A new computational model for the prediction of toxicity of phosphonate derivatives using QSPR


Structural and electronic properties of a series of 25 phosphonate derivatives were analyzed applying density functional theory, with the exchange-correlation functional PBEPBE in combination with the 6-311++G** basis set for all atoms. The chemical reactivity of these derivatives has been interpreted using quantum descriptors such as frontier molecular orbitals (HOMO, LUMO), Hirshfeld charges, molecular electrostatic potential, and the dual descriptor [\(\Delta f(r)\)]. These descriptors are directly related to experimental median lethal dose (\(\text {LD}_{50})\), expressed as its decimal logarithm [\({A}_{\mathrm{obs}}= \text {log}_{10}\)(\(\text {LD}_{50})\)] through a multiple linear regression equation. The proposed model predicts the toxicity of phosphonates in function of the volume (V), the load of the most electronegative atom of the molecule (q), and the eigenvalue of the molecular orbital HOMO (\({E}_{\mathrm{HOMO}})\). The obtained values in the internal validation of the model are: \({R}^{2}= 82.71\)%, \({R}^{2}_{\mathrm{ADJ}} = 80.24\)%, \(F= 33.5\), \(\delta {K}=0.169\), \(\delta {Q}=0.011\), \({R}^{\mathrm{P}}=0.423\), \({R}^{\mathrm{N}} = -\,0.025\,(-\,0.311)\), and \({Q}^{2}_{\mathrm{boot}} = 75.45\)%. The toxicity of nine phosphonate derivatives used as test molecules was adequately predicted by the model. The theoretical results indicate that the oxygen atom of the O=P group plays an important role in the interaction mechanism between the phosphonate and the acetylcholinesterase enzyme, inhibiting the removal of the proton of the ser-200 residue by the his-440 residue.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6


  1. 1.

    Boeing IA, Crutchfield MM, Heitsch CW (2005) Phosphorus compounds (Phosphines and Phosphine Derivates). Encycl Chem Technol Kirk-Othmer. 5th ed.; 17. ISBN: 978-0-471-48506-3

  2. 2.

    Guest D, Grant B (1991) The complex action of phosphonates as antifungal agents. Biol Rev 66:159–187. https://doi.org/10.1071/APP9900113

    Article  Google Scholar 

  3. 3.

    Davis AJ, Say M, Snow AJ, Grant BR (1994) Sensitivity of \(Fusarium oxysporum \)f sp. cubense to phosphonate. Plant Pathol 43:200–205. https://doi.org/10.1111/j.1365-3059.1994.tb00571.x

    Article  CAS  Google Scholar 

  4. 4.

    Martin H, Grant BR, Stehmann C (1998) Inhibition of inorganic pyrophosphatase by phosphonate a site of action in phytophthora spp.? Pestic Biochem Physiol 61:65–77. https://doi.org/10.1006/pest.1998.2353

    Article  CAS  Google Scholar 

  5. 5.

    De Clercq E (2003) Clinical potential of the acyclic nucleoside phosphonates cidofovir, adefovir and tenofovir in treatment of DNA virus and retrovirus infections. Clin Microbiol Rev 16:569–596. https://doi.org/10.1128/CMR.16.4.569-596.2003

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  6. 6.

    Human Enviromental Risk Assessment on ingredients of European household cleaning products (HERA). http://www.heraproject.com/files/30-f-04-hera phosphonates full web wd.pdf. Retrieved 20 July 2017

  7. 7.

    Ternan NG, Mc Grath JW, Mc Mullan G, Quinn JP (1998) Review: organophosphonates: occurrence, synthesis and biodegradation by microorganisms. World J Microbiol Biotechnol 14:635–647. https://doi.org/10.1023/A:1008848401799

    Article  CAS  Google Scholar 

  8. 8.

    Kwiatkowska M, Huras B, Bukowska B (2014) The effect of metabolites and impurities of glyphosate on human erythrocytes (in vitro). Pest Biochem Physiol 109:34–43. https://doi.org/10.1016/j.pestbp.2014.01.003

    Article  CAS  Google Scholar 

  9. 9.

    Mesnage R, Defarge N, De Vendomois JS, Seralini GE (2015) Potential toxic effects of glyphosate and its commercial formulations below regulatory limits. Food Chem Toxicol 84:133–153. https://doi.org/10.1016/j.fct.2015.08.012

    Article  PubMed  CAS  Google Scholar 

  10. 10.

    Schultz TW, Cronin MTD, Walker JD, Aptula AO (2003) Quantitative structure-activity relationships (QSARs) in toxicology: a historical perspective. Theochem 622:1–22. https://doi.org/10.1016/S0166-1280(02)00614-0

    Article  CAS  Google Scholar 

  11. 11.

    Freidig AP, Dekkers S, Verwei M, Zvinavashe E, Bessems JGM, Van de Sandt JJM (2001) Development of a QSAR for worst case estimates of acute toxicity of chemically reactive compounds. Toxicol Lett 170:214–222. https://doi.org/10.1016/j.toxlet.2007.03.008

    Article  CAS  Google Scholar 

  12. 12.

    Koteswara RV, Hu G, Chaney MO, Yan SS (2013) Structure based design and synthesis of benzothiazole phosphonate analogues with inhibitors of human ABAD-A\(\beta \) for treatment of Alzheimers disease. Chem Biol Drug Des 81:238–249. https://doi.org/10.1111/cbdd.12068

    Article  CAS  Google Scholar 

  13. 13.

    Hurley MM, Balboa A, Lushington GH, Guo J (2005) Interactions of organophosphorus and related compounds. Chem Biol Interact 157–158:1321–325. https://doi.org/10.1016/j.cbi.2005.10.096

    CAS  Article  Google Scholar 

  14. 14.

    Singh S, Gupta R, Kumari M, Sharma S (2015) Nontarget effects of chemical pesticides and biological pesticide on rizhospheric microbial community structure and function in Vignia radiate. Environ Sci Pollut Res 22:11290–11300. https://doi.org/10.1007/s11356-015-4341-x

    Article  CAS  Google Scholar 

  15. 15.

    Bermúdez JMS, Cronin TD (2006) Quantitative structure activity relationships for the toxicity of organophosphorus and carbamate pesticides to the rainbow trout onchorhyncus mykiss. Pest Manag Sci 62:819–83. https://doi.org/10.1016/S0166-1280(02)00614-0

    Article  Google Scholar 

  16. 16.

    Bencsura A, Enyedi IY, Kovach IM (1996) Probing the active site of acetylcholinesterase by molecular dynamics of tis phosphonate ester adducts. J Am Chem Soc 118:8531–8541. https://doi.org/10.1021/ja952406v

    Article  CAS  Google Scholar 

  17. 17.

    Kovarik Z, Radic Z, Berman HA, Simeon-Rudolf V, Reiner E, Taylor P (2003) Acetylcholinesterase active centre and gorge conformations analyzed by combinatorial mutations and enantiomeric phosphonates. Biochem J 373:33–40. https://doi.org/10.1042/BJ20021862

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  18. 18.

    Colovi MB, Krstic DZ, Lazarevic-Pasti TD, Bondzic AM, Vasic VM (2013) Acetylcholinesterase Inhibitors: pharmacology and toxicology. Curr Neuropharmacol 11:315–335. https://doi.org/10.2174/1570159X11311030006

    Article  Google Scholar 

  19. 19.

    Organisation for Economic Co-operation and Development (OECD). http://www.oecd.org/chemicalsafety/testing/oecdguidelinesforthetestingofchemicals.htm. Retrieved 26 Jan 2018

  20. 20.

    Prieto P, Cole T, Curren R, Gibson RM, Liebsch M, Raabe H, Toumainen AM, Whelan M, Kinsner-Ovaskainen A (2013) Assessment of the predictive capacity of the 3T3 neutral red uptake cytotoxicity test method to identify substances not classified for acute oral toxicity (LD50\(>\) 2000 mg/kg): Results of an ECVAM validation study. Regul Toxicol Pharmacol 65:344–365. https://doi.org/10.1016/j.yrtph.2012.11.013

    Article  PubMed  CAS  Google Scholar 

  21. 21.

    Andersson CD, Hillgren JM, Lindgren C, Qian W, Akfur C, Berg L, Ekström F, Linusson A (2015) Benefits of statistical molecular design, covariance analysis, and reference models in QSAR: a case study. J Comput Aided Mol Des 29:199–215. https://doi.org/10.1007/s10822-014-9808-1

    Article  PubMed  CAS  Google Scholar 

  22. 22.

    Petrescu AM, Putz MV, Ilia G (2015) Quantitative structure-activity/ecotoxicity relationships (QSAR/QEcoSAR) of a series of phosphonates. Environ Toxicol Pharmacol 40:800–824. https://doi.org/10.1016/j.etap.2015.08.032

    Article  PubMed  CAS  Google Scholar 

  23. 23.

    Camacho RL, Gutiérrez E, Guzmán E, Aquino E, Cruz J, Rodríguez JGA, Olvera O, Pandiyan T, Medina JL (2015) Density functional theory and electrochemical studies: structure–efficiency relationship on corrosion inhibition. J Chem Inf Model 55:2391–2402. https://doi.org/10.1021/acs.jcim.5b00385

    Article  CAS  Google Scholar 

  24. 24.

    National Center for Biotechnology Information (NCBI)[Internet]. Bethesda (MD): National Library of Medicine (US), National Center for Biotechnology Information; [1988]—[cited Apr 06, 2017]. https://www.ncbi.nlm.nih.gov

  25. 25.

    TOXNET Data Base. https://toxnet.nlm.nih.gov/newtoxnet/hsdb.htm. Retrieved 15 June 2017

  26. 26.

    CHEMSPIDER (2013). http://www.chemspider.com. Accessed 15 Jan 2017

  27. 27.

    Elstner M, Porezag D, Jungnickel G, Elsner J, Haugk M, Frauenheim T, Suhai S, Seifert G (1998) Self-consistent-charge density-functional tight-binding method for simulations of complex materials properties. Phys Rev B 58:7260. https://doi.org/10.1103/PhysRevB.58.7260

    Article  CAS  Google Scholar 

  28. 28.

    Perdew JP, Burke K, Ernzerhof M (1996) Generalized gradient approximation made simple. Phys Rev Lett 77:3865–3868. https://doi.org/10.1103/PhysRevLett.77.3865

    Article  PubMed  CAS  Google Scholar 

  29. 29.

    Perdew JP, Burke K, Ernzerhof M (1997) Generalized gradient approximation made simple (Erratum). Phys Rev Lett 78:1396. https://doi.org/10.1103/PhysRevLett.78.1396

    Article  CAS  Google Scholar 

  30. 30.

    Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, Cheeseman JR, Scalmani G, Barone V, Mennucci B, Petersson GA, Nakatsuji H, Caricato M, Li X, Hratchian HP, Izmaylov AF, Bloino J, Zheng G, Sonnenberg JL, Hada M, Ehara M, Toyota K, Fukuda R, Hasegawa J, Ishida M, Nakajima T, Honda Y, Kitao O, Nakai H, Vreven T, Montgomery JA Jr, Peralta JE, Ogliaro F, Bearpark M, Heyd JJ, Brothers E, Kudin KN, Staroverov VN, Kobayashi R, Normand J, Raghavachari K, Rendell A, Burant JC, Iyengar SS, Tomasi J, Cossi M, Rega N, Millam NJ, Klene M, Knox JE, Cross JB, Bakken V, Adamo C, Jaramillo J, Gomperts R, Stratmann RE, Yazyev O, Austin AJ, Cammi R, Pomelli C, Ochterski JW, Martin RL, Morokuma K, Zakrzewski VG, Voth GA, Salvador P, Dannenberg JJ, Dapprich S, Daniels AD, Farkas O, Foresman JB, Ortiz JV, Cioslowski J, Fox DJ (2009) Gaussian 09, revision A.02. Gaussian, Wallingford, CT

  31. 31.

    Jardínez C, Vela A, Cruz J, Alvarez RJ, Alvarado JG (2016) Reduced density gradient as a novel approach for estimating QSAR descriptors, and its application to 1,4-dihydropyridine derivatives with potential antihypertensive. J Mol Model 22:296. https://doi.org/10.1007/s00894-016-3159-x

    Article  PubMed  CAS  Google Scholar 

  32. 32.

    Ramamoorthy H, Abraham P, Isaac B, Selvakumar D (2017) Role for NF-kB inflammatory signaling pathway in tenofovir disoproxil fumarate (TDF) induced renal damage in rats. Food Chem Toxicol 99:103–118. https://doi.org/10.1016/j.fct.2016.11.29

    Article  PubMed  CAS  Google Scholar 

  33. 33.

    Cortez A, Li Y, Miller AT, Zhang X, Yue K, Maginnis J, Hampton J, Hall DS, Shapiro M, Nayak B, D’Oro U, Li Ch, Skibinski D, Mbow ML, Singh M, O’Hagan DT, Cooke MP, Valiante NM, Wu TYH (2016) Incorporation of phosphonate into benzonaphthyridine toll-like receptor 7 agonists for adsorption to aluminum hydroxide. J Med Chem 59:5868–5878. https://doi.org/10.1021/acs.jmedchem.6b00489

    Article  PubMed  CAS  Google Scholar 

  34. 34.

    Scneider C, bierwisch A, Koller M, Worek F, Kubik S (2016) Detoxification of VX and other V-type nerve agents in water at 37 \(^{\circ }\)C and pH 7.4 by substituted sulfonatocaxil [4] arenes. Angew Chem Int Ed 55:12668–12672. https://doi.org/10.1002/anie.201606881

    Article  CAS  Google Scholar 

  35. 35.

    Szabo A, Ostlund NS (1989) Chapter 3. The Hartree Fock approximation. Modern quantum chemistry: introduction to advanced electronic structure theory. Dover Books on Chemistry/Dover Publications, Mineola, NY. ISBN: 0-486-69186-1

  36. 36.

    Parr RG, Donnelly RA, Levy M, Palke WE (1978) Electronegativity-the density functional viewpoint. J Chem Phys 68:3801–3807. https://doi.org/10.1063/1.436185

    Article  CAS  Google Scholar 

  37. 37.

    Pearson RG (1988) Absolute electronegativity and hardness: application to inorganic chemistry. Inorg Chem 27:734–740. https://doi.org/10.1021/ic00277a030

    Article  CAS  Google Scholar 

  38. 38.

    Pearson RG (1994) Principle of maximum physical hardness. J Phys Chem 98:1989–1992. https://doi.org/10.1002/qua.560560404

    Article  CAS  Google Scholar 

  39. 39.

    Gázquez JL, Cedillo A, Vela A (2007) Electrodonating and electroaccepting powers. J Phys Chem A 111:1966–1970. https://doi.org/10.1021/jp065459f

    Article  PubMed  CAS  Google Scholar 

  40. 40.

    Morell C, Grand A, Toro-Labbé A (2005) New dual descriptor for chemical reactivity. J Phys Chem A 109:205–212. https://doi.org/10.1021/jp046577a

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  41. 41.

    Talete srl (2010) Dragon 06. Todeschini R, Consonni V, Wiley-VCH, Weinheim, Germany, in the Series ’Methods and Principles in Medicinal Chemistry’ edited by R. Mannhojd, H. Kubinyi, and H. Timmerman. Copyright\(\copyright \) 2010, Talete srl, Milano, Italy

  42. 42.

    Hansch C, Maloney PP, Fujita T, Muir RM (1962) Correlation of biological activity of phenoxyacetic acids with Hammett substituent constants and partition coefficients. Nature 194:178–180. https://doi.org/10.1038/194178b0

    Article  CAS  Google Scholar 

  43. 43.

    Mobydigs (2004) Todeschini R, Ballabio D, Consionni V, Mauri A, Pavan M, Milano Chemometics and QSAR Research Group. Copyright, 2004, Talete srl, Milano, Italy

  44. 44.

    Tschinki M, Bachman RE, Gabbal FP (2000) Coordination of dimethyl methylphosphonate to the bidentate Lewis acid 1,2-bis(chloromercurio)tetrafluorobenzene. Organometallics 19:2633–2636. https://doi.org/10.1021/om990987h

    Article  CAS  Google Scholar 

  45. 45.

    Daly SM, Grassi M, Shenoy DK, Ugozzoli F, Dalcanale J (2007) Supramolecular surface plasmon resonance (SPR) sensors for organophosphorus vapor detection. J Mater Chem 17:1809–1818. https://doi.org/10.1039/B615516B

    Article  CAS  Google Scholar 

  46. 46.

    Lu T, Manzeti S (2014) Wavefunction and reactivity study of benzo[a]pyrene diol epoxide and its enantiomeric forms. Struct Chem 25:1521–1533. https://doi.org/10.1007/s11224-014-0430-6

    Article  CAS  Google Scholar 

  47. 47.

    Desiraju GR, Stciner T (2001) The weak hydrogen bond in structural chemistry and biology. Oxford Science Publications, Oxford

    Book  Google Scholar 

  48. 48.

    Multiwfn (2017) Lu T (2017) A multifunctional wave function analyzer, Version 3.4.1(dev). http://sobereva.com/multiwfn

  49. 49.

    Bader RFW (1990) Atoms in molecules: A quantum theory. Oxford Uni. Press, Oxford

    Google Scholar 

  50. 50.

    Popelier PLA, Bader RFW (1992) The existence of an intramolecular C–H...O hydrogen bond in creatine and carbomyl sarcosine. Chem Phys Lett 189:542–548. https://doi.org/10.1016/0009-2614(92)85247-8

    Article  CAS  Google Scholar 

  51. 51.

    Espinosa E, Molins E, Lecomte C (1998) Hydrogen bond strengths revealed by topological analyses of experimentally observed electron densities. Chem Phys Lett 285:170–173. https://doi.org/10.1016/S0009-2614(98)00036-0

    Article  CAS  Google Scholar 

  52. 52.

    Todeschini R, Consonni V, Mauri A, Pavan M (2004) Detecting “bad” regression models: multicriteria fitness functions in regression analysis. Anal Chim Acta 515:199–208. https://doi.org/10.1016/j.aca.2003.12.010

    Article  CAS  Google Scholar 

  53. 53.

    Consonni V, Ballabio D, Todeschini R (2009) Comments on the definition of the Q2 parameter for QSAR validation. J Chem Inf Model 49:1669–1678. https://doi.org/10.1021/ci900115y

    Article  PubMed  CAS  Google Scholar 

  54. 54.

    Consonni V, Ballabio D, Todeschini D (2010) Evaluation of model predictive ability by external validation techniques. J Chemometrics 24:194–201. https://doi.org/10.1002/cem.1290

    Article  CAS  Google Scholar 

  55. 55.

    Tropsha A, Gramatica P, Gombar VK (2003) The importance of being earnest: validation is the absolute essential for successful application and interpretation of QSPR models. QSAR Comb Sci 22:69–77. https://doi.org/10.1002/qsar.200390007

    Article  CAS  Google Scholar 

  56. 56.

    Golbraikh A, Tropsha A (2002) Beware of q2!. J Mol Gr Model 20:269–276. https://doi.org/10.1016/S1093-3263(01)00123-1

    Article  CAS  Google Scholar 

Download references


We gratefully acknowledge the Dirección General de Cómputo y Tecnologías de Información y Comunicación (DGCTIC) at the Universidad Nacional Autónoma de México, and we also acknowledge Programa Annual Universitario (PAI 3312) for financial support.

Author information



Corresponding author

Correspondence to Julián Cruz-Borbolla.

Ethics declarations

Conflict of interest

The authors declared that they have no conflict of interest.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supporting Information Available:

The molecular structure, plotted the ESP, Δf, Quantum descriptors and Correlation matrix with all descriptors. This material is available free of charge via the Internet at http:// (docx 11.8 MB)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Camacho-Mendoza, R.L., Aquino-Torres, E., Cordero-Pensado, V. et al. A new computational model for the prediction of toxicity of phosphonate derivatives using QSPR. Mol Divers 22, 269–280 (2018). https://doi.org/10.1007/s11030-018-9819-2

Download citation


  • Toxicity
  • DFT
  • Phosphonates
  • QSPR
  • QSAR
  • \(\hbox {LD}_{50}\)
  • Quantum chemical descriptor
  • Acetylcholinesterase