Physics and Materials Chemistry
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Physics and Materials Chemistry. 2021, 7(1), 1-13
DOI: 10.12691/pmc-7-1-1
Open AccessArticle

Predictive Modeling of Toxoplasma Gondii Activity of a Series of Substituted Imidazole-Thiosemicarbazides Using Quantum Descriptors

Sopi Thomas Affi1, 2, Bafétigué Ouattara3, Georges Stéphane Dembélé1, 2, Mamadou Guy-Richard Koné1, 2, and Nahossé Ziao1, 2

1Laboratoire de Thermodynamique et de Physico-Chimie du Milieu, UFR SFA, Université NANGUI ABROGOUA, 02 BP 801 Abidjan 02, Côte-d’Ivoire

2Groupe Ivoirien de Recherches en Modélisation des Maladies (GIR2M)

3Laboratoire de Physique Fondamentale et Appliquée, UFR SFA, Université NANGUI ABROGOUA, 02 BP 801 Abidjan 02, Côte-d’Ivoire

Pub. Date: December 12, 2021

Cite this paper:
Sopi Thomas Affi, Bafétigué Ouattara, Georges Stéphane Dembélé, Mamadou Guy-Richard Koné and Nahossé Ziao. Predictive Modeling of Toxoplasma Gondii Activity of a Series of Substituted Imidazole-Thiosemicarbazides Using Quantum Descriptors. Physics and Materials Chemistry. 2021; 7(1):1-13. doi: 10.12691/pmc-7-1-1

Abstract

Quantitative Structure Activity Relationship (QSAR) study of Toxoplasma gondii was done on a series of twenty-five (25) imidazole-thiosemicarbazide molecules. In order to obtain molecular descriptors all these molecules were optimized at B3LYP/LanL2DZ level. This study was performed using the linear multiple regression (MLR), nonlinear regression (MNLR) and artificial neural network (ANN) methods. These statistical methods allow to find three (3) quantitative models. Quantum descriptors which such as energy gap (ΔE), dipole moment (μ), enthalpy of formation (ΔfH), bond length (D(C-S)) and lipophilicity (Logp) were used in models elaboration. Among obtained models, RNA model has much better predictive ability than other models with R2 = 0.9291 and RMCE = 0.00023. A decrease in energy gap (ΔE) which is the main descriptor could significantly improve the Toxoplasma gondii IC50 inhibitory concentration of substituted imidazole-thiosemicarbazide analogues. Furthermore, the external validation test pIC50 theo/ pIC50 exp and the applicability domain from Cook's distance were verified.

Keywords:
QSAR RNA Energy gap (ΔE) Toxoplasma gondii activity

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References:

[1]  J. MCAULEY, K. M. BOYER, D. PATEL, M. METS, C. SWISHER, N. ROIZEN, C. WOLTERS, L. STEIN, M. STEIN et W. SCHEY, “Early and longitudinal evaluations of treated infants and children and untreated historical patients with congenital toxoplasmosis: The Chicago Collaborative Treatment Trial,” Clinical Infectious Diseases , vol. 19, p. 38-72, 1994.
 
[2]  F. DAFFOS, V. MIRLESSE, P. HOHLFELD, F. JACQUEMARD, P. THULLIEZ et F. FORESTIER, “Toxoplasmosis pregnancy.,” Lancet , vol. 344, p. 541, 1994.
 
[3]  U. Tendeur, A. Heckeroth et L. Weiss, “Toxoplasma gondii: des animaux aux humains.,” Int. J. Parasitol., vol. 30, pp. 1217-1258, 2000.
 
[4]  P. Agata, W. Lidia, B. Adrian, S. Edyta, W. Monika, T. Nazar, H. Anna, H. Miroslaw et D. Katarzyna, “Discovery of Potent and Selective Halogen-Substituted Imidazole-Thiosemicarbazides for Inhibition of Toxoplasma gondii Growth In Vitro via Structure-Based Design,” Molecules, vol. 24, p. 1618, 2019.
 
[5]  A. Paneth, L. Węglińska, A. Bekier, E. Stefaniszyn, M. Wujec, N. Trotsko, A. Hawrył, M. Hawrył et K. Dzitko, “Discovery of Potent and Selective Halogen-Substituted Imidazole-Thiosemicarbazides for Inhibition of Toxoplasma gondii Growth In Vitro via Structure,” Molecules, vol. 24, pp. 1-14, 2019.
 
[6]  W. R. Sherman, “5-Nitro-2-furyl-substituted 1,3,4-Oxadiazoles, 1,3,4-Thiazoles, and 1,3,5-Triazines,” The Journal of Organic Chemistry, vol. 1, pp. 88-95, 1961.
 
[7]  A. Jalilian, S. Sattari, M. Bineshmarvasti, A. Shafiee et M. A. Daneshtalab, Pharm. Med. Chem. , vol. 333, p. 347, 2000.
 
[8]  C. B. Chapleo, P. L. Myers, A. C. B. Smith, M. R. Stillings, I. F. Tulloch et D. S. Walter, “Substituted 1,3,4-thiadiazoles with anticonvulsant activity. 4.Amidines,” Journal of medicinal chemistry , vol. 1, n° %131, pp. 7-11, 1988.
 
[9]  E. F. Da Silva, M. M. Canto-Cavalheiro, V. R. Braz, L. Cysne-Finkelstein et L. L. Leon, “Synthesis, and biological evaluation of new 1,3,4-thiadiazolium-2-phenylamine derivates against Leishmania amazonensis promastigotes and amastigotes,” European Journal of medicinal chemistry, vol. 12, n° %137, pp. 979-984, 2002.
 
[10]  N. Grynberg, A. Santos et A. Echevarria, “Synthesis and in vivo antitumor activity of new heterocyclic derivatives of the 1,3,4-thiadiazolium-2-aminide class,” Anti-cancer drugs, vol. 8, n° %11, pp. 88-91, 1997.
 
[11]  T. I. Oprea, “Chemoinformatics in Drug Discovery,” Ed. WILEY-VCH Verlag., 2005.
 
[12]  E. A. Rekka et P. N. Kourounakis, “Chemistry and Molecular Aspects of Drug Design and Action,” Ed. Taylor & Francis Group, 2008.
 
[13]  S. M. Free et J. W. Wilson, “A Mathematical Contribution to Structure-Activity Studies,” J. Med. Chem., vol. 7, pp. 395-399, 1964.
 
[14]  C. Hansch et T. Fujita, “ρ – σ – π, analysis: method for correlation of biological activity and chemical structure,” J. Am. Chem. Soc., vol. 86, pp. 1616-1626, 1964.
 
[15]  T. Partal et H. K. Cigizoglu, “Estimation and forecasting of daily suspended sediment data using wavelet-neural networks,” Journal of Hydrology, vol. 358 , n° %134, pp. 317-331, 2008.
 
[16]  K. Hornik, M. Stinchcombe et H. White, “Multilayer feed-forward networks are universal approximators,” Neural Networks computation, vol. 2, pp. 359-366, 1989.
 
[17]  C. Roussillon, “Prévision de la température par les Réseaux de Neurones Artificiels,” Université Victor Hugo Besancon, France, 2004.
 
[18]  JMPPro13, Statistical Discovery, Scintilla: SAS institute Inc., 1998-2014.
 
[19]  X. V. 2. C. Addinsoft, XLSTAT and Addinsoft are Registered Trademarks of Addinsoft., 2014, pp. 1995-2014 .
 
[20]  M. Excel, 2016.
 
[21]  M. J. Frisch, G. W. Trucks, H. B. Schlegel et G. E. Scuseria, “Gaussian 09, Revision A.02,” Gaussian, Inc., Wallingford CT, 2009.
 
[22]  P. K. Chattaraj, A. Cedillo et R. G. Parr, J. Phys. Chem., vol. 103, p. 7645, 1991.
 
[23]  P. W. Ayers et R. G. Parr, J. Am Chem. Soc, vol. 122, p. 2000, 2010.
 
[24]  F. De Proft, J. M. L. Martin, P. Geerlings et :. :, Chem. Phys Let., vol. 250, p. 393, 1996.
 
[25]  C. Hansch, P. G. Sammes et J. B. Taylor, “in:Comprehensive Medicinal Chemistry,” Computers and the medicinal chemist, vol. 4, pp. 33-58, 1990.
 
[26]  R. Franke, “Theoretical Drug Design Methods,” Elsevier, 1984.
 
[27]  G. W. Snedecor et W. G. Cochran, “Methods, Statistical,” Oxford and IBH: New Delhi, India, p. 381, 1967.
 
[28]  N. J.-B. Kangah, M. G.-R. Koné, C. G. Kodjo, B. R. N’guessan, A. L. C. Kablan, S. A. Yéo et N. Ziao, “Antibacterial Activity of Schiff Bases Derived from Ortho Diaminocyclohexane, Meta-Phenylenediamine and 1,6-Diaminohexane: Qsar Study with Quantum Descriptors,,” International Journal of Pharmaceutical Science Invention, vol. 6, n° %13, pp. 38-43, 2017.
 
[29]  E. X. Esposito, A. J. Hopfinger et J. D. Madura, “Methods for Applying the Quantitative Structure-Activity Relationship Paradigm,,” Methods in Molecular Biology, vol. 275, pp. 131-213., 2004.
 
[30]  M. Frisch, G. Trucks, H. Schlegel et G. Scuseria, “Revision A.02,” chez Gaussian 09, Wallingford CT, Gaussian, Inc., 2009.
 
[31]  M. W. Chase, C. A. Davies, J. R. Downey, D. J. Frurip, R. A. McDonald et A. N. Syverud, “JANAF Thermochemical Tables,” J. Phys. Ref. , vol. 14, n° %11, 1985.
 
[32]  S. Chaltterjee, A. Hadi et B. Price, “Regression Analysis by Examples,” Wiley VCH: New York, 2000.
 
[33]  H. Phuong, “Synthèse et étude des relations structure/activité quantitatives (QSAR/2D) d’analoguesBenzo[c]phénanthridiniques,” France, 2007.
 
[34]  A. Vessereau, Méthodes statistiques en biologie et en agronomie, vol. 538, Paris: Lavoisier (Tec & Doc)., 1988.
 
[35]  J. N’dri, M.-G. Koné, C. KODJO, S. AFFI, A. KABLAN, O. OUATTARA et D. Soro, “Quantitative Activity Structure Relationship (QSAR) of a Series of Azet idinones Derived from Dap-sone by the Method of Density Functional Theory (DFT),” IRA International Journal of Applied Sciences (ISSN 2455-4499), vol. 8, n° %12, pp. 55-62, 2017.
 
[36]  K. R. Clarke et M. Ainsworth, “A method of linking multivariate community structure to environmental variables.,” Marine Ecology, vol. 92, pp. 205-219, 1993.
 
[37]  B. Escofier et J. Pagès, Analyses factorielles simples et multiples: Objectifs, méthodes et interprétation., vol. 318, Paris: Dunod, 2008.
 
[38]  T. Oprea, Chemoinformatics in drug discovery, Allemagne: Ed. Wiley-VCH Verlag, 2005.
 
[39]  E. Rekka et P. Kourounakis, Chemistry and molecular aspects of drug design and action, Etats Unies: LLC. Ed. Taylor & Francis Group, 2008.
 
[40]  L. Eriksson, J. Jaworska, A. Worth, M. D. Cronin, R. M. Mc Dowell et P. Gramatica, “Methods for Reliability and Uncertainty Assessment and for Applicability Evaluations of Classification- and Regression-Based QSARs,” Environmental Health Perspectives, vol. 111, n° %110, pp. 1361-1375, 2003.
 
[41]  G. Dreyfus, “ Réseaux de neurones artificiels,” Toulouse, France., 1998.
 
[42]  G. Dreyfus, J. Martinez, M. Samuelides, M. Gordon, F. Badran, S. Thiria et L. Herault, Réseaux de Neurones Artificiels. 2 édition, New York, USA: Groupe Eyrolles, 2002, p. 374 .
 
[43]  I. Rivals, “Modélisation et commande de processus par réseaux de neurones artificiels. Application au pilotage d’un véhicule autonome.,” France, 1995.
 
[44]  J. M. Poveda, A. Garcia, P. J. Martin-Alvarez et L. Cabezas, “Application of partial least squares (PLS) regression to predict the ripening time of Manchego cheese,” Food Chemistry, vol. 84, n° %11, pp. 29-33, 2004.
 
[45]  C. Faur-Brasquet et P. Le Cloirec, “Modelling of the flow behaviour of activated carbon cloths using a neural network approach,” Chemical Engineering and Processing, vol. 2 , n° %142, pp. 645-652, 2003.
 
[46]  V. Labet, “Etude Théorique de Quelques Aspects de la Réactivité des Bases de l'ADN-Définition de nouveaux outils théoriques d'étude de la réactivité chimique. Chemical Sciences.,” 2009.
 
[47]  B. Samir, “Etude théorique et expérimentale des réactions de cycloaddition Diels&Alder et 1,3- dipolaire,” 2013.
 
[48]  O. Dorosh et Z. Kisiel, “Electric Dipole Moments of Acetone and of Acetic Acid measured in Supersonic Expansion,” Acta Physica Polonica A, vol. 112 , 2007.
 
[49]  E. Rutkowska, K. Pajak et K. Jozwiak, “Lipophilicity - Methods of Determination and its Role in Medicinal Chemistry,” Acta Poloniae Pharmaceutica - Drug Research, vol. 70, n° %11, pp. 3-18, 2013.
 
[50]  A. Cozma, V. Zaharia, A. Ignat, S. Gocan et N. Grinberg, “Prediction of the Lipophilicity of Nine New Synthesized Selenazoly and Three Aroyl–Hydrazinoselenazoles Derivatives by Reversed-Phase High Performance Thin-Layer Chromatography,” Journal of Chromatographic Science , vol. 50, n° %1157, p. 161, 2012.
 
[51]  R. Mannhold, G. I. Poda, C. Ostermann et I. V. Tetko, “Calculation of Molecular Lipophilicity: State-of-the-Art and Comparison of LogP Methods on More Than 96,000 Compounds,” Journal of Pharmaceutical Sciences, vol. 98, n° %13, pp. 861-893, 2009.
 
[52]  M. A. Bakht, M. F. Alajmi, P. Alam, A. Alam, P. Alam et T. M. Aljarba, “Theoretical and experimental study on lipophilicity and wound healing activity of ginger compounds,” Asian Pacific Journal of Tropical Biomedicine , vol. 4 , n° %14, pp. 329-333, 2014.
 
[53]  J. Kujawski, H. Popielarska, A. Myka, B. Drabińska et M. K. Bernard, “The logP Parameter as a Molecular Descriptor in the Computer-aided Drug Design - an Overview,” Computational Methods In Science And Technology, vol. 18 , n° %12, pp. 81-88, 2012.
 
[54]  G. Hea, L. Fenga et H. Chena, “International Symposium on Safety Science and Engineering in China,” Proc. Engin, vol. 43, pp. 204-209, 2012 .
 
[55]  K. Roy et e. al, “A Primer on QSAR/QSPR Modeling Chapter 2 Statistical Methods in QSAR/QSPR,,” Springer Briefs in Molecular Science, pp. 37-59, 2015.
 
[56]  F. Sahigara, K. Mansouri, D. Ballabio, A. Mauri et V. C. a. R. Todeschini, “Comparison of Different Approaches to Define the Applicability Domain of QSAR Models,” Molecules, vol. 17, pp. 4791-4810, 2012.
 
[57]  Rakotomalala et Ricco, Pratique de la Régression Linéaire Multiple Diagnostic et sélection de variables,Version 2.1.
 
[58]  N. A. Joseph, “Contribution à l’étude de l’activité biologique de composes dérivés du nitrobenzène: étude par diffraction des rayons X – modélisation,” 2014.
 
[59]  N. N.-Jeliazkova et J. Jaworska, “ An Approach to Determining Applicability Domains for QSAR Group Contribution Models: An Analysis of SRC KOWWIN,” ATLA 33, p. 461-470, 2005.
 
[60]  acdlabs, Advanced Chemistry Development/ Chemskecht, 1994-2010.