Modelling in vitro hepatotoxicity using molecular interaction fields and SIMCA

Journal of Molecular Graphics and Modelling

Volumn 22, Issue 6, 2004, Pages 487-497

  Clark, Robert D ^a   Wolohan, Philippa R N ^a   Hodgkin, Edward E ^a   Kelly, James H ^b   Sussman, Norman L ^b  

^a TRIPOS INC   (United States)

^b Amphioxus Cell Technologies   (United States)

Author keywords

CoMFA; HepG2 C3A; In silico toxicology; In vitro hepatotoxicity; Molecular field analysis; SIMCA

Indexed keywords

COMPUTATIONAL METHODS; MATHEMATICAL MODELS; TOXICITY;

HEPATOTOXICITY; PHYSICOCHEMICAL PROPERTIES;

DRUG PRODUCTS;

BIOAVAILABILITY; CELL CULTURE; CONFERENCE PAPER; CONTROLLED STUDY; DATA ANALYSIS; DISEASE MARKER; HUMAN; HUMAN CELL; LIVER TOXICITY; MATHEMATICAL MODEL; MOLECULAR INTERACTION; PHYSICAL CHEMISTRY; PKA; PRIORITY JOURNAL; SOLUBILITY;

ADENOSINE TRIPHOSPHATE; BIOLOGICAL ASSAY; CASPASES; CELL PROLIFERATION; COMPUTER SIMULATION; DRUG DESIGN; DRUG EVALUATION, PRECLINICAL; HEPATOCYTES; HUMANS; L-LACTATE DEHYDROGENASE; MOLECULAR STRUCTURE; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; TOXICOLOGY;

EID: 2942585269     PISSN: 10933263     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jmgm.2004.03.009     Document Type: Conference Paper

References (36)

1. van de Waterbeemd H., Gifford E. ADMET in silico modeling: towards prediction paradise? Nat. Rev. Drug Discov. 2:2003;192-204
2. Stouch T.R., Kenyon J.R., Johnson S.R., Chen X.-Q., Doweyko A., Li Y. In silico ADME/Tox: why models fail. J. Comput.-Aided Mol. Des. 17:2003;83-92
3. Clark D.E. Rapid calculation of polar molecular surface area and its application to the prediction of transport phenomena. 1. Prediction of intestinal absorption. J. Pharm. Sci. 88:1999;807-814
4. Cruciani G., Crivori P., Carrupt R.-A., Testa B. Molecular fields in quantitative structure-permeation relationships: the VolSurf approach. J. Mol. Struct. (Theochem.). 503:2000;17-30
5. Clark D.E. Rapid calculation of polar molecular surface area and its application to the prediction of transport phenomena. 2. Prediction of blood-brain barrier penetration. J. Pharm. Sci. 88:1999;815-821
6. Crivori P., Cruciani G., Carrupt P.-A., Testa B. Predicting blood-brain barrier permeation from three-dimensional molecular structure. J. Med. Chem. 43:2000;2204-2216
7. de Groot M.J., Ackland M.J., Horne V.A., Alex A.A., Jones B.C. A novel approach to predicting P450 mediated drug metabolism. CYP2D6 catalyzed N-dealkylation reactions and qualitative metabolite predictions using a combined protein and pharmacophore model for CYP2D6. J. Med. Chem. 42:1999;4062-4070
8. Rao S., Aoyama R., Schrag M., Trager W.F., Rettie A., Jones J.P. A refined 3-dimensional QSAR of cytochrome P450 2C9: computational predictions of drug interactions. J. Med. Chem. 43:2000;2789-2796
9. Snyder R., Sanger R., Wang J., Eakins S. Three-dimensional quantitative structure activity relationship for CYP2D6 substrates. Quant. Struct.-Act. Relat. 21:2002;357-368
10. Zamora I., Afzelius I., Cruciani G. Predicting drug metabolism: a site of metabolism prediction tool applied to the cytochrome P450. J. Med. Chem. 46:2003;2313-2324
11. Lipinski C.A., Lombardo F., Dominy B.W., Feeney P.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Del. Rev. 23:1997;3-25
12. R.D. Cramer III, S.A. DePriest, D.E. Patterson, P. Hecht, The developing practice of comparative molecular field analysis, in: H. Kubinyi (Ed.), 3D QSAR in Drug Design, vol. 1, ESCOM, Leiden, 1993, pp. 443-485.
13. Y.C. Martin, 3D QSAR: current state, scope, and limitations, in: H. Kubinyi, G. Folkers, Y.C. Martin (Eds.), 3D QSAR in Drug Design, vol. 3, Kluwer Academic Publishers/ESCOM, Dordrecht, 1998, pp. 3-23.
14. C.J. Blankley, Recent developments in 3D-QSAR, in: H. van de Waterbeemd (Ed.), Structure-Property Correlations in Drug Research, Academic Press, Austin, 1996, pp. 111-177.
15. R.D. Clark, J.M. Leonard, A. Strizhev, Pharmacophore models and comparative molecular field analysis (CoMFA), in: O. Güner (Ed.), Pharmacophore Perception, Development, and Use in Drug Design, International University Line, La Jolla, 2000, pp. 151-169.
16. Goodford P.J. A computational procedure for determining energetically favorable binding sites on biologically important molecules. J. Med. Chem. 28:1985;849-857
17. Klebe G., Abraham U., Mietzner T. Molecular similarity indices in a comparative analysis (CoMSIA) of drug molecules to correlate and predict their biological activity. J. Med. Chem. 37:1994;4130-4146
18. R.D. Clark, A.M. Ferguson, R.D. Cramer, Bioisosterism and molecular diversity, in: H. Kubinyi, G. Folkers, Y.C. Martin (Eds.), 3D QSAR in Drug Design, vol. 2, Kluwer Academic Publishers/ESCOM, Dordrecht, 1998, pp. 211-224.
19. Wolohan P.R.N., Clark R.D. Predicting drug pharmacokinetic properties using molecular interaction fields and SIMCA. J. Comput.-Aided Mol. Des. 17:2003;65-76
20. Cramer R.D., Patterson D.E., Clark R.D., Soltanshahi F., Lawless M.S. Virtual compound libraries: a new approach to decision making in molecular discovery research. J. Chem. Inf. Comput. Sci. 38:1998;1010-1023
21. Cramer R.D., Poss M.A., Hermsmeir M.A., Caulfield T.J., Kowala M.C., Valentine M.T. Prospective identification of biologically active structures by topomer shape similarity searching. J. Med. Chem. 42:2000;3919-3933
22. Cramer R.D., Jilek R.J., Andrews K.M. dbtop: topomer similarity searching of conventional databases. J. Mol. Graph. Model. 20:2002;447-462
23. S. Wold, M. Sjöström, Method for analyzing chemical data in terms of similarity and analogy, in: B.R. Kowalski (Ed.), Chemometrics: Theory and Applications, vol. 52, ACS Symposium Series, 1977, pp. 243-282.
24. Sigma catalog number SC001. http://Sigma-Aldrich.com.
25. The Merck Index, 12th Ed., Version 12:3, Chapman & Hall/CRCnetBASE Electronic Publishing Division, 2000 (CD-ROM).
26. Gasteiger J., Marsili M. Iterative partial equalization of orbital electronegativity - a rapid access to atomic charges. Tetrahedron. 36:1980;3219-3228
27. Kelly J.H., Sussman N.L. A fluorescent cell-based assay for cytochrome P-450 isozyme 1A2 induction and inhibition. J. Biomol. Screen. 5:2000;249-253
28. Duewer D.L., Clark R.D. Rank-order analysis for robust evaluation of multi-response, multi-block comparisons. J. Chemometrics. 5:1991;503-521
29. R.D. Clark, J.J. Parlow, L.H. Brannigan, D.M. Schnur, D.L. Duewer, Applications of scaled rank-sum statistics in herbicide QSAR, in: C. Hansch, T. Fujita (Eds.), Classical and Three-Dimensional QSAR in Agrochemistry, vol. 606, ACS Symposium Series, American Chemical Society, Washington DC, 1995, pp. 264-281.
30. Clark R.D. OptiSim: an extended dissimilarity selection method for finding diverse representative subsets. J. Chem. Inf. Comput. Sci. 37:1997;1181-1188
31. R.D. Clark, US Patent 6, 535, 819 B1 (2003).
32. Yoshida F., Topliss J.G. QSAR model for drug human oral bioavailability. J. Med. Chem. 43:2000;2575-2595
33. Raevsky O.A., Trepalin S.V., Trepalina H.P., Gerasimenko V.A., Raevskaja O.E. SLIPPER-2001 - software for predicting molecular properties on the basis of physicochemical descriptors and structural similarity. J. Chem. Inf. Comput. Sci. 42:2002;540-549
34. Raevsky O.A., Schaper K.-J., Artursson P., McFarland J.W. A novel approach for prediction of intestinal absorption of drugs in humans based on hydrogen bond descriptors and structural similarity. Quant. Struct.-Act. Relat. 20:2002;402-413
35. Sietsema W.K. The absolute oral bioavailability of selected drugs. Int. J. Clin. Pharmacol. Ther. Toxicol. 27:1989;179-211
36. Veber D.F., Johnson S.R., Cheng H.-Y., Smith B.R., Ward K.W., Kopple K.D. Molecular properties that influence the oral bioavailability of drug candidates. J. Med. Chem. 45:2002;2615-2623