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Quantitative structure-activity relationships (QSAR) and molecular modelling in cancer research

  • Guest Editorial
  • Experimental Oncology
  • Published:
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Summary

The methods of quantitative structure-activity relationships and molecular modelling that have developed during the last 25 years are nowadays widely applied to describe the relationships between chemical structures of molecules and their biological activities in a quantitative manner. In cancer research also, many attempts have been made to understand structure-activity relationships and to design new antitumor drugs on a more rational basis. Owing to the enormous number of publications, only a few, typical examples are reviewed in this editorial. Much emphasis is given to a discussion of the limitations and the inherent problems of all the different approaches. As a result of the progress in our knowledge derived from experimental methods, the computational methods improve in their predictive ability, thus leading to more reliable results. However, the quantitative description of structure-activity relationships, as well as the modelling of drug-receptor interactions, are still (and will remain for the near future) very difficult. The transport and the distribution of a drug in a biological system is a function of its lipophilicity and its degree of dissociation or ionization at the pH value of the aqueous phases of the system. The interaction of the drug with its binding site at the receptor is determined by the lipophilicity pattern, the charge distribution, the electron density, and the polarizability pattern at the surface of the molecule. Of course, the three-dimensional structure of the molecule is of utmost importance for its fit to the binding site; however, in the case of a more or less flexible molecule, the bound conformation need not be identical to the minimum energy conformation; a less favored conformation may bind to the receptor, when the net interaction energy is large enough to compensate for the energy differences, provided the energy barriers between these conformations are not too large. Not only the ligand, but also the binding site can change its conformation, thus, a flexible fit between both partners occurs. Additional complications arise from different binding modes of chemically closely related molecules, from the insertion of water molecules at the binding site, and from entropy effects. Nature, as well as science, is not trivial. How can we then expect simple answers to complex questions?

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Abbreviations

QSAR:

quantitative structure-activity relationships

NMR:

nuclear magnetic resonance

References

  • Atwell GJ, Baguley BC, Finlay GJ, Rewcastle GW, Denny AW (1986) Potential antitumor agents: 47. 3′-Methylamino analogues of amsacrine with in vivo solid tumor activity. J Med Chem 29:1769–1776

    Google Scholar 

  • Badger J, Minor I, Kremer MJ, Oliveira MA, Smith TJ, Griffith JP, Guerin DMA, Krishnaswamy S, Luo M, Rossmann MG, McKinlay MA, Diana GD, Dutko FJ, Fancher M, Rueckert RR, Heinz BA (1988) Structural analysis of a series of antiviral agents complexed with human rhinovirus 14. Proc Natl Acad Sci USA 85:3304–3308

    Google Scholar 

  • Balaban AT, Niculescu-Duvaz I, Simon Z (1987) Topological aspects of QSAR for biologically active molecules. Acta Pharm Jugosl 37: 7–35

    Google Scholar 

  • Balaji VN, Dixon JS, Smith DH, Venkataraghavan R, Murdock KC (1985) Design of anticancer drugs using modeling techniques. Ann NY Acad Sci 439: 140–161

    Google Scholar 

  • Blaney JM, Hansch C, Silipo C, Vittoria A (1984) Structure-activity relationships of dihydrofolate reductase inhibitors. Chem Rev 84: 333–407

    Google Scholar 

  • Broyde S, Hingerty BE (1988) Conformations of DNA modified by aromatic amines: Minimized semiempirical potential energy calculations and model building. In: Silverman BD (ed) Computer simulation of carcinogenic processes. CRC Press, Boca Raton, Fl, pp 117–140

    Google Scholar 

  • Chan CL, Lien EJ, Tokes ZA (1987) Synthesis, biological evaluation, and quantitative structure-activity relationship analysis of 2-hydroxy-1H-isoindolediones as new cytostatic agents. J Med Chem 30: 509–514

    Google Scholar 

  • Chririac A, Dragomir O, Motoc F, Motoc I (1979) A Fujita-Ban analysis of antitumoral activity of Schiff bases. Univ Timisoara [Prepr], Ser Chim; ref CA 93: 187549k

  • Clark T (1988) Molecular orbital and force-field calculations for structure and energy predictions. In: Jochum C, Hicks MG, Sunkel J (eds) Physical property prediction in organic chemistry. Springer, Berlin Heidelberg, New York, pp 95–101

    Google Scholar 

  • Coats EA, Shah KJ, Milstein SR, Genther CS, Nene DM, Roesener J, Schmidt J, Pleiss M, Wagner E, Baker JK (1982) 4-Hydroxyquinoline-3-carboxylic acids as inhibitors of cell respiration. 2. Quantitative structure-activity relationship of dehydrogenase enzyme and Ehrlich ascites tumor cell inhibitions. J Med Chem 25: 57–63

    Google Scholar 

  • Coats EA, Milstein SR, Pleiss MA, Roesener JA, Schmidt J, McDonald J, Reed R (1983) Comparative analysis of cellular respiratory inhibition by substituted phenylglyoxal bis(4-methyl-3-thiosemicarbazone) zinc chelates. Farm Ed Sci 38: 143–152

    Google Scholar 

  • Cuthbertson AF, Thomson C (1987) Electrostatic potentials of tumor promoters. J Mol Graphics 5: 92–96

    Google Scholar 

  • De AU, Pal D (1976) Quantitative structure-activity relationship (QSAR) and rational drug design for some antineoplastic thalidomide and glutarimide derivatives. J Indian Chem Soc 53: 1049–1052

    Google Scholar 

  • Denny WA, Cain BF, Atwell GJ, Hansch C, Panthananickal A, Leo A (1982) Potential antitumor agents 36. Quantitative relationships between experimental antitumor activity, toxicity, and structure for the general class of 9-anilinoacridine antitumor agents. J Med Chem 25: 276–315

    Google Scholar 

  • Denny WA, Atwell GJ, Baguley BC, Rewcastle GW (1984) QSAR in the design of potential antitumor agents: the example of the 9-anilinoacridines. In: Kuchar M (ed) QSAR Des Bioact Compd. Prous, Barcelona, pp 97–116

    Google Scholar 

  • Dove S, Coats E, Scharfenberg P, Franke R (1985) 7-Substituted 4-hydroxyquinoline 3-carboxylic acids as inhibitors of dehydrogenase enzymes and of the respiration of Ehrlich ascites tumor cells: multivariate analyses and quantitative structure-activity relationship for polar substituents. J Med Chem 28: 447–451

    Google Scholar 

  • Dunn III WJ, Wold S (1981) The carcinogenicity ofN-nitroso compounds: a SIMCA pattern recognition study. Bioorg Chem 10: 29–45

    Google Scholar 

  • Dunn III WJ, Greenberg MJ, Callejas SS (1976) Use of cluster analysis in the development of structure-activity relations for antitumor triazenes. J Med Chem 19: 1299–1301

    Google Scholar 

  • Dunn III WJ, Wold S, Edlund U, Hellberg S, Gasteiger J (1984) Multivariate structure-activity relationships between data from a battery of biological tests and an ensemble of structure descriptors: the PLS method. Quant Struct-Act Relat 3: 131–137

    Google Scholar 

  • Ebert C, Lassiani L, Linda P, Nisi C, Alunni S, Clementi S (1984) Chemometric investigation of antitumor tests. Quant Struct-Act Relat 3: 143–147

    Google Scholar 

  • Enslein K, Craig PN (1982) Carcinogenesis: a predictive structureactivity model. J Toxicol Environ Health 10: 521–530

    Google Scholar 

  • Fink SI, Leo A, Yamakawa M, Hansch C, Quinn FR (1980) The quantitative structure-selectivity relationship of anthracycline antitumor activity and cardiac toxicity. Farm Ed Sci 35: 965–979

    Google Scholar 

  • Free Jr SM, Wilson JW (1964) A mathematical contribution to structure-activity studies. J Med Chem 7: 395–399

    Google Scholar 

  • Hansch C (1971) Quantitative structure-activity relationships in drug design. In: Ariëns EJ (ed) Drug design, vol 1. Academic Press, New York, pp 271–342

    Google Scholar 

  • Hansch C (1979) QSAR in cancer chemotherapy. Farm Ed Sci 34: 89–104

    Google Scholar 

  • Hansch C (1984/85) The QSAR paradigm in the design of less toxic molecules. Drug Metab Rev 15: 1279–1294

    Google Scholar 

  • Hansch C, Clayton JM (1973) Lipophilic character and biological activity of drugs. II: the parabolic case. J Pharm Sci 62: 1–21

    Google 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

    Google Scholar 

  • Hansch C, Steward AR, Isawa J (1965) The correlation of localisation rates of benzeneboronic acids in brain and tumor tissue with substituent constants. Mol Pharmacol 1: 87–92

    Google Scholar 

  • Hansch C, Silipo C, Steller EE (1975) Formulation of de novo substituent constants in correlation analysis: inhibition of dihydrofolate reductase by 2,4-diamino-5-(3,4-dichlorophenyl)-6-substituted pyrimidines. J Pharm Sci 64: 1186–1191

    Google Scholar 

  • Hansch C, Hatheway GJ, Quinn FR, Greenberg N (1978) Antitumor 1-(X-aryl)-3,3-dialkyltriazenes:2. On the role of correlation analysis in decision making in drug modification toxicity quantitative structure-activity relationships of 1-(X-phenyl)-3,3-dialkyltriazenes in mice. J Med Chem 21: 574–577

    Google Scholar 

  • Hansch C, Leo A, Schmidt C, Jow PYC, Montgomery JA (1980) Antitumor structure-activity relationships. Nitrosoureas vs L-1210 leukemia. J Med Chem 23: 1095–1101

    Google Scholar 

  • Henry DR, Jurs PC, Denny WA (1982) Structure-antitumor activity relationships of 9-anilinoacridines using pattern recognition. J Med Chem 25: 899–908

    Google Scholar 

  • Hodes L (1986) A two-component approach for predicting antitumor activity from chemical structure in large scale screening. J Med Chem 29: 2207–2212

    Google Scholar 

  • Hopfinger AJ (1981) A general QSAR for dihydrofolate reductase inhibition by 2,4-diaminotriazines based upon molecular shape analysis. Arch Biochem Biophys 206: 153–163

    Google Scholar 

  • Hopfinger AJ (1984) A QSAR study of the Ames mutagenicity of 1-(X-phenyl)-3,3-dialkyltriazenes using molecular potential energy fields and molecular shape analysis. Quant Struct-Act Relat 3: 1–5

    Google Scholar 

  • Irie K, Hagiwara N, Tokuda H, Koshimizu K (1987) Structure-activity studies of the indole alkaloid tumor promoter teleocidins. Carcinogenesis 8: 547–552

    Google Scholar 

  • Itai A, Kato Y, Tomioka N, Iitaka Y, Endo Y, Hasegawa M, Shudo K, Fujiki H, Sakai S (1988) A receptor model for tumor promoters: rational superposition of teleocidines and phorbol esters. Proc Natl Acad Sci USA 85: 3688–3692

    Google Scholar 

  • Jeffrey AM, Liskamp RMJ (1986) Computer-assisted molecular modeling of tumor promoters: rationale for the activity of phorbol esters, teleocidin B, and aplysiatoxin. Proc Natl Acad Sci USA 83: 241–245

    Google Scholar 

  • Johnels D, Gillner M, Norden B, Toftgard R, Gustafsson JA (1989) Quantitative structure-activity relationship (QSAR) analysis using the partial least squares (PLS) method: the binding of polycyclic aromatic hydrocarbons (PAH) to the rat liver 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) receptor. Quant StructAct Relat 8: 83–89

    Google Scholar 

  • Jones EY, Stuart DI, Walker NPC (1989) Structure of tumour necrosis factor. Nature 338: 225–228

    Google Scholar 

  • Jurs PC, Hasan MN, Henry DR, Stouch TR, Whalen-Pedersen EK (1983) Computer-assisted studies of molecular structure and carcinogenic activity. Fundam Appl Toxicol 3: 343–349

    Google Scholar 

  • Jurs PC, Stouch TR, Czerwinski M, Narvaez JN (1985) Computerassisted studies of molecular structure-biological activity relationships. J Chem Inf Comput Sci 25: 296–308

    Google Scholar 

  • Kier LB, Simons RJ, Hall LH (1978) Structure-activity studies on mutagenicity of nitrosamines using molecular connectivity. J Pharm Sci 67: 725–726

    Google Scholar 

  • Klopman G, Macina OT (1987) Computer-automated structure evaluation of antileukemic 9-anilinoacridines. Mol Pharmacol 31:457–476

    Google Scholar 

  • Kubinyi H (1977) Quantitative structure activity relationships. 7. The bilinear model, a new model for nonlinear dependence of biological activity on hydrophobic character. J Med Chem 20: 625–629

    Google Scholar 

  • Kubinyi H (1988) Free Wilson analysis. Theory, applications and its relationship to Hansch analysis. Quant Struct-Act Relat 7:121–133

    Google Scholar 

  • Kuroda R, Neidle S (1988) Crystallographic and computer-modeling studies on the metabolites of polycyclic aromatic hydrocarbons and their interactions with nucleic acids. In: Silverman BD (ed) Computer simulation of carcinogenic processes. CRC Press, Boca Raton, Fl, pp 141–168

    Google Scholar 

  • Leavitt SA, Mass MJ (1985) Computer-assisted correlation of structure and biological activity in a set of retinoids. Cancer Res 45: 4741–4747

    Google Scholar 

  • Leo A, Panthananickal A, Hansch C, Theiss J, Shimkin M, Andrews AW (1981) A comparison of mutagenic and carcinogenic activities of aniline mustards. J Med Chem 24: 859–864

    Google Scholar 

  • Lewis DFV (1989) Molecular orbital calculations on tumor-inhibitory phenyl aziridines: QSARs. Xenobiotica 19: 341–356

    Google Scholar 

  • Marshall GR (1987) Computer-aided drug design. Annu Rev Pharmacol Toxicol 27: 193–213

    Google Scholar 

  • Maysinger D, Birus M, Movrin M (1979) Structure-activity relationships of isatinN-Mannich bases deduced from the Free-Wilson model. Acta Pharm Jugosl 29: 15–18

    Google Scholar 

  • McFarland JW, Gans DJ (1987) Cluster significance analysis in quantitative structure-activity relationship (QSAR). Pharmacochem Libr 10: 25–29

    Google Scholar 

  • Miyashita Y, Seki T, Takahashi Y, Daiba S, Tanaka Y, Yotsui Y, Abe H, Sasaki S (1981) Computer-assisted structure-carcinogenicity studies on polycyclic aromatic hydrocarbons by pattern recognition methods. Anal Chim Acta 133: 603–613

    Google Scholar 

  • Mohammad SN, Hopfinger AJ, Bickers DR (1983) Intrinsic mutagenicity of polycyclic aromatic hydrocarbons: a quantitative structure-activity study based upon molecular shape analysis. J Theor Biol 102: 323–331

    Google Scholar 

  • Moore MH, Hunter WN, Langlois d'Estaintot B, Kennard O (1989) DNA-drug interactions. The crystal structure of d(CGATCG) complexed with daunomycin. J Mol Biol 206: 693–705

    Google Scholar 

  • Moriguchi I, Komatsu K (1977) Adaptive least-squares classification applied to structure-activity correlation of antitumor mitomycin derivatives. Chem Pharm Bull 25: 2800–2802

    Google Scholar 

  • Nasr M, Paull KD, Narayanan VL (1984) Computer-assisted structure-activity correlations. Adv Pharmacol Chemother 20: 123–190

    Google Scholar 

  • Nasr M, Paull KD, Narayanan VL (1985) Computer-assisted structure-anticancer activity correlations of carbamates and thiocarbamates. J Pharm Sci 74: 831–836

    Google Scholar 

  • Neidle S (1984) Computer graphics in the study of drug-nucleic acid interactions. Biochem Soc Trans 12:1008–1011

    Google Scholar 

  • Neidle S, Abraham ZHL, Collier DA, Islam SA (1987) Application of computer-assisted modeling to structure-activity studies with intercalating drugs. Bristol-Myers Cancer Symp 8:83–109

    Google Scholar 

  • Niculescu-Duvaz I, Simon Z, Voiculet N (1985) QSAR application in chemical carcinogenesis: II. QSAR analysis of a class of carcinogenesis inhibitors: retinoids. Carcinogenesis 6: 479–486

    Google Scholar 

  • Nilsson LM, Carter RE, Sterner O, Liljefors T (1988) Structure-activity relationships for unsaturated dialdehydes: 2. A PLS correlation of theoretical descriptors for six compounds with mutagenic activity in the AmesSalmonella assay. Quant Struct-Act Relat 7: 84–91

    Google Scholar 

  • Pet-Edwards J, Rosenkranz HS, Chankong V, Haimes YY (1985) Cluster analysis in predicting the carcinogenicity of chemicals using short-term assays. Mutat Res 153: 167–185

    Google Scholar 

  • Poulos TL, Howard AJ (1987) Crystal structures of metyrapone- and phenylimidazole-inhibited complexes of cytochrome P-450cam. Biochemistry 26: 8165–8174

    Google Scholar 

  • Prakash G, Hodnett EM (1978) Discriminant analysis and structure-activity relationships: 1. Naphthoquinones. J Med Chem 21: 369–374

    Google Scholar 

  • Purcell WP, Clayton JM (1968) Application of regression analyses to antitumor activities of various acetylenic carbamates. J Med Chem 11: 199–203

    Google Scholar 

  • Quinn FR, Neiman Z, Beisler JA (1981) Toxicity quantitative structure-activity relationships of colchicines. J Med Chem 24: 636–639

    Google Scholar 

  • Rao SN, Singh UC, Kollman PA (1986) Molecular mechanics simulations on covalent complexes between anthramycin and B DNA. J Med Chem 29: 2484–2492

    Google Scholar 

  • Rekker RF (1983) Quantitative structure-activity relationship studies around cytotoxic drugs. Dev Pharmacol 3: 23–46

    Google Scholar 

  • Rippmann F (1990) Hydrophobicity and tumor promoting activity of phorbol esters. Quant Struct-Act Relat 9, 1–5

    Google Scholar 

  • Romkes M, Piskorska-Pliszczynska J, Keys B, Safe S, Fujita T (1987) Quantitative structure-activity relationships analysis of interactions of 2,3,7,8-tetrachlorodibenzo-p-dioxin and 2-substituted analogues with rat, mouse, guinea pig, and hamster cytosolic receptor. Cancer Res 47: 5108–5111

    Google Scholar 

  • Rosenkranz HS, Klopman G (1986) Mutagens, carcinogens, and computers. Prog Clin Biol Res[A]209: 71–104

    Google Scholar 

  • Scherrer RA, Howard SM (1977) Use of distribution coefficients in quantitative structure-activity relationships. J Med Chem 20: 53–58

    Google Scholar 

  • Selassie CD, Strong CD, Hansch C, Delcamp TJ, Freisheim JH, Khwaja TA (1986) Comparison of triazines as inhibitors of L1210 dihydrofolate reductase and of L1210 cells sensitive and resistant to methotrexate. Cancer Res 46: 744–756

    Google Scholar 

  • Silverman BD (1988) Molecular conformation and polycyclic aromatic hydrocarbon (PAH) carcinogenesis. In: Silverman BD (ed) Computer simulation of carcinogenic processes. CRC Press, Boca Raton, Fl, pp 91–116

    Google Scholar 

  • Simiti I, Schwartz I, Coman M (1974) Heterocycles XXXVI. Free-Wilson structure-activity study of some substituted thiazoles. Rev Roum Biochim 11: 139–143; ref CA 82: 132793p

    Google Scholar 

  • Stepan A, Badilescu II, Simon Z (1977) Minimal topological difference (MTD) studies of the structure-activity relationship of triazine derivatives inhibiting dihydrofolate reductase. An Univ Timisoara, Ser Stiinte Fiz-Chim 15: 61–71; ref CA 91: 186411s

    Google Scholar 

  • Tinland B (1976) Structure-activity relationship for antitumor thiosemicarbazones. Farm Ed Sci 31: 888–890

    Google Scholar 

  • Venger BH, Hansch C, Hatheway GJ, Amrein YU (1979) Ames test of 1-(X-phenyl)-3,3-dialkyltriazenes. A quantitative structureactivity study. J Med Chem 22: 473–476

    Google Scholar 

  • Wender PA, Cribbs CA, Koehler KF, Sharkey NA, Herald CL, Kamano Y, Pettit GR, Blumberg PM (1988) Modeling of the bryostatins to the phorbol ester pharmacophore in protein kinase C. Proc Natl Acad Sci USA 85: 7197–7201

    Google Scholar 

  • Wishnok JS, Archer MC, Edelman AS, Rand WM (1978) Nitrosamine carcinogenicity: a quantitative Hansch-Taft structure-activity relationship. Chem Biol Interact 20: 43–54

    Google Scholar 

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  1. Wirkstoffdesign, Hauptlaboratorium BASF AG, D-6700, Ludwigshafen, Federal Republic of Germany

    Hugo Kubinyi

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The “Journal of Cancer Research and Clinical Oncology” publishes in loose succession “Editorials” and “Guest editorials” on current and/or controversial problems in experimental and clinical oncology. These contributions represent exclusively the personal opinion of the author

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Kubinyi, H. Quantitative structure-activity relationships (QSAR) and molecular modelling in cancer research. J Cancer Res Clin Oncol 116, 529–537 (1990). https://doi.org/10.1007/BF01637071

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