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Collect. Czech. Chem. Commun. 1999, 64, 1551-1571
https://doi.org/10.1135/cccc19991551

QSPR and QSAR Models Derived Using Large Molecular Descriptor Spaces. A Review of CODESSA Applications

Mati Karelsona,*, Uko Marana, Yilin Wangb and Alan R. Katritzkyb,*

a Department of Chemistry, University of Tartu, 2 Jakobi Str., Tartu 51014, Estonia
b Center for Heterocyclic Compounds, Department of Chemistry, University of Florida, P.O. Box 117200, Gainesville, FL 32611-7200, U.S.A

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  • Zhao Yuankai, Mulder Roger J., Houshyar Shadi, Le Tu C.: A review on the application of molecular descriptors and machine learning in polymer design. Polym. Chem. 2023, 14, 3325. <https://doi.org/10.1039/D3PY00395G>
  • Wang Liangliang, Ding Junjie, Pan Li, Cao Dongsheng, Jiang Hui, Ding Xiaoqin: Quantum chemical descriptors in quantitative structure–activity relationship models and their applications. Chemometrics and Intelligent Laboratory Systems 2021, 217, 104384. <https://doi.org/10.1016/j.chemolab.2021.104384>
  • Yang Liangliang, Pijuan-Galito Sara, Rho Hoon Suk, Vasilevich Aliaksei S., Eren Aysegul Dede, Ge Lu, Habibović Pamela, Alexander Morgan R., de Boer Jan, Carlier Aurélie, van Rijn Patrick, Zhou Qihui: High-Throughput Methods in the Discovery and Study of Biomaterials and Materiobiology. Chem. Rev. 2021, 121, 4561. <https://doi.org/10.1021/acs.chemrev.0c00752>
  • Raznahan Mohammad Moein, Riahi Siavash, Mousavi Seyed Hamed: A simple, robust and efficient structural model to predict CO2 absorption for different amine solutions: Concern to design new amine compounds. Journal of Environmental Chemical Engineering 2020, 8, 104572. <https://doi.org/10.1016/j.jece.2020.104572>
  • Rachuru Sanjeev, Vandanapu Jagannadham: Do phase transition temperatures Tmp and Tbp obey linear free energy relationships?. Journal of Molecular Liquids 2020, 302, 112496. <https://doi.org/10.1016/j.molliq.2020.112496>
  • Toropova Alla P.: Medicinal Chemistry and Computational Chemistry: Mutual Influence and Harmonization. MRMC 2020, 20, 1320. <https://doi.org/10.2174/138955752014200626163614>
  • Doucet J. P., Doucet‐Panaye A., Papa E.: Topological QSAR Modelling of Carboxamides Repellent Activity to Aedes Aegypti. Molecular Informatics 2019, 38. <https://doi.org/10.1002/minf.201900029>
  • Cam Ihsan Burak, Yorulmaz Nuri, Yasar Mehmet Murat, Eroglu Erol: Development of Quantitative Structure-Property Relationship (QSPR) Models of Aspartyl-Derivatives Based on Eigenvalues (EVA) of Calculated Vibrational Spectra. Food Biophysics 2019, 14, 300. <https://doi.org/10.1007/s11483-019-09577-z>
  • Gimadiev T.R., Klimchuk O., Nugmanov R.I., Madzhidov T.I., Varnek A.: Sydnone-alkyne cycloaddition: Which factors are responsible for reaction rate ?. Journal of Molecular Structure 2019, 1198, 126897. <https://doi.org/10.1016/j.molstruc.2019.126897>
  • Khaheshi Shima, Riahi Siavash, Mohammadi-Khanaposhtani Mohammad, shokrollahzadeh Hoda: Prediction of Amines Capacity for Carbon Dioxide Absorption Based on Structural Characteristics. Ind. Eng. Chem. Res. 2019, 58, 8763. <https://doi.org/10.1021/acs.iecr.9b00567>
  • Karakashev Stoyan I., Smoukov Stoyan K.: CMC prediction for ionic surfactants in pure water and aqueous salt solutions based solely on tabulated molecular parameters. Journal of Colloid and Interface Science 2017, 501, 142. <https://doi.org/10.1016/j.jcis.2017.04.046>
  • Gupta Monika, Jangra Harish, Bharatam Prasad V., Madan A. K.: Relative eccentric distance sum/product indices for QSAR/QSPR: Development, evaluation and application. ACS Comb. Sci. 2014, 140131154307. <https://doi.org/10.1021/co400088p>
  • Ni Zhong, Lin Xianfu: Insight into substituent effects in Cal-B catalyzed transesterification by combining experimental and theoretical approaches. J Mol Model 2013, 19, 349. <https://doi.org/10.1007/s00894-012-1552-7>
  • Piir G., Sild S., Maran U.: Comparative analysis of local and consensus quantitative structure-activity relationship approaches for the prediction of bioconcentration factor. SAR and QSAR in Environmental Research 2013, 24, 175. <https://doi.org/10.1080/1062936X.2012.762426>
  • Tetko Igor V., Sopasakis Pantelis, Kunwar Prakash, Brandmaier Stefan, Novoratskyi Sergii, Charochkina Larysa, Prokopenko Volodymyr, Peijnenburg Willie J.G.M.: Prioritisation of Polybrominated Diphenyl Ethers (PBDEs) by Using the QSPR-THESAURUS Web Tool. Altern Lab Anim 2013, 41, 127. <https://doi.org/10.1177/026119291304100112>
  • Lee Yugyung, Jana Sourav, Acharya Gayathri, Lee Chi H: Computational analysis and predictive modeling of polymorph descriptors. Chemistry Central Journal 2013, 7. <https://doi.org/10.1186/1752-153X-7-23>
  • Guendouzi Abdelkrim, Mekelleche Sidi Mohamed: Prediction of the melting points of fatty acids from computed molecular descriptors: A quantitative structure–property relationship study. Chemistry and Physics of Lipids 2012, 165, 1. <https://doi.org/10.1016/j.chemphyslip.2011.10.001>
  • Le Tu, Epa V. Chandana, Burden Frank R., Winkler David A.: Quantitative Structure–Property Relationship Modeling of Diverse Materials Properties. Chem. Rev. 2012, 112, 2889. <https://doi.org/10.1021/cr200066h>
  • Weis Derick C., MacFarlane Douglas R.: Computer-Aided Molecular Design of Ionic Liquids: An Overview. Aust. J. Chem. 2012, 65, 1478. <https://doi.org/10.1071/CH12344>
  • Liu Yi, Holder Andrew J.: A quantum mechanical quantitative structure–property relationship study of the melting point of a variety of organosilicons. Journal of Molecular Graphics and Modelling 2011, 31, 57. <https://doi.org/10.1016/j.jmgm.2011.08.003>
  • Tulp Indrek, Dobchev Dimitar A., Katritzky Alan R., Acree William, Maran Uko: A General Treatment of Solubility 4. Description and Analysis of a PCA Model for Ostwald Solubility Coefficients. J. Chem. Inf. Model. 2010, 50, 1275. <https://doi.org/10.1021/ci1000828>
  • Katritzky Alan R., Kuanar Minati, Slavov Svetoslav, Hall C. Dennis, Karelson Mati, Kahn Iiris, Dobchev Dimitar A.: Quantitative Correlation of Physical and Chemical Properties with Chemical Structure: Utility for Prediction. Chem. Rev. 2010, 110, 5714. <https://doi.org/10.1021/cr900238d>
  • Piir G., Sild S., Roncaglioni A., Benfenati E., Maran U.: QSAR model for the prediction of bio-concentration factor using aqueous solubility and descriptors considering various electronic effects. SAR and QSAR in Environmental Research 2010, 21, 711. <https://doi.org/10.1080/1062936X.2010.528596>
  • Hu Jiwei, Zhang Xiaoyi, Wang Zhengwu: A Review on Progress in QSPR Studies for Surfactants. IJMS 2010, 11, 1020. <https://doi.org/10.3390/ijms11031020>
  • Katritzky Alan R., Slavov Svetoslav H., Stoyanova-Slavova Iva S., Kahn Iiris, Karelson Mati: Quantitative Structure–Activity Relationship (QSAR) Modeling of EC50of Aquatic Toxicities forDaphnia magna. Journal of Toxicology and Environmental Health, Part A 2009, 72, 1181. <https://doi.org/10.1080/15287390903091863>
  • Beteringhe Adrian, Radutiu Ana C., Culita Daniela C., Mischie Alice, Spafiu Florica: Quantitative Structure–Retention Relationship (QSRR) Study for Predicting Gas Chromatographic Retention Times for Some Stationary Phases. QSAR Comb. Sci. 2008, 27, 996. <https://doi.org/10.1002/qsar.200730097>
  • Katritzky Alan R., Slavov Svetoslav H., Dobchev Dimitar A., Karelson Mati: QSAR modeling of the antifungal activity against Candida albicans for a diverse set of organic compounds. Bioorganic & Medicinal Chemistry 2008, 16, 7055. <https://doi.org/10.1016/j.bmc.2008.05.014>
  • Zhu Hao, Tropsha Alexander, Fourches Denis, Varnek Alexandre, Papa Ester, Gramatica Paola, Öberg Tomas, Dao Phuong, Cherkasov Artem, Tetko Igor V.: Combinatorial QSAR Modeling of Chemical Toxicants Tested against Tetrahymena pyriformis. J. Chem. Inf. Model. 2008, 48, 766. <https://doi.org/10.1021/ci700443v>
  • Liu K. P., Xia B. B., Zhang X. Y.: Review of QSPR Modeling of Mobilities of Peptides in Capillary Zone Electrophoresis. Journal of Liquid Chromatography & Related Technologies 2008, 31, 1808. <https://doi.org/10.1080/10826070802129001>
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  • Katritzky Alan R., Slavov Svetoslav H., Dobchev Dimitar A., Karelson Mati: QSPR modeling of UV absorption intensities. J Comput Aided Mol Des 2007, 21, 371. <https://doi.org/10.1007/s10822-007-9118-y>
  • Katritzky Alan R., Slavov Svetoslav H., Dobchev Dimitar A., Karelson Mati: Rapid QSPR model development technique for prediction of vapor pressure of organic compounds. Computers & Chemical Engineering 2007, 31, 1123. <https://doi.org/10.1016/j.compchemeng.2006.10.001>
  • Katritzky Alan R., Dobchev Dimitar A., Tulp Indrek, Karelson Mati, Carlson David A.: QSAR study of mosquito repellents using Codessa Pro. Bioorganic & Medicinal Chemistry Letters 2006, 16, 2306. <https://doi.org/10.1016/j.bmcl.2005.11.113>
  • Sun Ning, He Xuezhong, Dong Kun, Zhang Xiangping, Lu Xingmei, He Hongyan, Zhang Suojiang: Prediction of the melting points for two kinds of room temperature ionic liquids. Fluid Phase Equilibria 2006, 246, 137. <https://doi.org/10.1016/j.fluid.2006.05.013>
  • Katritzky Alan R., Dobchev Dimitar A., Fara Dan C., Karelson Mati: QSAR studies on 1-phenylbenzimidazoles as inhibitors of the platelet-derived growth factor. Bioorganic & Medicinal Chemistry 2005, 13, 6598. <https://doi.org/10.1016/j.bmc.2005.06.067>
  • Katritzky Alan R., Fara Dan C.: How Chemical Structure Determines Physical, Chemical, and Technological Properties:  An Overview Illustrating the Potential of Quantitative Structure−Property Relationships for Fuels Science. Energy Fuels 2005, 19, 922. <https://doi.org/10.1021/ef040033q>
  • C. Basak Subhash, Mills Denise, El-Masri Hisham A, Mumtaz Moiz M, Hawkins Douglas M: Predicting blood:air partition coefficients using theoretical molecular descriptors. Environmental Toxicology and Pharmacology 2004, 16, 45. <https://doi.org/10.1016/j.etap.2003.09.002>
  • Trohalaki Steven, Pachter Ruth, Geiss Kevin T., Frazier John M.: Halogenated Aliphatic Toxicity QSARs Employing Metabolite Descriptors. J. Chem. Inf. Comput. Sci. 2004, 44, 1186. <https://doi.org/10.1021/ci0342627>
  • Tämm Kaido, Fara Dan C., Katritzky Alan R., Burk Peeter, Karelson Mati: A Quantitative Structure−Property Relationship Study of Lithium Cation Basicities. J. Phys. Chem. A 2004, 108, 4812. <https://doi.org/10.1021/jp037594n>
  • Mazzatorta Paolo, Vračko Marjan, Jezierska Aneta, Benfenati Emilio: Modeling Toxicity by Using Supervised Kohonen Neural Networks. J. Chem. Inf. Comput. Sci. 2003, 43, 485. <https://doi.org/10.1021/ci0256182>
  • Bosque Ramón, Sales Joaquim: A QSPR Study of O−H Bond Dissociation Energy in Phenols. J. Chem. Inf. Comput. Sci. 2003, 43, 637. <https://doi.org/10.1021/ci025632e>
  • Hiob Rein, Karelson Mati: QSPR models derived for the kinetic data of the gas-phase homolysis of the carbon–methyl bond. Computers & Chemistry 2002, 26, 237. <https://doi.org/10.1016/S0097-8485(01)00112-7>
  • Katritzky Alan R., Jain Ritu, Lomaka Andre, Petrukhin Ruslan, Karelson Mati, Visser Ann E., Rogers Robin D.: Correlation of the Melting Points of Potential Ionic Liquids (Imidazolium Bromides and Benzimidazolium Bromides) Using the CODESSA Program. J. Chem. Inf. Comput. Sci. 2002, 42, 225. <https://doi.org/10.1021/ci0100494>
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  • Fitch William L., McGregor Malcolm, Katritzky Alan R., Lomaka Andre, Petrukhin Ruslan, Karelson Mati: Prediction of Ultraviolet Spectral Absorbance Using Quantitative Structure−Property Relationships. J. Chem. Inf. Comput. Sci. 2002, 42, 830. <https://doi.org/10.1021/ci010116u>
  • Amić D., Basak S.C., Lučić B., Nikolić S., Trinajstić N.: Structure-water solubility modeling of aliphatic alcohols using the weighted path numbers. SAR and QSAR in Environmental Research 2002, 13, 281. <https://doi.org/10.1080/10629360290002776>
  • Katritzky Alan R., Perumal Subbu, Petrukhin Ruslan, Kleinpeter Erich: CODESSA-Based Theoretical QSPR Model for Hydantoin HPLC-RT Lipophilicities. J. Chem. Inf. Comput. Sci. 2001, 41, 569. <https://doi.org/10.1021/ci000099t>
  • Katritzky Alan R., Tatham Douglas B., Maran Uko: Correlation of the Solubilities of Gases and Vapors in Methanol and Ethanol with Their Molecular Structures. J. Chem. Inf. Comput. Sci. 2001, 41, 358. <https://doi.org/10.1021/ci000124v>
  • Bosque Ramon, Sales Joaquim: A QSPR Study of the 31P NMR Chemical Shifts of Phosphines. J. Chem. Inf. Comput. Sci. 2001, 41, 225. <https://doi.org/10.1021/ci000458k>
  • Katritzky Alan R., Tatham Douglas B., Maran Uko: Theoretical Descriptors for the Correlation of Aquatic Toxicity of Environmental Pollutants by Quantitative Structure-Toxicity Relationships. J. Chem. Inf. Comput. Sci. 2001, 41, 1162. <https://doi.org/10.1021/ci010011r>
  • Katritzky Alan R., Perumal Subbu, Petrukhin Ruslan: A QSRR Treatment of Solvent Effects on the Decarboxylation of 6-Nitrobenzisoxazole-3-carboxylates Employing Molecular Descriptors. J. Org. Chem. 2001, 66, 4036. <https://doi.org/10.1021/jo0011843>
  • Katritzky Alan R., Chen Ke, Maran Uko, Carlson David A.: QSPR Correlation and Predictions of GC Retention Indexes for Methyl-Branched Hydrocarbons Produced by Insects. Anal. Chem. 2000, 72, 101. <https://doi.org/10.1021/ac990800w>
  • Hiob Rein, Karelson Mati: Quantitative Relationship between Rate Constants of the Gas-Phase Homolysis of C−X Bonds and Molecular Descriptors. J. Chem. Inf. Comput. Sci. 2000, 40, 1062. <https://doi.org/10.1021/ci0004457>
  • Katritzky Alan R., Maran Uko, Lobanov Victor S., Karelson Mati: Structurally Diverse Quantitative Structure−Property Relationship Correlations of Technologically Relevant Physical Properties. J. Chem. Inf. Comput. Sci. 2000, 40, 1. <https://doi.org/10.1021/ci9903206>