.
88. J. S. Mason, in Molecular Similarity in Drug Design, P. M. Dean, Ed., Blackie Academic and Professional, Glasgow, 1995, pp. 138-162. Chapter 6. Experiences with Searching for Molecular Similarity in Flexible 3D Databases.
89. N. C. Cohen, J. M. Blaney, C. Humblet, P. Gund, and D. C. Barry, J. Med. Chem., 33, 883 (1990). Molecular Modeling Software and Methods for Medicinal Chemistry. There are too many molecular modeling packages to mention individually. The reference given here is a perspective on molecular modeling packages and the functionality they provide. Its vintage is such that many new programs have since become accessible. See D. B. Boyd, this volume's appendix for a current, comprehensive listing of molecular modeling packages.
90. M. G. Bures, C. Black-Schaefer, and G. Gardner, J. Comput.-Aided Mol. Design, 5, 323 (1991). The Discovery of Novel Auxin Transport Inhibitors by Molecular Modeling and Three-Dimensional Pattern Analysis.
91. G. R. Marshall, C. D. Barry, H. E. Bosshard, R. A. Dammkoehler, and D. A. Dunn, in Computer-Assisted Drug Design, American Chemical Society Symposium, No. 112, E. C. Olsen and R. E. Christoffersen, Eds., ACS, Washington, 1979, pp. 205-226. The Conformational Parameter in Drug Design: The Active Analog Approach.
92. D. Mayer, C. B. Naylor, I. Motoc, and G. R. Marshall, J. Comput.-Aided Mol. Design, 1, 3 (1987). A Unique Geometry of the Active Site of Angiotensin-Converting Enzyme Consistent with Structure Activity Studies.
93. D. F. Ortwine, T. C. Malone, C. F. Bigge, J. T. Drummond, C. Humblet, G. Johnson, and G. W. Pinter, J. Med. Chem., 35, 1345 (1992). Generation of N-Methyl-D-Aspartate Agonist and Competitive Antagonist Pharmacophore Models. Design and Synthesis of Phosphonalkyl-Substituted Tetrahydroisoquinolines as Novel Antagonists.
94. A. T. Brint and P. Willett, J. Chem. Inf. Comput. Sci., 27, 152 (1987). Algorithm for the Identification of Three-Dimensional Maximal Common Substructures.
95. R. Carbo and L. Domingo, Int. J. Quantum Chem., 32, 517 (1987). LCAO-MO Similarity Measures and Taxonomy.
96. A. J. Hopfinger, J. Med. Chem., 26, 990 (1983). Theory and Analysis of Molecular Potential Energy Fields in Molecular Shape Analysis: A QSAR Study of 2,4-Diamino-5-Benzylpyrimidines as DHFR Inhibitors.
97. E. E. Hodgkin and W. G. Richards, Int. J. Quantum Chem., Quantum Biol. Symp., 14, 105 (1987). Molecular Similarity Based on Electrostatic Potential and Electric Field.
98. M. Manaut, F. Sanz, J. Jose, and M. Milesi, J. Comput.-Aided Mol. Design, 5, 371 (1991). Automatic Search for Maximum Similarity between Molecular Electrostatic Potential Distributions.
99. J. D. Petke, J. Comput. Chem., 14, 928 (1993). Cumulative and Discrete Similarity Analysis of Electrostatic Potentials and Fields.
100. A. C. Good, J. Mol. Graph., 10, 144 (1992). The Calculation of Molecular Similarity: Alternative Formulas, Data Manipulation and Graphical Display.
101. C. Burt and W. G. Richards, J. Comput.-Aided Mol. Design., 4, 231 (1990). Molecular Similarity: The Introduction of Flexible Fitting.
102. A. C. Good, E. E. Hodgkin, and W. G. Richards, J. Chem. Inf. Comput. Sci., 32, 188 (1992). The Utilization of Gaussian Functions for the Rapid Evaluation of Molecular Similarity.
103. A. C. Good and W. G. Richards, J. Chem. Inf. Comput. Sci., 33, 112 (1993). Rapid Evaluation of Shape Similarity Using Gaussian Functions.
104. P.-L. Chau and P. M. Dean, J. Mol. Graphics, 5, 97 (1987). Molecular Recognition: 3D Surface Structure Comparison by Gnomonic Projection.
105. P. M. Dean and P.-L. Chau, J. Mol. Graph. 5, 152 (1987). Molecular Recognition: Optimized Searching Through Molecular 3-Space for Pattern Matches on Molecular Surfaces.
106. R. B. Hermann and D. K. Herron, J. Comput.-Aided Mol. Design, 5, 511 (1991). OVID and SUPER: Two Overlap Programs for Drug Design.
107. P. Bladen, J. Mol. Graphics, 7, 130 (1989). A Rapid Method for Comparing and Matching the Spherical Parameter Surfaces of Molecules and Other Irregular Objects.
108. F. E. Blaney, D. Naylor, and J. Woods, J. Mol. Graphics, 11, 157 (1993). MAMBAS: A Real Time Graphics Environment for QSAR.
109. A. C. Good, in Molecular Similarity in Drug Design, P. M. Dean, Ed., Blackie Academic and Professional, Glasgow, 1995, pp. 25-56. Chapter 2. 3D Molecular Similarity Indices and Their Application in QSAR Studies.
110. G. M. Downs and P. Willett, this volume. Similarity Searching in Databases of Chemical Structures.
111. M. L. Connolly, J. Am. Chem. Soc., 107, 1118 (1985). Computation of Molecular Volume.
112. R. D. Cramer III, J. D. Bunce, and D. E. Patterson, Quant. Struct. Act. Relat., 7, 18 (1988). Cross-Validation, Bootstrapping, and PLS Compared with Multiple Linear Regression in Conventional QSAR Studies.
113. J. W. McFarland, J. Med. Chem., 35, 2543 (1992). Comparative Molecular Field Analysis of Anticoccidial Triazines. This paper contains a number of references to other interesting articles that utilize the CoMFA technique.
114. C. L. Waller, T. I. Oprea, A. Giolitti, and G. R. Marshall, J. Med. Chem., 36, 4152 (1993). Three-Dimensional QSAR of HIV-1 Protease Inhibitors. 1. A CoMFA Study Employing Experimentally Determined Alignment Rules.
115. T. I. Oprea, C. L. Waller, and G. R. Marshall, J. Med. Chem., 37, 2206 (1994). Three-Dimensional QSAR of HIV-1 Protease Inhibitors. 2. Predictive Power using Limited Exploration of Alternative Binding Modes.
116. SYBYL, a molecular modeling package developed and distributed by Tripos Associates, St. Louis, MO.
117. H. Kubinyi, Ed., 3D QSAR in Drug Design, Theory, Methods and Applications, ESCOM, Leiden, 1993.
118. J. S. Mason, unpublished results.
119. For more information on the LDL receptor system, see M. Huettinger, M. Herrman, H. Goldenberg, E. Granzer, and M. Leineweber, Arteriosclerosis and Thrombosis, 13, 1005 (1993). Hypolipidemic Activity of HOE-402 Is Mediated by Stimulation of the LDL Receptor Pathway.
120. J. S. Mason, unpublished results.
121. For more information on the endothelin receptor system, see A. M. Doherty, J. Med. Chem., 35, 1493 (1992). Endothelin: A New Challenge.
122. M. L. Connolly, J. Mol. Graphics, 11, 139 (1993). The Molecular Surface Package.
123. P. J. Goodford, J. Med. Chem., 28, 849 (1985). Computational Procedure for Determining Energetically Favorable Binding Sites on Biologically Important Molecules. Program known as GRID, developed and distributed by Molecular Discovery Ltd., Oxford, U.K.
124. R. Norel, D. Fischer, H. J. Wolfson, and R. Nussinov, Protein. Eng., 7, 39 (1994). Molecular Surface Recognition by a Computer Vision Based Technique.
125. V. J. van Geerestein, N. C. Perry, P. D. J. Grootenhuis, and C. A. G. Haasnoot, Tetrahedron Comput. Methodol., 3, 595 (1992). 3D Database Searching on the Basis of Ligand Shape Using the SPERM Prototype Method.
126. G. Lauri and P. Bartlett, J. Comput.-Aided Mol. Design, 8, 51 (1994). CAVEAT: A Program to Facilitate the Design of Organic Molecules.
127. R. Nilakantan, N. Bauman, and R. Venkataraghavan, J. Chem. Inf. Comput. Sci., 31, 527 (1991). A Method for Automatic Generation of Novel Chemical Structures and Its Potential Applications to Drug Design.
128. J. B. Moon and W. J. Howe, Proteins, 11, 314 (1991). Computer Design of Bioactive Molecules: A Method for Receptor Based De Novo Design.
129. S. H. Rotstein and M. A. Murcko, J. Comput.-Aided Mol. Design, 7, 23 (1992). GENSTAR: A Method for De Novo Drug Design.
130. V. J. Gillet, W. Newell, P. Mata, G. Myatt, S. Sike, Z. Zsoldos, and P. Johnson, J. Chem. Inf. Comput. Sci., 34, 207 (1994). SPROUT: Recent Developments in the De Novo Design of Molecules.
131. H. J. Bohm, J. Comput.-Aided Mol. Design, 6, 593 (1992). LUDI: Rule Based Automatic Design of New Substituents for Enzyme Inhibitor Leads.
132. D. A. Pearlman and M. A. Murcko, J. Comput. Chem., 14, 1184 (1993). CONCEPTS: A New Dynamic Algorithm for De Novo Drug Suggestion.
133. Y. Nishibata and A. Itai, J. Med. Chem., 36, 2921 (1993). Confirmation of the Usefulness of a Structure Construction Program Based on 3D Receptor Structure for Rational Lead Generation.
134. R. S. Bohacek and C. McMartin, J. Am. Chem. Soc., 116, 5560 (1994). Multiple Highly Diverse Structures Complementary to Enzyme Binding Sites - Results of Extensive Application of a De Novo Design Method Incorporating Combinatorial Growth.
135. R. A. Lewis, D. C. Roe, C. Huang, T. E. Ferrin, R. Langridge, and I. D. Kuntz, J. Mol. Graphics, 10, 66 (1992). Automated Site Directed Drug Design Using Molecular Lattices.
136. A. Smellie, S. D. Kahn, and S. L. Teig, J. Chem. Inf. Comput. Sci., 35, 285 (1995). Analysis of Conformational Coverage. 1. Validation and Estimation of Coverage.
137. A. Smellie, S. D. Kahn, and S. L. Teig, J. Chem. Inf. Comput. Sci., 35, 295 (1995). Analysis of Conformational Coverage. 2. Application of Conformational Models.