Excplicit calculation of 3D molecular similarity

This is a preview of subscription content, access via your institution.


  1. 1.

    Cramer, R.D. III, DePriest, S.A., Patterson D.E. and Hecht, P., The developing practice of Comparative Molecular Field Analysis, In 3D QSAR in drug design, Kubinyi, H. (Ed.) ESCOM, Leiden, 1993, pp. 443–485.

    Google Scholar 

  2. 2.

    Martin, Y.C., Bures, M.G., Danaher, E.A., DeLazzer, J., Lico, I. and Pavlik, P.A., A few new approach to pharmacophore mapping and its application to dopaminergic and benzodiazepine agonists, J. Comput.-Aided Mol. Design, 7 (1993) 83–102.

    Google Scholar 

  3. 3.

    Hopfinger, A.J., A QSAR investigation of DHFR inhibiton by Bakers Triazines based upon molecular shape analysis, J. Am. Chem. Soc., 102 (1980) 7196–7206.

    Google Scholar 

  4. 4.

    Hopfinger, A.J., Theory and analysis of molecular potential energy fields in molecular shape analysis: A QSAR study of 2,4-diamino-5-benzylpyrimidines as DHFR inhibitors, J. Med. Chem., 26 (1983) 990–996.

    Google Scholar 

  5. 5.

    Hermann, R.B. and Herron, D.K., OVID and SUPER: Two overlapprograms for drug design, J. Comput.-Aided Mol. Design, 5 (1991) 511–524.

    Google Scholar 

  6. 6.

    Masek, B.B., Merchant, A. and Matthew, J.B., Molecular shape comparisons of angiotensin II receptor antagonists, J. Med. Chem., 36 (1993) 1230–1238.

    Google Scholar 

  7. 7.

    Carbo, R., Leyda, L. and Arnau, M., An electron density measure of the similarity between two compounds, Int. J. Quantum Chem., 17 (1980) 1185–1189.

    Google Scholar 

  8. 8.

    Downs, G.M. and Willett, P., Similarity searching in databases of chemical structures, In Lipkowitz, K.B. and Boyd, D.B. (Eds.) Reviews in computational chemistry, Vol. 7, VCH, New York, 1995, pp. 1–66.

    Google Scholar 

  9. 9.

    Holland, J.D., Ranade, S.S. and Willett, P., A fast algorithm for selecting sets of dissimilar molecules from large chemical databases, Quant. Struct.-Act. Relat., 14 (1995) 501–506.

    Google Scholar 

  10. 10.

    Hodgkin, E.E. and Richards, W.G., Molecular similarity based on electrostatic potential and electric field, Int. J. Quantum Chem. Quantum Biol. Symp., 14 (1987) 105–110.

    Google Scholar 

  11. 11.

    Hodgkin, E.E. and Richards, W.G., Molecular similarity, Chem. Br., (1988) 1141–1144.

  12. 12.

    Petke, J.D., Cumulative and discrete similarity analysis of electrostatic potentials and fields, J. Comp. Chem., 14 (1993) 928–933.

    Google Scholar 

  13. 13.

    Bowen-Jenkins, P.E. and Richards, W.G., Molecular similarity in terms of valence electron density, J. Chem. Soc. Chem. Commun. (1986) 133–135.

  14. 14.

    Hodgkin, E.E. and Richards, W.G., A semi-empirical method for calculating molecular similarity, J. Chem. Soc. Chem. Commun., (1986) 1342–1344.

  15. 15.

    Carbo, R. and Domingo, L., LCAO-MO similarity measures and taxonomy, Int. J. Quantum Chem., 32 (1987) 517–545.

    Google Scholar 

  16. 16.

    Amovilli, C. and McWeeny, R., Shape and similarity: Two aspects of molecular recognition, J. Mol. Struct., 227 (1991) 1–9.

    Google Scholar 

  17. 17.

    Cioslowski, J. and Fleischmann, E.D., Assessing molecular similarity from results of ab initio electronic structure calculations, J. Am. Chem. Soc., 113 (1991) 64–67.

    Google Scholar 

  18. 18.

    Cooper, D.L. and Allen, N.L., A novel approach to molecular similarity, J. Comput.-Aided Mol. Design, 3 (1991) 253–259.

    Google Scholar 

  19. 19.

    Burt, C., Huxley, P. and Richards, W.G., The application of molecular similarity calculations, J. Comp. Chem., 11 (1990) 1139–1146.

    Google Scholar 

  20. 20.

    Burt, C. and Richards, W.G., Molecular similarity: The introduction of flexible fitting, J. Comput.-Aided Mol. Design 4 (1990) 231–238.

    Google Scholar 

  21. 21.

    Richard, A.M., Quantitative comparison of MEPs for structure activity studies, J. Comp. Chem., 12 (1991) 959–969.

    Google Scholar 

  22. 22.

    Good, A.C., The calculation of molecular similarity: Alternative formulas, data manipulation and graphical display, J. Mol. Graph., 10 (1992) 144–151.

    Google Scholar 

  23. 23.

    Good, A.C., Hodgkin, E.E. and Richards, W.G., The utilisation of Gaussian functions for the rapid evaluation of molecular similarity, J. Chem. Inf. Comput. Sci., 32 (1992) 188–191.

    Google Scholar 

  24. 24.

    Meyer, A.M. and Richards, W.G., Similarity of molecular shape, J. Comput.-Aided Mol. Design, 5 (1991) 426–439.

    Google Scholar 

  25. 25.

    Moon, J.B. and Howe, W.J., 3D database searching and de novo design construction methods in molecular design, Tetrahedron Comput. Methodol., 3 (1992) 697–711.

    Google Scholar 

  26. 26.

    van Geerestein, V.J., Perry, N.J., Grootenhuis, P.D.J. and Haasnoot, C.A.G., 3D database searching on the basis of shape using the SPERM prototype method, Tetrahedron Comput. Methodol., 3 (1992) 595–613.

    Google Scholar 

  27. 27.

    Good, A.C. and Richards, W.G., Rapid evaluation of shape similarity using Gaussian functions, J. Chem. Inf. Comput. Sci., 33 (1993) 112–116.

    Google Scholar 

  28. 28.

    Nilakantan, R., Bauman, N. and Venkataraghavan, R., New method for rapid characterization of molecular shapes: Applications in drug design, J. Chem. Inf. Comput. Sci., 33 (1993) 79–85.

    Google Scholar 

  29. 29.

    Hahn, M., Three-dimensional shape-based searching of conformationally flexible compounds, J. Chem. Inf. Comput. Sci., 37 (1997) 80–86.

    Google Scholar 

  30. 30.

    Namasivayam, S. and Dean, P.M., Statistical method for surface pattern matching between dissimilar molecules: Electrostatic potentials and accessible surfaces, J. Mol. Graph., 4 (1986) 46–50.

    Google Scholar 

  31. 31.

    Chau, P.-L. and Dean, P.M., Molecular recognition: 3D surface structure comparison by gnomonic projection, J. Mol. Graph., 5 (1987) 97–100.

    Google Scholar 

  32. 32.

    Dean, P.M. and Chau, P.-L., Molecular recognition: Optimised searching through molecular 3-space for pattern matches on molecular surfaces, J. Mol. Graph., 5 (1987) 152–158.

    Google Scholar 

  33. 33.

    Dean, P.M., Callow, P. and Chau, P.-L., Molecular recognition: Blind searching for regions of strong structural match on the surfaces of two dissimilar molecules, J. Mol. Graph., 6 (1988) 28–34.

    Google Scholar 

  34. 34.

    Manaut, M., Sanz, F., Jose, J. and Milesi, M., Automatic search for maximum similarity between MEP distributions, J. Comput.-Aided Mol. Design, 5 (1991) 371–380.

    Google Scholar 

  35. 35.

    Sanz, F., Manaut, F., Rodriguez, J., Lozoya, E. and Lopez-de-Brinao, E., MEPSIM: A computational package for analysis and comparison of Molecular Electrostatic Potentials, J. Comput.-Aided Mol. Design, 7 (1993) 337–347.

    Google Scholar 

  36. 36.

    Perry, N.C. and van Geerestein, V.J., Database searching on the basis of 3D molecular similarity using the SPERM program, J. Chem. Inf. Comput. Sci., 32 (1992) 607–616.

    Google Scholar 

  37. 37.

    Badel, A., Mornon, J.P. and Hazout, S., Searching for geometric molecular shape complementarity using bi-dimensional surface profiles, J. Mol. Graph., 10 (1992) 205–211.

    Google Scholar 

  38. 38.

    Blaney, F.E., Finn, P., Phippen, R.W. and Wyatt, M., Molecular surface comparison: Application to molecular design, J. Mol. Graph., 11 (1993) 98–105.

    Google Scholar 

  39. 39.

    Blaney, F.E., Naylor, D. and Woods, J., MAMBAS: A real time graphics environment for QSAR, J. Mol. Graph., 11 (1993) 157–165.

    Google Scholar 

  40. 40.

    Reynolds, C.A., Burt, C. and Richards, W.G., A linear molecular similarity index, Quant. Struct.-Act. Relat., 11 (1992) 34–35.

    Google Scholar 

  41. 41.

    Klebe, G., Abraham, U. and Mietzner, T., Molecular similarity indices in a comparative analysis (ComSIA) of drug molecules to correlate and predict their biological activity, J. Med. Chem., 37 (1994) 4130–4146.

    Google Scholar 

  42. 42.

    Kearsley, S.K. and Smith, G.M., An alternative method for the alignment of molecular structure: Maximizing electrostatic and steric overlap, Tetrahedron Comput. Methodol., 3 (1990) 615–633.

    Google Scholar 

  43. 43.

    Good, A.C., Peterson, S.J. and Richards, W.G., QSARs from similarity matrices: Technique validation and application in the comparison of different similarity evaluation methods, J. Med. Chem., 36 (1993) 2929–2937.

    Google Scholar 

  44. 44.

    Sneath, P.H.A. and Sokal, R.R., Numerical Taxonomy, W.H. Freeman, San Francisco, CA, 1973.

    Google Scholar 

  45. 45.

    Good, A.C., 3D molecular similarity indices and their application in QSAR studies, In Dean, P.M. (Ed.) Molecular similarity in drug design, Blackie Academic and Professional, Glasgow, 1995, pp. 138–162.

    Google Scholar 

  46. 46.

    Brown, R.D. and Martin, Y.C., The information content of 2D and 3D structural descriptor relevant to ligand-receptor binding, J. Chem. Inf. Comput. Sci., 37 (1997) 1–9.

    Google Scholar 

  47. 47.

    Burgess, E.M., Ruell, J.A., Zalkow, L.H. and Haugwitz, R.D., Molecular similarity from atomic electro-static multipole comparisons: Application to anti-HIV drugs, J. Med. Chem., 38 (1995) 1635–1640.

    Google Scholar 

  48. 48.

    Measures, P.T., Mort, K.A., Allan, N.L. and Cooper, D.L., Applications of momentum space similarity, J. Comput.-Aided Mol. Design, 9 (1995) 331–340.

    Google Scholar 

  49. 49.

    Automated Similarity Package, developed and distributed by Oxford Molecular, the Medewar Centre, Oxford Science Park, Oxford OX4 4GA, U.K.

  50. 50.

    Bone, R.G. and Villar, H.O., Discriminating D1 and D2 agonists with a hydrophobic similarity index, J. Mol. Graph., 13 (1995) 165–74.

    Google Scholar 

  51. 51.

    Szabo, A. and Ostland, N.S., Modern quantum chemistry, Macmillan, New York, 1982, pp. 410–412.

  52. 52.

    McMahon, A.J. and King, P.M., Optimization of the Carbo molecular similarity index using gradient methods, J. Comp. Chem., 18 (1997) 151–158.

    Google Scholar 

  53. 53.

    Wild, D.J. and Willett, P., Similarity searching in files of three-dimensional chemical structures: Alignment of molecular electrostatic potential fields with a genetic algorithm, J. Chem. Inf. Comput. Sco., 36 (1996) 159–167.

    Google Scholar 

  54. 54.

    Thorner, D.A., Wild, D.J., Willett, P. and Wright, P.M., Similarity seearching in files of three-dimensional chemical structures: Flexible field-based searching of molecular electrostatic potentials, J. Chem. Inf. Comput. Sci., 36 (1996) 900–908.

    Google Scholar 

  55. 55.

    Frisch, M.J., Head, G.M., Schlegel, H.B., Raghavachari, K., Binkley, J.S., Gonzalez, C., Defrees, D.J., Fox, D.J., Whiteside, R.A., Seeger, R., Melius, C.F., Baker, J., Martin, R., Kahn, L.R., Stewart, J.J.P., Fluder, E.M., Topiol, S. and Pople, J.A., Gaussian 88, Gaussian. Inc., Pittsburgh, PA, U.S.A.

  56. 56.

    Grant, J.A. and Pickup, B.T., A Gaussian description of molecular shape, J. Phys. Chem., 99 (1995) 3503–3510.

    Google Scholar 

  57. 57.

    Grant, J.A., Gallardo, M.A. and Pickup, B.T., A fast method of molecular shape comparison: A simple application of a Gaussian description of molecular shape, J. Compt. Chem., 17 (1996) 1653–1666.

    Google Scholar 

  58. 58.

    Chapman, D., The measurement of molecular diversity: A three-dimensional approach, J. Comput.-Aided Mol. Design, 10 (1996) 501–512.

    Google Scholar 

  59. 59.

    Bladen, P., A rapid method for comparing and matching the spherical parameter surfaces of molecules and other irregular objects, J. Mol. Graph., 7 (1989) 130–137.

    Google Scholar 

  60. 60.

    Blaney, F.E., Edge, C., Phippen, R.W., Molecular surface comparison: 2. Similarity of electrostatic surface vectors in drug design, J. Mol. Graph., 13 (1995) 165–74.

    Google Scholar 

  61. 61.

    Connolly, M.L., Computation of molecular volume, J. Am. Chem. Soc., 107 (1985) 1118–1124.

    Google Scholar 

  62. 62.

    Connolly, M.L., Analytical molecular surface calculation, J. Appl. Cryst., 16 (1983) 548–558.

    Google Scholar 

  63. 63.

    Masek, B.B., Merchant, A. and Matthew, J.B., Molecular skins: A new concept for quantitative shape matching of a protein with its small molecular mimics, Protein, 17 (1993) 193–202.

    Google Scholar 

  64. 64.

    Perkins, T.D.J., Mills, J.E.J. and Dean, P.M., Molecular surface-volume and property matching to superpose flexible dissimilar molecules, J. Comput.-Aided Mol. Design, 9 (1995) 479–490.

    Google Scholar 

  65. 65.

    Seri-Levy, A. and Richards, W.G., Chiral drug potency: Pfeiffer's rule and computed chirality coefficients, Tetrahedron Asymmetry, 4 (1993) 1917–1921.

    Google Scholar 

  66. 66.

    Seri-Levy, A., West, S. and Richards, W.G., Molecular similarity, quantitative chirality and QSAR for chiral drugs, J. Med. Chem., 37 (1994) 1727–1732.

    Google Scholar 

  67. 67.

    Dughan, L., Burt, C. and Richards, W.G., The study of peptide bond isosteres using molecular similarity, J. Mol. Struct., 235 (1991) 481–488.

    Google Scholar 

  68. 68.

    Montanari, C.A., Tute, M.S., Beezer, A.E. and Mitchell, J.C., Determination of receptor-bound drug conformations by QSAR using flexible fitting to derive a molecular similarity index, J. Comput.-Aided Mol. Design, 10 (1996) 67–73.

    Google Scholar 

  69. 69.

    Cardozo, M.G., Kawai, T., Iimura, Y., Sugimoto, H., Yamanishi, Y. and Hopfinger, A.J., Conformational analyses and molecular shape comparisons of a series ofinandone-benzylpiperidine inhibitors of acetylcholinesterase, J. Med. Chem., 35 (1992) 590–601.

    Google Scholar 

  70. 70.

    Tokarski, J.S. and Hopfinger, A.J., Three-dimensional molecular shape and analysis-quantitative structure- activity relationship of a series of cholecystokinin-A receptor antagonists, J. Med. Chem., 37 (1994) 3639–3654.

    Google Scholar 

  71. 71.

    Burke, B.J., Dunn, W.J. III and Hopfinger, A.J., Construction of a molecular shape analysis-three-dimensinoal quantitative structure-analysis relationship for an analog series of pyridobenzodiazepinone inhibitor of muscarinic 2 and 3 receptor, J. Med. Chem., 37 (1994) 3775–3788.

    Google Scholar 

  72. 72.

    Rhyu, K.B., Patel, H.C. and Hopfinger, A.J., A 3D-QSAR study of anticoccoidial triazines using molecular shape analysis, J. Chem. Inf. Comput. Sci., 35 (1995) 771–778.

    Google Scholar 

  73. 73.

    Holzgrabe, U. and Hopfinger, A.J., Conformational analysis, molecular shape comparison, and pharma-cophore identification of different allosteric modulators of muscarinic receptors, J. Chem. Inf. Comput. Sci., 36 (1996) 1018–1024.

    Google Scholar 

  74. 74.

    Rum, G. and Herndon, W.C., Molecular similarity concepts: 5. Analysis of steroid protein binding constants, J. Am. Chem. Soc., 113 (1991) 9055–9060.

    Google Scholar 

  75. 75.

    Good, A.C., So, S. and Richards, W.G., Structure Activity Relationships from Similarity Matrices, J. Med. Chem., 36 (1993) 433–438.

    Google Scholar 

  76. 76.

    Horwell, D.C., Howson, W., Higginbottom, M., Naylor, D., Ratcliffe, G.S. and Williams, S., Quantitative structure-activity relationships (QSARs) of N-terminus fragments of NK1 tachykinin antagonists: A comparison of classical QSARs and three-dimensional QSARs from similarity matrices, J. Med. Chem., 38 (1995) 4454–4462.

    Google Scholar 

  77. 77.

    Good, A.C., Ewing, T.J.A., Gschwend, D.A. and Kuntz, I.D., New molecular shape descriptors: Application in database screening, J. Comput.-Aided Mol. Design, 9 (1995) 1–12.

    Google Scholar 

  78. 78.

    Bemis, G.W. and Kuntz, I.D., A fast efficient method for 2D and 3D molecular shape description, J. Comput.-Aided Mol. Design, 6 (1992) 607–628.

    Google Scholar 

  79. 79.

    Fisanick, W., Cross, K.P. and Rusinko, A. III, Similarity searching on CAS registry substances: 1. Global molecular property and generic atom triangle geometric searching, J. Chem. Inf. Comput. Sci., 32 (1992) 664–674.

    Google Scholar 

  80. 80.

    Norel, R., Fischer, D., Wolfson, H.J. and Nussinov, R., Molecular Surface Recognition by a Computer Vision Based Technique, Protein Eng., 7 (1994) 39–46.

    Google Scholar 

  81. 81.

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

    Google Scholar 

  82. 82.

    Good, A.C. and Kuntz, I.D., Investigating the extension of pair-wise distance pharmacophore measures to triplet based descriptors, J. Comput.-Aided Mol. Design, 9 (1995) 373–379.

    Google Scholar 

  83. 83.

    Pickett, S.D., Mason, J.S. and Mclay, I.M., Diversity profiling and design using 3D pharmacophores - pharmacophore derived queries (PDQ), J. Chem. Inf. Comput. Sci., 36 (1996) 1214–1233.

    Google Scholar 

  84. 84.

    Davies, E.K. and Briant, C., Combinatorial chemistry library design using pharmacophore diversity, URL http://www.awod.com/netsci/Science/Combichem/feature05.htlm.

  85. 85.

    Chem-Diverse, developed and distributed by Chemical Deisng Ltd., Roundway House, Cromwell Park, Chipping Norton, Oxon OX7 5SR, U.K.

  86. 86.

    Lewis, R.A., Good, A.C. and Pickett, S.D., Quantification of molecular similarity and its application to combinatorial chemistry, In Computer-assisted lead finding and optimization, Proceedings of the 11th European Symposium on QSAR, Lausanne, Switzerland, 1996, van de Waterbeemd, H., Testa, B. and Folkers, G. (Eds.) Wiley-VCH, Basel, 1997, 135–156.

    Google Scholar 

Download references


Rights and permissions

Reprints and Permissions

About this article

Cite this article

Good, A.C., Richards, W.G. Excplicit calculation of 3D molecular similarity. Perspectives in Drug Discovery and Design 9, 321–338 (1998). https://doi.org/10.1023/A:1027280526177

Download citation


  • Polymer
  • Molecular Similarity