CODESSA PublicationsThe following is a selection of publications on the research done by using the

CODESSA PRO (CODESSA) software (as of March 1st, 2006).

1. Prediction of hERG potassium channel affinity by the CODESSA approach,(A. Coi, I. Massarelli, L. Murgia, M. Saraceno, V. Calderone, A.M. Bianucci)Bioorg. & Med. Chem., 2006, 14, 3153.

2. QSPR analysis for infinite dilution activity coefficients of organic compounds(K. Tämm, P. Burk) J. Mol. Model., 2006, 12, 417.

3. QSAR study of polychlorinated dibenzodioxins, dibenzofurans, andBiphenyls using the heuristic method and support vector machine (F. Luan,W.P. Ma, X.Y. Zhang, H.X. Zhang, M.C. Liu, Z.D. Hu, B.T. Fan), QSAR &Comb. Sci., 2006, 25, 46.

4. QSPR Modeling of Lanthanide-Organic Complex Stability Constants (R.Svetlitski, A. Lomaka, M. Karelson), Separat. Sci. Technol., 2006, 41, 197.

5. Reparameterized Austin Model 1 for the Quantitative Structure-PropertyRelationships in Liquid Media (D.A. Dobchev, M. Karelson), J. Mol. Model.,2006, 12, 503.

6. QSAR Study of Mosquito Repellents Using Codessa Pro (A.R. Katritzky, D.A.Dobchev, I. Tulp, D.A. Carlson, M. Karelson), Bioorg. & Med. Chem. Lett., 2006,16, 2306.

7. Antimalarial Activity: A QSAR Modeling Using CODESSA PRO Software(A.R. Katritzky, D.C. Fara, I. Slavova, D.A. Dobchev, M. Karelson ), Bioorg. &Med. Chem., 2006, 14, 2333.

8. Development of quantitative structure gas chromatographic relativeretention time models on seven stationary phases for 209 polybrominateddiphenyl ether congeners (Y.W. Wang, A. Li, H.X. Liu, Q.H. Zhang, W.P. Ma,W.L. Song, G.B. Jiang), J. Chromatogr. A, 2006, 1103, 314.

9. Open Computing Grid for Molecular Science and Engineering, (S. Sild, U.Maran, A. Lomaka, and M. Karelson), J. Chem. Inf. Model., 2006, 46, ASAP.

10. QSPR Correlation of Melting Point for Drug Compounds Based on DifferentSources of Molecular Descriptors (H. Modarresi, J.C. Dearden,, and H.Modarress), J. Chem. Inf. Model., 2006, 46, ASAP.

11. Combination of a Modified Scoring Function with Two-DimensionalDescriptors for Calculation of Binding Affinities of Bulky, Flexible Ligandsto Proteins (C. Hetényi, G. Paragi, U. Maran, Z. Timár, M. Karelson, and B.Penke), J. Am. Chem. Soc., 2006, 128, 1233.

12. QSAR studies on 1-phenylbenzimidazoles as inhibitors of the platelet-derived growth factor (Katritzky AR, Dobchev DA, Fara DC, Karelson M)Bioorg & Med. Chem 2005, 13, 6598.

13. QSAR Model for Predicting Pesticide Aquatic Toxicity (P. Mazzatorta, M.Smiesko, E. Lo Piparo, and E. Benfenati), J. Chem. Inf. Model., 2005, 45, 1767.

14. Variable selection and interpretation in structure-affinity correlationmodeling of estrogen receptor binders (Marini F, Roncaglioni A, Novic M) J.Chem. Inf. Model., 2005, 45, 1507.

15. The classification of solvents by combining classical QSPR methodology withprincipal component analysis (Katritzky AR, Fara DC, Kuanar M, Hur E,Karelson M) J. Phys. Chem A, 2005, 109, 10323.

16. Accurate quantitative structure-property relationship model to predict thesolubility of C-60 in various solvents based on a novel approach using a least-squares support vector machine (Liu HX, Yao XJ, Zhang RS, Liu MC, Hu ZD,Fan BT) J. Phys. Chem B, 2005, 109, 20565.

17. QSAR modeling of blood : air and tissue : air partition coefficients usingtheoretical descriptors (Katritzky AR, Kuanar M, Fara DC, Karelson M, AcreeWE, Solov'ev VP, Varnek A), Bioorg & Med. Chem 2005, 13, 6450.

18. QSPR prediction of GC retention indices for nitrogen-containing polycyclicaromatic compounds from heuristically computed molecular descriptors (Hu

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RJ, Liu HX, Zhang RS, Xue CX, Yao XJ, Liu MC, Hu ZD, Fan BT) Talanta,2005, 68, 31.

19. Prediction of pK(a) for neutral and basic drugs based on radial basisfunction neural networks and the heuristic method (Luan F, Ma WP, ZhangHX, Zhang XY, Liu MC, Hu ZD, Fan BT), Pharm. Res., 2005, 22, 1454.

20. QSAR study on thiazole and thiadiazole analogues as antagonists for theadenosine A(1) and A(3) receptors (Borghini A, Pietra D, Domenichelli P,Bianucci AM) Bioorg & Med. Chem 2005, 13, 5330.

21. RP-HPLC determination of lipophilicity of 22 penicillins, their correlationwith reported values and establishment of quantitative structure-log K-Wrelationships, (Grover M, Gulati M, Singh B, Singh S), QSAR & Comb. Sci.,2005, 24, 639.

22. An application of the QM-QSAR method to predict and rationalizelipophilicity of simple monomers (Holder AJ, Ye L, Yourtee DM, Agarwal A,Eick JD, Chappelow CC) Dental Materials, 2005, 21, 591.

23. Prediction of retention time of a variety of volatile organic compounds basedon the heuristic method and support vector machine (Luan F, Xue CX, ZhangRS, Zhao CY, Liu MC, Hu ZD, Fan BT), Anal. Chem. Acta, 2005, 537, 101.

24. Support vector machine and the heuristic method to predict the solubility ofhydrocarbons in electrolyte (Ma WP, Zhang XY, Luan F, Zhang HX, ZhangRS, Liu MC, Hu ZD, Fang BT) J. Phys. Chem A, 2005, 109, 3485.

25. QSPR treatment of the soil sorption coefficients of organic pollutants(I. Kahn, D. Fara, M. Karelson, U. Maran, P.L. Andersson), J. Chem. Inf. Model.,2005, 45, 94.

26. A general treatment of solubility. 3. Principal component analysis (PCA) ofthe solubilities of diverse solutes in diverse solvents (Katritzky AR, Tulp I,Fara DC, Lauria A, Maran U, Acree WE) J. Chem. Inf. Model., 2005, 45, 913.

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27. Study of quantitative structure-mobility relationship of the peptides based onthe structural descriptors and support vector machines (Liu HX, Yao XJ, XueCX, Zhang RS, Liu MC, Hu ZD, Fan BT), Anal. Chem. Acta, 2005, 542, 249.

28. How chemical structure determines physical, chemical, and technologicalproperties: An overview illustrating the potential of quantitative structure-property relationships for fuels science (A.R. Katritzky, D.C Fara), Energy &Fuels 2005, 19, 922.

29. The prediction of human oral absorption for diffusion rate-limited drugsbased on heuristic method and support vector machine (Liu HX, Hu RJ,Zhang RS, Yao XJ, Liu MC, Hu ZD, Fan BT), J. Comput-Aid. Mol. Design, 2005,19, 33.

30. QSAR treatment of drugs transfer into human breast milk (A.R. Katritzky,D.A. Dobchev, E. Hur, D.C Fara, M. Karelson), Bioorg & Med. Chem 2005, 13,1623.

31. Quantitative structure-property relationship (QSPR) models for boilingpoints, specific gravities, and refraction indices of hydrocarbons (Z.Y. Ha ,Z. Ring , S.J. Liu), Energy & Fuels 2005, 19, 152.

32. Application of counterpropagation artificial neural network for modellingproperties of fish antibiotics (E. Maran, M. Novic, P. Barbieri, J. Zupan), SAR& QSAR in Environ. Res. 2004, 15, 469.

33. Using variable and fixed topological indices for the prediction of reactionrate constants of volatile unsaturated hydrocarbons with OH radicals (M.Pompe, M. Veber, M. Randic, A.T.), Molecules, 2004, 9, 1160.

34. Quantitative structure-property relationship modeling of β-cyclodextrincomplexation free energies (A.R. Katritzky, D.C Fara, H.F. Yang, M. Karelson,T. Suzuki, V.P. Solov'ev, A. Varnek) J. Chem. Inf. Comput. Sci., 2004, 44, 529.

35. A quantitative structure-property relationship study of lithium cationbasicities (K. Tämm, D.C. Fara, A.R. Katritzky, P. Burk, M. Karelson, J. Phys.Chem. A, 2004, 108, 4812.

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36. Quantitative Aspects of Solvent Polarity, (A.R. Katritzky, D. Fara, H. Yang, T.Tamm, M. Karelson) Chem. Rev., 2004, 104, 175.

37. Quantitative prediction of logk of peptides in high-performance liquidchromatography based on molecular descriptors by using the heuristicmethod and support vector machine. (H. X. Liu, C. X. Xue, R. S. Zhang, X. J.Yao, M. C. Liu, Z. D. Hu, and B. T. Fan) J Chem Inf Comput Sci, 2004, 44, 1979.

38. "In silico" design of new uranyl extractants based on phosphoryl-containingpodands: QSPR studies, generation and screening of virtual combinatoriallibrary, and experimental tests (A. Varnek, D. Fourches, V.P. Solov'ev, V.E.Baulin, A.N. Turanov, V.K. Karandashev, D. Fara, A.R. Katritzky) J. Chem. Inf.Comput. Sci., 2004, 44, 1365.

39. QSPR of 3-aryloxazolidin-2-one antibacterials (A.R. Katritzky, D.C. Fara, M.Karelson) Bioorg & Med. Chem 2004, 12, 3027.

40. QSPR treatment of rat blood : air, saline : air and olive oil: air partitioncoefficients using theoretical molecular descriptors (A.R. Katritzky, M.Kuanar, D.C. Fara, M. Karelson, W.E. Acree) Bioorg & Med. Chem 2004, 12,4735.

41. QSPR models for various physical properties of carbohydrates based onmolecular mechanics and quantum chemical calculations. (J.D. Dyekjaer,S.Ó. Jónsdóttir) Carbohydr. Res. 2004, 339, 269.

42. QSAR and classification models of a novel series of COX-2 selectiveinhibitors: 1,5-diarylimidazoles based on support vector machines (Liu HX,Zhang RS, Yao XJ, Liu MC, Hu ZD, Fan BT), J. Comput.-Aid. Mol. Design,2004, 18, 389.

43. Quantum-connectivity descriptors in modeling solubility of environmentallyimportant organic compounds (E. Estrada, E.J. Delgado, J.B. Alderete, G.A.Jana) J. Comput. Chem., 2004, 25, 1787.

44. Comparative study of QSAR/QSPR correlations using support vectormachines, radial basis function neural networks, and multiple linearregression (Yao XJ, Panaye A, Doucet JP, Zhang RS, Chen HF, Liu MC, HuZD, Fan BT), J. Chem. Inf. Comput. Sci., 2004, 44, 1257.

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45. Quantitative structure-activity relationships of alpha(1) adrenergicantagonists (S. Eric, T. Solmajer, J. Zupan, M. Novic, M. Oblak, D. Agbaba) J.Mol. Modeling, 2004, 10, 139.

46. Quantitative structure-activity relationships of Streptococcus pneumoniaeMurD transition state analogue inhibitors (M. Kotnik, M. Oblak, J. Humljan,S. Gobec, U. Urleb, T. Solmajer) QSAR & Comb. Sci. 2004, 23, 399.

47. Study of quantitative structure-mobility relationship of carboxylic andsulphonic acids in capillary electrophoresis (C.X. Xue, H.X. Liu, X.J. Yao,M.C. Liu, Z. Hu, B.T. Fan, J. Chromatogr. A 2004, 1048, 233.

48. QSAR for toxicities of polychlorodibenzofurans, polychlorodibenzo-1,4-dioxins, and polychlorobiphenyls (A. Beteringhe, A.T. Balaban) ARKIVOC2004 (1) 163.

49. QSAR study using topological indices for inhibition of carbonic anhydrase IIby sulfanilamides and Schiff bases (A.T. Balaban, S.C. Basak, A. Beteringhe,D. Mills, C.T. Supuran) Molecular Diversity, 2004, 8, 401.

50. Using Variable and Fixed Topological Indices for the Prediction of ReactionRate Constants of Volatile Unsaturated Hydrocarbons with OH Radicals(M.Pompe, M. Veber, M Randić, A.T. Balaban) Molecules, 2004, 9, 1160.

51. Application of Artificial Neural Networks to the QSPR Study, (M. Novič, A.Roncaglioni) Kem. Ind. 2004, 53, 323.

52. Tuning Neural and Fuzzy-Neural Networks for Toxicity Modeling (P.Mazzatorta, E. Benfenati, C.-D. Neagu, G. Gini) J. Chem. Inf. Comput. Sci., 2003,43, 513.

53. A general treatment of solubility. 1. The QSPR correlation of solvation freeenergies of single solutes in series of solvents (A.R. Katritzky, A.A. Oliferenko,P.V. Oliferenko, R. Petrukhin, D.B. Tatham, U. Maran, A. Lomaka, W.E. Acree)J. Chem. Inf. Comput. Sci., 2003, 43, 1794.

54. A general treatment of solubility. 2. QSPR prediction of free energies ofsolvation of specified solutes in ranges of solvents (A.R. Katritzky, A.A.

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Oliferenko, P.V. Oliferenko, R. Petrukhin, D.B. Tatham, U. Maran, A. Lomaka,W.E. Acree) J. Chem. Inf. Comput. Sci., 2003, 43, 1806.

55. QSPR models based on molecular mechanics and quantum chemicalcalculations. 2. Thermodynamic properties of alkanes, alcohols, polyols, andethers. (J.D. Dyekjaer, S.Ó. Jónsdóttir) Ind. & Eng. Chem. Res., 2003, 42, 4241.

56. Chain melting temperature estimation for phosphatidyl cholines by quantummechanically derived quantitative structure property relationships(A.J. Holder, D.M. Yourtee, D.A. White, A.G. Glaros, R. Smith) J. Comp.-Aid.Mol. Des., 2003, 17, 223.

57. Nitrobenzene toxicity: QSAR correlations and mechanistic interpretations(A.R. Katritzky, P. Oliferenko, A. Oliferenko, A. Lomaka, M. Karelson) J. Phys.Org. Chem., 2003, 16, 811.

58. Layer matrices and distance property descriptors (M.V. Diudea, O. Ursu)Ind. J. Chem A., 2003, 42, 1283.

59. Correlation between molecular structures and relative electrophoreticmobility in capillary electrophoresis: Alkylpyridines, (X.J. Yao, B.T. Fan, J.P.Doucet, A. Panaye, M.C. Liu, R.S. Zhang, Z.D. Hu, Chines. J. Chem. 2003, 21,1247.

60. Prediction of boiling points of ketones using a quantitative structure-property relationship treatment (A. Komasa) Pol. J. Chem. 2003, 77, 1491.

61. Thermodynamic Study of the Solubility of Some Sulfonamides inCyclohexane (F. Martínez, C.M. Ávila, A. Gómez), J. Braz. Chem. Soc., 2003,14, 803.

62. Mutagenicity of aminoazo dyes and their reductive-cleavage metabolites: aQSAR/QPAR investigation (L. Sztandera, A. Garg, S. Hayik, K.L. Bhat, C.W.Bock) Dyes and Pigments, 2003, 59, 117.

63. QSAR modeling of genotoxicity on non-congeneric sets of organiccompounds (U. Maran, S. Sild) Artif. Intell. Rev., 2003, 20, 13.

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64. Predicting melting points of quaternary ammonium ionic liquids (D.M. Eike,J.F. Brennecke, E.J. Maginn) Green Chem., 2003, 5, 323.

65. Six-membered cyclic ureas as HIV-1 protease inhibitors: A QSAR studybased on CODESSA PRO approach (A.R. Katritzky, A. Oliferenko, A.Lomaka, M. Karelson) Bioorg & Med. Chem. Lett. 2002, 12, 3453.

66. QSPR models based on molecular mechanics and quantum chemicalcalculations - 1. Construction of Boltzmann-averaged descriptors foralkanes, alcohols, diols, ethers and cyclic compounds. (J.D. Dyekjaer, K.Rasmussen, S.Ó. Jónsdóttir), J. Mol. Modeling, 2002, 8, 277.

67. Charge-transfer interactions in the inhibition of MAO-A byphenylisopropylamines - a QSAR study (G. Vallejos, M.C. Rezende, B.K.Cassels) J. Comput-Aid. Mol. Design, 2002, 16, 95.

68. Correlation of liquid viscosity with molecular structure for organiccompounds using different variable selection methods (B. Lucic, I. Basic, D.Nadramija, A. Milicevic, N. Trinajstic, T. Suzuki, R. Petrukhin, M. Karelson,A.R. Katritzky) ARKIVOC, 2002, 4, 45.

69. QSPR models derived for the kinetic data of the gas-phase homolysis of thecarbon-methyl bond (R. Hiob, M. Karelson) Comput. & Chem. 2002, 26, 237.

70. Constructing a useful tool for characterizing amino acid conformers bymeans of quantum chemical and graph theory indices (C. Cardenas, M.Obregon, E.J. Llanos, E. Machado, H.J. Bohorquez, J.L. Villaveces, M. E.Patarroyo) Comput. & Chem. 2002, 26, 667.

71. Novel potent 5-HT3 receptor Ligands based on the pyrrolidone structure:Synthesis, biological evaluation, and computational rationalization of theligand-receptor interaction modalities (A. Cappelli, M. Anzini, S. Vomero, L.Mennuni, F. Makovec, E. Doucet, M. Hamon, M.C. Menziani, P.G. De Benedetti,G. Giorgi, C. Ghelardini, S. Collina) Bioorg & Med. Chem. 2002, 10, 779.

72. The Present Utility and Future Potential to Medicinal Chemistry ofQSAR/QSPR with Whole Molecule Descriptors, (A.R. Katritzky, D. Tatham,D. Fara, U. Maran, A. Lomaka, M. Karelson) Current Topics in MedicinalChemistry, 2002, 2, 1333.

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73. QSPR correlation of the melting point for pyridinium bromides, potentialionic liquids (A.R. Katritzky, A. Lomaka, R. Petrukhin, R. Jain, M. Karelson,A.E. Visser, R.D. Rogers) J. Chem. Inf. Comput. Sci., 2002, 42, 71.

74. Correlation of the melting points of potential ionic liquids (imidazoliumbromides and benzimidazolium bromides) using the CODESSA program(A.R. Katritzky, R. Jain, A. Lomaka, R. Petrukhin, M. Karelson, A.E. Visser,R.D. Rogers) J. Chem. Inf. Comput. Sci., 2002, 42, 225.

75. A General QSPR Treatment for Dielectric Constants of Organic Compounds(S. Sild, M. Karelson) J. Chem. Inf. Comput. Sci., 2002, 42, 360.

76. Prediction of Ultraviolet Spectral Absorbance using Quantitative Structure-Property Relationships, (W.L. Fitch, M. McGregor, A.R. Katritzky, A. Lomaka,R. Petrukhin, M. Karelson) J. Chem. Inf. Comput. Sci., 2002, 42, 830.

77. General and class specific models for prediction of soil sorption using variousphysicochemical descriptors (P.L. Andersson, U. Maran, D. Fara, M. Karelson,J.L.M. Hermens) J. Chem. Inf. Comput. Sci., 2002, 42, 1450.

78. A QSPR study of sweetness potency using the CODESSA program (A.R.Katritzky, R. Petrukhin, S. Perumal,, M. Karelson, I. Prakash, N. Desai) Croat.Chem. Acta, 2002, 75, 475.

79. A QSPR model for the prediction of the gas-phase free energies of activationof rotation around the N-C(O) bond (J. Leis, M. Karelson) Comput. & Chem.2002, 26, 667.

80. Mutagenicity of aminoazobenzene dyes and related structures: aQSAR/QPAR investigation (A. Garg, K.L. Bhat, C.W. Bock) Dyes andPigments, 2002, 55, 35.

81. Quantitative Structure–Property Relationships for the Normal BoilingTemperatures of Acyclic Carbonyl Compounds (O. Ivanciuc, T. Ivanciuc, A.T.Balaban), Int. J. Mol. Design, 2002, 1, 252.

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82. QSAR of Flavonoids: 4. Differential Inhibition of Aldose Reductase andp56lck Protein Tyrosine Kinase (A. Štefanič-Petek, A. Krbačič, T. Šolmajer)Croat. Chem. Acta., 2002, 75, 517.

83. QSPR Correlation of Free-Radical Polymerization Chain-TransferConstants for Styrene (A.R. Katritzky, F.H. Ignatz-Hoover, R. Petrukhin, M.Karelson) J. Chem. Inf. Comput. Sci., 2001, 41, 295.

84. Quantum mechanical quantitative structure activity relationships to avoidmutagenicity in dental monomers (D. Yourtee, A.J. Holder, R. Smith, J.A.Morrill, E. Kostoryz, W. Brockmann, A. Glaros, C. Chappelow, D. Eick) J.Biomater. Sci. – Polym. Sci. 2001, 12, 89.

85. Correlation of the Solubilities of Gases and Vapors in Methanol and Ethanolwith Their Molecular Structures (A.R. Katritzky, D.B. Tatham, U. Maran) J.Chem. Inf. Comput. Sci., 2001, 41, 358.

86. CODESSA-Based Theoretical QSPR Model for Hydantoin HPLC-RTLipophilicities (A.R. Katritzky, S. Perumal, R. Petrukhin, E. Kleinpeter) J.Chem. Inf. Comput. Sci., 2001, 41, 569.

87. The variable connectivity index (1)chi(f) versus the traditional moleculardescriptors: A comparative study of (1)chi(f) against descriptors ofCODESSA (M. Randic, M. Pompe) J. Chem. Inf. Comput. Sci., 2001, 41, 631.

88. Factors influencing predictive models for toxicology (E. Benfenati, N. Piclin,A. Roncaglioni, M.R. Vari) SAR QSAR Environm. Res. 2001, 12, 593.

89. A QSRR-Treatment of Solvent Effects on the Decarboxylation of 6-Nitrobenzisoxazole-3-carboxylates Employing Molecular Descriptors (A.R.Katritzky, S. Perumal, R. Petrukhin) J. Org. Chem., 2001, 66, 4036.

90. Interpretation of Quantitative Structure - Property and -ActivityRelationships (A.R. Katritzky, R. Petrukhin, D. Tatham, S. Basak, E. Benfenati,M. Karelson, U. Maran) J. Chem. Inf. Comput. Sci., 2001, 41, 679.

91. Theoretical Descriptors for the Correlation of Aquatic Toxicity ofEnvironmental Pollutants by Quantitative Structure-Toxicity Relationships

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(A.R. Katritzky, D.B. Tatham, U. Maran) J. Chem. Inf. Comput. Sci., 2001, 41,1162.

92. QSPR Analysis of Flash Points (A.R. Katritzky, R. Petrukhin, R. Jain, M.Karelson) J. Chem. Inf. Comput. Sci., 2001, 41, 1521.

93. Perspective on the Relationship between Melting Points and ChemicalStructure (A.R. Katritzky, R. Jain, A. Lomaka, R. Petrukhin, U. Maran, M.Karelson) Crystal Growth & Design, 2001, 1, 261.

94. QSAR Correlations of the Algistatic Activity of 5-Amino-1-aryl-1H-tetrazoles (A.R. Katritzky, R. Jain, R. Petrukhin, S.N. Denisenko, T. Schelenz) S. Q. Env. Res., 2001, 12, 259.

95. QSPR Correlation and Predictions of GC Retention Indexes for Methyl-Branched Hydrocarbons Produced by Insects (A.R. Katritzky, K. Chen, U.Maran, D.A. Carlson) Anal. Chem., 2000, 72, 101.

96. Non-linear QSAR Treatment of Genotoxicity (M. Karelson, S.Sild, U. Maran)Mol. Simulat., 2000, 24, 229.

97. Structurally Diverse Quantitative Structure-Property RelationshipCorrelations of Technologically Relevant Physical Properties (A.R. Katritzky,U. Maran, V.S. Lobanov, M. Karelson) J. Chem. Inf. Comput. Sci., 2000, 40, 1.

98. Prediction of Liquid Viscosity for Organic Compounds by a QuantitativeStructure-Property Relationship (A.R. Katritzky, K. Chen, Y. Wang, M.Karelson, B. Lucic, N. Trinajstic, T. Suzuki, G. Shuurmann) J. Phys. Org.Chem., 2000, 13, 80.

99. Quantitative relationship between rate constants of the gas-phase homolysisof C-X bonds and molecular descriptors (R. Hiob, M. Karelson) J. Chem. Inf.Comput. Sci., 2000, 40, 1062.

100.Quantitative structure-activity relationship of flavonoid analogues. 3.Inhibition of p56(lck) protein tyrosine kinase (M. Oblak, M. Randic, T.Solmajer) J. Chem. Inf. Comput. Sci., 2000, 40, 994.

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101.QSAR equations for N-methyl-(substituted-phenyl)-urethanes byPRECLAV program (L. Tarko) Rev. Roum. Chim., 2000, 45, 809.

102.Improved QSARs for predictive toxicology of halogenated hydrocarbons, (S.Trohalaki, E. Gifford, R. Pachter) Comput. & Chem. 2000, 24, 421.

103.A Comprehensive QSAR Treatment of the Genotoxicity of Heteroaromaticand Aromatic Amines (A.R. Katritzky, U. Maran, M. Karelson) Quant. Struct.Act. Relat. Pharmacol. Chem. Biol., 1999, 18, 3.

104.A New Efficient Approach for Variable Selection Based on Multiregression:Prediction of Gas Chromatographic Retention Times and Response Factors(A.R. Katritzky, B. Lucic, N. Trinajstic, S. Sild, M. Karelson,) J. Chem. Inf.Comput. Sci., 1999, 39, 610.

105.Development of quantitative structure-property relationships usingcalculated descriptors for the prediction of the physicochemical properties (n(D), p, bp, epsilon, eta) of a series of organic solvents (M. Cocchi, P.G. DeBenedetti, R. Seeber, L. Tassi, A. Ulrici) J. Chem. Inf. Comput. Sci., 1999, 39,1190.

106.QSPR Treatment of Solvent Scales (A.R. Katritzky, T. Tamm, Y. Wang, S.Sild, M. Karelson) J. Chem. Inf. Comput. Sci., 1999, 39, 684.

107.A Unified Treatment of Solvent Properties (A.R. Katritzky, T. Tamm, Y.Wang, M. Karelson) J. Chem. Inf. Comput. Sci., 1999, 39, 692.

108.QSPR prediction of densities of organic liquids (M. Karelson, A. Perkson)Comput. & Chem. 1999, 23, 49.

109.Estimation of the liquid viscosity of organic compounds with a quantitativestructure-property model (O. Ivanciuc, T. Ivanciuc, P.A. Filip, D. Cabrol-Bass)J. Chem. Inf. Comput. Sci., 1999, 39, 515.

110.QSPR and QSAR Models Derived Using Large Molecular DescriptorSpaces. A Review of CODESSA Applications (M. Karelson, U. Maran, Y.Wang, A. R. Katritzky) Collect. Czech. Chem. Commun., 1999, 64, 1551.

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111.Insights into Sulfur Vulcanization from QSPR Quantitative Structure-Property Relationship Studies (A.R. Katritzky, F. Ignatz-Hoover, V.S.Lobanov, M. Karelson) Rubber Chem. Technol., 1999, 72, 318.

112.Relevance of theoretical molecular descriptors in quantitative structure-activity relationship analysis of alpha 1-adrenergic receptor antagonists(M.C. Menziani, M. Montorsi, P.G. De Benedetti, M. Karelson) Bioorg & Med.Chem. 1999, 7, 2437.

113.QSAR study in the N-aryl-anthranylic acids class (T. Laszlo) Revista deChemie, 1999, 50, 864.

114.QSPR and QSAR Models Derived with CODESSA Multipurpose StatisticalAnalysis Software. (M. Karelson, U. Maran, Y. Wang, A.A. Katritzky), AAAITech. Report, 1999, SS-99-01, 12.

115.Evaluation of quantitative structure-activity relationship methods for large-scale prediction of chemicals binding to the estrogen receptor (W. Tong, D.R.Lowis, R. Perkins, Y. Chen, W.J. Welsh, D.W. Goddette, T.W. Heritage, D.M.Sheehan) J. Chem. Inf. Comput. Sci., 1998, 38, 669.

116.Normal Boiling Points for Organic Compounds: Correlation and Predictionby a Quantitative Structure - Property Relationship (A.R. Katritzky, V.S.Lobanov, M. Karelson) J. Chem. Inf. Comput. Sci., 1998, 38, 28.

117.Quantitative Structure - Property Relationship (QSPR) Correlation of GlassTransition Temperatures of High Molecular Weight Polymers (A.R.Katritzky, S. Sild, V. Lobanov, M. Karelson) J. Chem. Inf. Comput. Sci., 1998, 38, 300.

118.Correlation of the Aqueous Solubility of Hydrocarbons and HalogenatedHydrocarbons with Molecular Structure (A.R. Katritzky, P.D.T. Huibers) J.Chem. Inf. Comput. Sci., 1998, 38, 283.

119.Relationship of Critical Temperatures to Calculated Molecular Properties(A.R. Katritzky, L. Mu, M. Karelson) J. Chem. Inf. Comput. Sci., 1998, 38, 293.

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120.Quantitative structure-property relationship study of normal boiling pointsfor halogen/oxygen/sulfur-containing organic compounds using theCODESSA program (O. Ivanciuc, T. Ivanciuc, A.T. Balaban), Tetrahedron,1998, 54, 9129.

121.QSPR Studies on Vapor Pressure, Aqueous Solubility, and the Prediction ofWater-Air Partition Coefficients (A.R. Katritzky, Y. Wang, S. Sild, T. Tamm,M. Karelson) J. Chem. Inf. Comput. Sci., 1998, 38, 720.

122.General Quantitative Structure-Property Relationship Treatment of theRefractive Index of Organic Compounds (A.R. Katritzky, S. Sild, M.Karelson) J. Chem. Inf. Comput. Sci., 1998, 38, 840.

123.Theoretical descriptors in quantitative structure - Affinity and selectivityrelationship study of potent N4-substituted arylpiperazine 5-HT1(Alpha)receptor antagonists (M.C. Menziani, P.G. De Benedetti, M. Karelson) Bioorg& Med. Chem. 1998, 6, 535.

124.Correlation and Prediction of the Refractive Indices of Polymers by QSPR(A.R. Katritzky, S. Sild, M. Karelson) J. Chem. Inf. Comput. Sci., 1998, 38,1171.

125.Prediction of Critical Micelle Concentration Using a Quantitative Structure-Property Relationship Approach. 2. Anionic Surfactants (A.R. Katritzky,P.D.T. Huibers, V.S. Lobanov, D.O. Shah, M. Karelson) J. Colloid and InterfaceSci., 1997, 187, 113.

126.QSPR as a Means of Predicting and Understanding Chemical and PhysicalProperties in Terms of Structure (A.R. Katritzky, M. Karelson, V.S. Lobanov) Pure Appl. Chem., 1997, 69, 245.

127.Predicting Surfactant Cloud Point from Molecular Structure (A.R.Katritzky, P.D.T. Huibers, D.O. Shah) J. Colloid and Interface Sci., 1997, 193,132.

128.Prediction of Melting Points for the Substituted Benzenes: A QSPRApproach (A.R. Katritzky, U. Maran, M. Karelson, V.S. Lobanov) J. Chem. Inf.Comput. Sci., 1997, 37, 913.

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129.QSPR Treatment of the Unified Nonspecific Solvent Polarity Scale (A.R.Katritzky, L. Mu, M. Karelson) J. Chem. Inf. Comput. Sci., 1997, 37, 756.

130.QSAR calculation programme (T. Laszlo) Revista de Chemie, 1997, 48, 676.

131.CODESSA version 2.13 for Windows (O. Ivanciuc) J. Chem. Inf. Comput. Sci.,1997, 37, 405.

132.Prediction of Critical Micelle Concentration Using a Quantitative Structure-Property Relationship Approach. 1. Nonionic Surfactants (A.R. Katritzky,P.D.T. Huibers, V.S. Lobanov, D.O. Shah, M. Karelson) Langmuir, 1996, 12,1462.

133.Correlation of Boiling Points with Molecular Structure. 1. A Training Set of298 Diverse Organics and a Test Set of 9 Simple Inorganics (A.R. Katritzky,L. Mu, V.S. Lobanov, M. Karelson) J. Phys. Chem., 1996, 100, 10400.

134.Quantum-Chemical Descriptors in QSAR/QSPR Studies (M. Karelson, V.S.Lobanov, A.R. Katritzky) Chem. Rev., 1996, 96, 1027.

135.Prediction of Polymer Glass Transition Temperatures Using A GeneralQuantitative Structure-Property Relationship Treatment (A.R. Katritzky, P.Rachwal, K.W. Law, M. Karelson, V.S. Lobanov) J. Chem. Inf. Comput. Sci.,1996, 36, 879.

136.A QSPR Study of the Solubility of Gases and Vapors in Water (A.R.Katritzky, L. Mu, M. Karelson) J. Chem. Inf. Comput. Sci., 1996, 36, 1162.

137.Comprehensive Descriptors for Structural and Statistical Analysis. 1Correlations Between Structure and Physical Properties of SubstitutedPyridines (A.R. Katritzky, V.S. Lobanov, M. Karelson, R. Murugan, M.P.Grendze, J.E. Toomey Jr.) Rev. Roum. Chim., 1996, 41, 851.

138.QSPR: The Correlation and Quantitative Prediction of Chemical andPhysical Properties from Structure (A.R. Katritzky, V.S. Lobanov, M.Karelson) Chem. Soc. Rev., 1995, 279.

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139.Predicting Physical Properties from Molecular Structure (A.R. Katritzky,R.Murugan, M.P. Grendze, J.E. Toomey, Jr, M. Karelson, V. Lobanov, P.Rachwal) Chemtech., 1994, 24, 17.

140.Prediction of Gas Chromatographic Retention Times and Response FactorsUsing a General Quantitative Structure-Property Relationship Treatment(A.R. Katritzky, E.S. Ignatchenko, R.A. Barcock, V.S. Lobanov, M. Karelson) Anal. Chem., 1994, 66, 1799.

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