Abstract
Aim:
To develop an artificial neural network model for predicting the resistance index (RI) of taxoids.
Methods:
A dataset of 63 experimental data points were compiled from published studies and randomly subdivided into training and external test sets. Electrotopological state (E-state) indices were calculated to characterize molecular structure together with a principle component analysis to reduce the variable space and analyze the relative importance of E-state indices. Back propagation neural network technique was used to build the models. Five-fold cross-validation was performed and 5 models with different compound composition in training and validation sets were built. The independent external test set was used to evaluate the predictive ability of models.
Results:
The final model proved to be good with the cross-validation Q2cv0.62, external testing R2 0.84, and the slope of the regression line through the origin for the testing set at 0.9933.
Conclusion:
The quantitative structure-activity relationship model can predict the RI to a relative nicety, which will aid in the development of new anti-multidrug resistance taxoids.
Similar content being viewed by others
Article PDF
References
Wani MC, Taylor HL, Wall ME, Coggon P, McPhail AT . Plant antitumor agents. VI. Isolation and structure of taxol, a novel antileukemic and antitumor agent from Taxus brevifolia. J Am Chem Soc 1971; 93: 2325–7.
Gueritte-Voegelein F, Guenard D, Mangatal L, Potier P, Guilhem J, Cesario M, et al. Structure of a synthetic taxol precursor: Ntert-butoxycarbonyl-10–deacetyl-N-debenzoyltaxol. Acta Crystallogr C 1990; 46: 781–4.
Kingston DGI . Recent advances in the chemistry of taxol. J Nat Prod 2000; 63: 726–34.
Miller ML, Ojima I . Chemistry and chemical biology of taxane anticancer agents. Chem Rec 2001; 1: 195–211.
Kingston DGI, Newman DJ . Taxoids: cancer-fighting compounds from nature. Curr Opin Drug Discov Devel 2007; 10: 130–44.
Edwards P . Peptoid positional scanning libraries for identification of multidrug resistance reversal agents. Drug Discov Today 2006; 11: 669–70.
Burchenal JH, Holmberg EA . The utility of resistant leukaemias in screening for chemotherapeutic activity. Ann N Y Acad Sci 1958; 76: 826–9.
Leslie EM, Deeley RG, Cole SPC . Multidrug resistance proteins: role of P-glycoprotein, MRP1, MRP2, and BCRP (ABCG2) in tissue defense. Toxicol Appl Pharmacol 2005; 204: 216–37.
Orr GA, Verdier-Pinard P, McDaid H, Horwitz SB . Mechanisms of taxol resistance related to microtubules. Oncogene 2003; 22: 7280–95.
Ojima I, Ferlini C . New insights into drug resistance in cancer. Chem Biol 2003; 10: 583–4.
Cunningham SL, Cunningham AR, Day BW . CoMFA, HQSAR and molecular docking studies of butitaxel analogues with betatubulin. J Mol Model 2005; 11: 48–54.
Czaplinski KHA, Grunewald GL . A comparative molecular-field analysis derived model of the binding of taxol analogs to microtubules. Bioorg Med Chem Lett 1994; 4: 2211–6.
Mohanraj S, Doble M . 3-d QSAR studies of microtubule stabilizing antimitotic agents towards six cancer cell lines. QSAR Comb Sci 2006; 25: 952–60.
Pineda O, Farras J, Maccari L, Manetti F, Botta M, Vilarrasa J . Computational comparison of microtubule-stabilising agents laulimalide and peloruside with taxol and colchicine. Bioorg Med Chem Lett 2004; 14: 4825–9.
Roy K, Pal DK, De AU, Sengupta C . Hansch analysis of anticancer activities of C-2-modified paclitaxel analogs against human ovarian carcinoma 1A9, human colon carcinoma HCT116 and human Burkitt lymphoma CA46 cell lines. Indian J Chem Sect B-Org Chem Incl Med Chem 1999; 38: 1194–202.
Monti E, Gariboldi M, Maiocchi A, Marengo E, Cassino C, Gabano E, et al. Cytotoxicity of cis-platinum (II) conjugate models. The effect of chelating arms and leaving groups on cytotoxicity: A quantitative structure—activity relationship approach. J Med Chem 2005; 48: 857–66.
van de Waterbeemd H, Gifford E . ADMET in silico modelling: Towards prediction paradise? Nat Rev Drug Discov 2003; 2: 192–204.
Yu HS, Adedoyin A . ADME-Tox in drug discovery: integration of experimental and computational technologies. Drug Discov Today 2003; 8: 852–61.
Helguera AM, Rodriguez-Borges JE, Garcia-Mera X, Fernandez F, Natalia M, Cordeiro DS . Probing the anticancer activity of nucleoside analogues: A QSAR model approach using an internally consistent training set. J Med Chem 2007; 50: 1537–45.
Wang YH, Li Y, Li YH, Yang SL, Yang L . Modeling K-m values using electrotopological state: Substrates for cytochrome P450 3A4-mediated metabolism. Bioorg Med Chem Lett 2005; 15: 4076–84.
Habibi-Yangjeh A, Danandeh-Jenagharad M, Nooshyar M . Application of artificial neural networks for predicting the aqueous acidity of various phenols using QSAR. J Mol Model 2006; 12: 338–47.
Siu FM, Che CM . Quantitative structure—activity (affinity) relationship (QSAR) study on protonation and cationization of alpha-amino acids. J Phys Chem A 2006; 110: 12 348–54.
Su Q, Zhou L . QSAR modeling of AT 1 receptor antagonists using ANN. J Mol Model 2006; 12: 869–75.
Aoyama T, Suzuki Y, Ichikawa H . Neural networks applied to pharmaceutical problems. III. Neural networks applied to quantitative structure—activity relationship (QSAR) analysis. J Med Chem 1990; 33: 2583–90.
Wang YH, Li Y, Yang SL, Yang L . Classification of substrates and inhibitors of P-glycoprotein using unsupervised machine learning approach. J Chem Inf Model 2005; 45: 750–7.
Barboni L, Ballini R, Giarlo G, Appendino G, Fontana G, Bombardelli E . Synthesis and biological evaluation of methoxylated analogs of the newer generation taxoids IDN5109 and IDN5390. Bioorg Med Chem Lett 2005; 15: 5182–6.
Ojima I, Inoue T, Chakravarty S . Enantiopure fluorine-containing taxoids: potent anticancer agents and versatile probes for biomedical problems. J Fluor Chem 1999; 97: 3–10.
Ojima I, Kuduk SD, Pera P, Veith JM, Bernacki RJ . Synthesis and structure-activity relationships of nonaromatic taxoids: Effects of alkyl and alkenyl ester groups on cytotoxicity. J Med Chem 1997; 40: 279–85.
Ojima I, Slater JC, Michaud E, Kuduk SD, Bounaud PY, Vrignaud P, et al. Syntheses and structure-activity relationships of the second-generation antitumor taxoids: Exceptional activity against drug-resistant cancer cells. J Med Chem 1996; 39: 3889–96.
Ojima I, Wang T, Miller ML, Lin SN, Borella CP, Geng XD, et al. Synthesis and structure-activity relationships of new second-generation taxoids. Bioorg Med Chem Lett 1999; 9: 3423–8.
Zhu QQ, Guo ZR, Huang N, Wang MM, Chu FM . Comparative molecular field analysis of a series of paclitaxel analogues. J Med Chem 1997; 40: 4319–28.
Skehan P, Storeng R, Scudiero D, Monks A, McMahon J, Vistica D, et al. New colorimetric cytotoxicity assay for anticancer-drug screening. J Natl Cancer Inst 1990; 82: 1107–12.
Golbraikh A, Tropsha A . Beware of q2!. J Mol Graph Model 2002; 20: 269–76.
Kier LB, Hall LH . The prediction of ADMET properties using structure information representations. Chem Biodivers 2005; 2: 1428–37.
Hall LH, Kier LB . Electrotopological state indexes for atom types—a novel combination of electronic, topological, and valence state information. J Chem Inf Comput Sci 1995; 35: 1039–45.
Hall LH, Kier LB . The E-state as the basis for molecular structure space definition and structure similarity. J Chem Inf Comput Sci 2000; 40: 784–91.
Votano JR, Parham M, Hall LM, Hall LH, Kier LB, Oloff S, et al. QSAR modeling of human serum protein binding with several modeling techniques utilizing structure-information representation. J Med Chem 2006; 49: 7169–81.
Hagan MT, Menhaj MB . Training feedforward networks with the Marquardt algorithm. Neural Networks, IEEE Transactions on 1994; 5: 989–93.
Tetko IV, Livingstone DJ, Luik AI . Neural-network studies 1. Comparison of overfitting and overtraining. J Chem Inf Comput Sci 1995; 35: 826–33.
Berry MJA, Linoff G . Data mining techniques. NY: John Wiley & Sons; 1997.
Han LQ . The principle, design and application of artificial neural network. Beijing: Chemical Industry Publishing Company; 2002.
Chen LJ, Lian GP . Prediction of human skin permeability using artificial neural network (ANN). Acta Pharmacol Sin 2007; 28: 591–600.
Cramer RD, Patterson DE, Bunce JD . Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. J Am Chem Soc 1988; 110: 5959–67.
Ganesh T, Yang C, Norris A, Glass T, Bane S, Ravindra R, et al. Evaluation of the tubulin-bound paclitaxel conformation: Synthesis, biology, and SAR studies of C-4 to C-3′ bridged paclitaxel analogues. J Med Chem 2007; 50: 713–25.
Snyder JP, Nettles JH, Cornett B, Downing KH, Nogales E . The binding conformation of taxol in beta-tubulin: a model based on electron crystallographic density. Proc Natl Acad Sci USA 2001; 98: 5312–6.
Vander Velde DG, Georg GI, Grunewald GL, Gunn CW, Mitscher LA . “Hydrophobic collapse” of taxol and taxotere solution conformations in mixtures of water and organic solvent. J Am Chem Soc 1993; 115: 11 650–1.
Tropsha A, Gramatica P, Gombar VK . The importance of being earnest: validation is the absolute essential for successful application and interpretation of QSPR models. QSAR Comb Sci 2003; 22: 69–77.
Author information
Authors and Affiliations
Corresponding authors
Additional information
Project supported by the National Natural Science Foundation of China (No 30640066 and 30630075), and the Innovation Youth Foundation of Dalian Institute of Chemical Physics (No S200612).
Rights and permissions
About this article
Cite this article
Dong, Pp., Zhang, Yy., Ge, Gb. et al. Modeling resistance index of taxoids to MCF-7 cell lines using ANN together with electrotopological state descriptors. Acta Pharmacol Sin 29, 385–396 (2008). https://doi.org/10.1111/j.1745-7254.2008.00746.x
Received:
Accepted:
Issue Date:
DOI: https://doi.org/10.1111/j.1745-7254.2008.00746.x