QSAR analysis of the toxicity of nitroaromatics in Tetrahymena pyriformis: structural factors and possible modes of action

References

• Patai , S . 1982 . The Chemistry of Amino, Nitroso, and Nitro Compounds and their Derivatives , New York : John Wiley & Sons .
   Google Scholar
• Feuer , H and Nielsen , AT . 1990 . Nitro Compounds: Recent Advances in Synthesis and Chemistry , New York : VCH Publishing .
   Google Scholar
• Neilson , AH and Allard , A-S . 2008 . Environmental Degradation and Transformation of Organic Chemicals , Boca Raton , FL : CRC Press .
   Google Scholar
• Talmage , SS , Opresko , DM , Maxwell , CJ , Welsh , CJ , Cretella , FM , Reno , PH and Daniel , FB . 1999 . Nitroaromatic munition compounds: Environmental effects and screening values . Rev. Environ. Contam. Toxicol. , 161 : 1 – 156 .
   PubMedGoogle Scholar
• Rickert , DE . 1984 . Toxicity of Nitroaromatic Compounds , Bristol , PA : Hemisphere Publishing Corp. .
   Google Scholar
• Robidoux , PY , Svendsen , C , Caumartin , J , Hawari , J , Ampleman , G , Thiboutot , S , Weeks , JM and Sunahara , GI . 2000 . Chronic toxicity of energetic compounds in soil determined using the earthworm (Eisenia andrei) reproduction test . Environ. Toxicol. Chem. , 19 : 1764 – 1773 .
   Web of Science ®Google Scholar
• Donlon , BA , Razo-Flores , E , Field , JA and Lettinga , G . 1995 . Toxicity of N-substituted aromatics to acetoclastic methanogenic activity in granular sludge . Appl. Environ. Microbiol. , 61 : 3889 – 3893 .
   PubMed Web of Science ®Google Scholar
• Cronin , MTD and Schultz , TW . 2001 . Development of quantitative structure-activity relationships for the toxicity of aromatic compounds to Tetrahymena pyriformis: Comparative assessment of the methodologies . Chem. Res. Toxicol. , 14 : 1284 – 1295 .
   PubMed Web of Science ®Google Scholar
• Katritzky , AR , Oliferenko , P , Oliferenko , A , Lomaka , A and Karelson , M . 2003 . Nitrobenzene toxicity: QSAR correlations and mechanistic interpretations . J. Phys. Org. Chem. , 16 : 811 – 817 .
   Web of Science ®Google Scholar
• Kuz’min , VE , Muratov , EN , Artemenko , AG , Gorb , LG , Qasim , M and Leszczynski , J . 2008 . The effects of characteristics of substituents on toxicity of the nitroaromatics: HiT QSAR study . J. Comp. Aid. Mol. Des. , 22 : 747 – 759 .
   PubMed Web of Science ®Google Scholar
• Agrawal , WK and Khadikar , PV . 2001 . QSAR prediction of toxicity of nitrobenzenes . Bioorg. Med. Chem. , 9 : 3035 – 3040 .
   PubMed Web of Science ®Google Scholar
• Cronin , MTD , Gregory , BW and Schultz , TW . 1998 . Quantitative structure-activity analyses of nitrobenzene toxicity to Tetrahymena pyriformis . Chem. Res. Toxicol. , 11 : 902 – 908 .
   PubMed Web of Science ®Google Scholar
• Bearden , AP and Schultz , TW . 1998 . Comparison of Tetrahymena and Pimephales toxicity based on mechanism of action . SAR QSAR Environ. Res. , 9 : 127 – 153 .
   PubMed Web of Science ®Google Scholar
• Schultz , TV , Lin , DT and Arnold , LM . 1991 . QSARs for monosubstituted anilines eliciting the polar narcosis mechanism of action . Sci. Total Environ. , 109 : 569 – 580 .
   PubMed Web of Science ®Google Scholar
• Schultz , TW , Lin , DT and Wesley , SK . 1992 . QSARs for monosubstitutued phenols and the polar narcosis mechanism of toxicity . Qual. Assur. Good Pract. Regul. Law , 1 : 132 – 143 .
   PubMedGoogle Scholar
• Vaes , WHJ , Ramos , EU , Verhaar , HJM and Hermens , JLM . 1998 . Acute toxicity of nonpolar versus polar narcosis: Is there a difference? . Environ. Toxicol. Chem. , 17 : 1380 – 1384 .
   Web of Science ®Google Scholar
• Estrada , E and Uriarte , E . 2001 . Quantitative structure-toxicity relationships using Tops-Mode. 1. Nitrobenzene toxicity to Tetrahymena pyriformis . SAR QSAR Env. Res. , 12 : 309 – 324 .
   PubMed Web of Science ®Google Scholar
• Dearden , JC , Cronin , MTD , Schultz , TW and Lin , DT . 1995 . QSAR study of the toxicity of nitrobenzenes to Tetrahymena pyriformis . QSAR , 14 : 427 – 432 .
   Web of Science ®Google Scholar
• Schmitt , H , Altenburger , R , Jastorff , B and Schuurmann , G . 2000 . Quantitative structure-activity analysis of the algae toxicity of nitroaromatic compounds . Chem. Res. Toxicol. , 13 : 441 – 450 .
   PubMed Web of Science ®Google Scholar
• Zhu , H , Tropsha , A , Fourches , D , Varnek , A , Papa , E , Gramatica , P , Oberg , T , Dao , P , Cherkasov , A and Tetko , IV . 2008 . Combinatorial QSAR modeling of chemical toxicants tested against Tetrahymena pyriformis . J. Chem. Inf. Model. , 48 : 766 – 784 .
   PubMed Web of Science ®Google Scholar
• Cronin , MTD , Bryant , SE , Dearden , JC and Schultz , T . 1995 . Quantitative structure-activity study of the toxicity of benzonitriles to the ciliate Tetrahymena pyriformis . SAR QSAR Environ. Res. , 3 : 1 – 13 .
   PubMedGoogle Scholar
• Cronin , MTD and Schultz , TW . 1996 . Structure-toxicity relationships for phenols to Tetrahymena pyriformis . Chemosphere , 32 : 1453 – 1468 .
   PubMed Web of Science ®Google Scholar
• Mekenyan , O , Roberts , DW and Karcher , W . 1997 . Molecular orbital parameters as predictors of skin sensitization potential of halo- and pseudohalobenzenes acting as SNAr electrophiles . Chem. Res. Toxicol. , 10 : 994 – 1000 .
   PubMed Web of Science ®Google Scholar
• Fourches , D , Muratov , EN and Tropsha , A . 2010 . Trust, but verify: On the importance of chemical structure curation in cheminformatics and QSAR modeling research . J. Chem. Inf. Model. , 50 : 1189 – 1204 .
   PubMed Web of Science ®Google Scholar
• Kuz’min , VE , Artemenko , AG and Muratov , EN . 2008 . Hierarchical QSAR technology on the base of simplex representation of molecular structure . J. Comp. Aid. Mol. Des. , 22 : 403 – 421 .
   PubMed Web of Science ®Google Scholar
• Artemenko , AG , Muratov , EN , Kuz’min , VE , Kovdienko , NA , Hromov , AI , Makarov , VA , Riabova , OB , Wutzler , P and Schmidtke , M . 2007 . Identification of individual structural fragments of N,N′-(bis-5-nitropyrimidyl)dispirotripiperazine derivatives for cytotoxicity and antiherpetic activity allows the prediction of new highly active compounds . J. Antimicrob. Chemother. , 60 : 68 – 77 .
   PubMed Web of Science ®Google Scholar
• Kuz’min , VE , Artemenko , AG , Lozitska , RN , Fedtchouk , AS , Lozitsky , VP , Muratov , EN and Mescheriakov , AK . 2005 . Investigation of anticancer activity of macrocyclic Schiff bases by means of 4D-QSAR based on simplex representation of molecular structure . SAR QSAR Environ. Res. , 16 : 219 – 230 .
   PubMed Web of Science ®Google Scholar
• Kuz’min , VE , Muratov , EN , Artemenko , AG , Gorb , LG , Qasim , M and Leszczynski , J . 2008 . The effect of nitroaromatics’ composition on their toxicity in vivo: Novel, efficient non-additive 1D QSAR analysis . Chemosphere , 72 : 1373 – 1380 .
   PubMed Web of Science ®Google Scholar
• Muratov , EN , Artemenko , AG , Kuz’min , VE , Lozitsky , VP , Fedchuk , AS , Lozitska , RN , Boschenko , YA and Gridina , TL . 2005 . Investigation of anti-influenza activity using hierarchic QSAR technology on the base of simplex representation of molecular structure . Antivir. Res. , 65 : A62 – A63 .
   Web of Science ®Google Scholar
• Muratov , EN , Varlamova , EV , Artemenko , AG , Kuz’min , VE , Makarov , VA , Riabova , OB , Wutzler , P and Schmidtke , M . 2011 . QSAR analysis of [(biphenyloxy)propyl]isoxazoles – agents against coxsackievirus B3 . Future Med. Chem. , 3 : 31 – 43 .
   Web of Science ®Google Scholar
• Jolly , WL and Perry , WB . 1973 . Estimation of atomic charges by an electronegativity equalization procedure calibration with core binding energies . J. Am. Chem. Soc. , 95 : 5442 – 5450 .
   Web of Science ®Google Scholar
• Wang , R , Fu , Y and Lai , L . 1997 . A new atom–additive method for calculating partition coefficients . J. Chem. Inf. Comput. Sci. , 37 : 615 – 621 .
   Google Scholar
• Ioffe , BV . 1983 . Chemistry Refractometric Methods , Himiya : Leningrad .
   Google Scholar
• Kuz’min , VE , Artemenko , AG , Lozitsky , VP , Muratov , EN , Fedtchouk , AS , Dyachenko , NS , Nosach , LN , Gridina , TL , Shitikova , LI , Mudrik , LM , Mescheriakov , AK , Chelombitko , VA , Zheltvay , AI and Vanden Eynde , J-J . 2002 . The analysis of structure- anticancer and antiviral activity relationships for macrocyclic pyridinophanes and their analogues on the basis of 4D QSAR models (simplex representation of molecular structure) . Acta Biochim. Polon. , 49 : 157 – 168 .
   PubMed Web of Science ®Google Scholar
• Kuz’min , VE , Artemenko , AG , Muratov , EN , Volineckaya , IL , Makarov , VA , Riabova , OB , Wutzler , P and Schmidtke , M . 2007 . Quantitative Structure–Activity Relationship studies of [(biphenyloxy)propyl]isoxazole derivatives – human rhinovirus 2 replication inhibitors . J. Med. Chem. , 50 : 4205 – 4213 .
   PubMed Web of Science ®Google Scholar
• Lindgren , F , Geladi , P , Rannar , S and Wold , S . 1994 . Interactive variable selection (IVS) for PLS. Part 1: Theory and Algorithms . J. Chemometr. , 8 : 349 – 363 .
   Web of Science ®Google Scholar
• Rannar , S , Lindgren , F , Geladi , P and Wold , S . 1994 . A PLS kernel algorithm for data sets with many variables and fewer objects. Part 1: Theory and algorithm . J. Chemometr. , 8 : 111 – 125 .
   Web of Science ®Google Scholar
• Hasegawa , K , Miyashita , Y and Funatsu , K . 1997 . GA strategy for variable selection in QSAR studies: GA-based PLS analysis of calcium channel antagonists . J. Chem. Inf. Comput. Sci. , 37 : 306 – 310 .
   PubMedGoogle Scholar
• Carhart , RE , Smith , DH and Venkataraghavan , R . 1985 . Atom pairs as molecular features in structure - activity studies. Definition and application . J. Chem. Inf. Comput. Sci. , 25 : 64 – 73 .
   Google Scholar
• Kuz’min , VE , Artemenko , AG , Kovdienko , NA , Tetko , IV and Livingstone , DJ . 2000 . Lattice model for QSAR studies . J. Mol. Model. , 6 : 517 – 526 .
   Web of Science ®Google Scholar
• Vitiuk , NV and Kuz’min , VE . 1994 . Mechanistic models in chemometrics for the analysis of multidimensional data of researches. Analogue of dipole-moments method in the structure(composition)-property relationships analysis . Zh. Anal. Khimii , 49 : 165 – 167 .
   Google Scholar
• Lindgren , F , Geladi , P , Rдnnar , S and Wold , S . 1996 . Interactive variable selection (IVS) for PLS. Part 1: Theory and algorithms . J Chemometr. , 8 : 349 – 363 .
   Web of Science ®Google Scholar
• Kubinyi , H . 1996 . Evolutionary variable selection in regression and PLS analyses . J Chemometr. , 10 : 119 – 133 .
   Web of Science ®Google Scholar
• Kuz’min , VE , Muratov , EN , Artemenko , AG , Varlamova , EV , Gorb , LG , Wang , J and Leszczynski , J . 2009 . Consensus QSAR modeling of phosphor-containing chiral AChE inhibitors . QSAR Comb. Sci. , 28 : 664 – 677 .
   Google Scholar
• Breiman , L , Friedman , JH , Olshen , RA and Stone , CJ . 1984 . Classification and Regression Trees , Belmont : Wadsworth .
   Google Scholar
• Tropsha , A , Gramatica , P and Gombar , V . 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 .
   Google Scholar
• Muratov , EN , Artemenko , AG , Varlamova , EV , Polischuk , PG , Lozitsky , VP , Fedtchuk , AS , Lozitska , RN , Gridina , TL , Koroleva , LS , Sil’nikov , VN , Galabov , AS , Makarov , VA , Riabova , OB , Wutzler , P , Schmidtke , M and Kuz’min , VE . 2010 . Per aspera ad astra: Application of Simplex QSAR approach in antiviral research . Future Med. Chem. , 2 : 1205 – 1226 .
   PubMed Web of Science ®Google Scholar
• Tropsha , A . 2010 . Best practices for QSAR model development, validation, and exploitation . Mol. Inf. , 29 : 476 – 488 .
   PubMed Web of Science ®Google Scholar
• Tropsha , A and Golbraikh , A . 2007 . Predictive QSAR modeling workflow model, applicability domains, and virtual screening . Curr. Pharm. Des. , 13 : 3494 – 3504 .
   PubMed Web of Science ®Google Scholar
• Todeschini , R , Ballabio , D , Consonni , V , Manganaro , A and Mauri , A . 2009 . Canonical Measure of Correlation (CMC) and Canonical Measure of Distance (CMD) between sets of data. Part 1. Theory and simple chemometric applications . Anal. Chim. Acta , 548 : 45 – 51 .
   Web of Science ®Google Scholar
• Todeschini , R , Consonni , V and Pavan , M . 2004 . A distance measure between models: A tool for similarity/diversity analysis of model populations . Chemometr. Int. Lab. Sys. , 70 : 55 – 61 .
   Web of Science ®Google Scholar
• Davison , ML . 1983 . Introduction to multidimensional scaling and its applications . Appl. Psychol. Meas. , 7 : 373 – 379 .
   Web of Science ®Google Scholar
• Ad hoc Expert Group on QSARs, The Report from the Expert Group on (Quantitative) Structure–Activity Relationships [(Q)SARs] on the Principles for the Validation of (Q)SARs, OECD Environment Health and Safety Publications, Series on Testing and Assessment No. 49, OCED, Paris, 2004
   Google Scholar
• Muratov , EN , Kuz’min , VE and Artemenko , AG . Domain applicability: How far are ideal and reality? 235th ACS national Meeting, New Orleans, LA, 6–10 April 2008. Available at http://oasys2.confex.com/acs/235 nm/techprogram/P1145213.HTM
   Google Scholar
• Minieka , E . 1978 . Optimization Algorithms for Networks and Graphs , New York : Marcel Dekker .
   Google Scholar
• Jaworska , J , Nikolova-Jeliazkova , N and Aldenberg , T . 2005 . QSAR applicability domain estimation by projection of the training set in descriptor space: A review . Altern. Lab. Anim. , 33 : 445 – 459 .
   PubMed Web of Science ®Google Scholar
• Kubinyi , H . 1990 . Quantitative structure–activity relationships (QSAR) and molecular modeling in cancer research . J. Cancer Res. Clin. Oncol. , 116 : 529 – 537 .
   PubMed Web of Science ®Google Scholar
• Gramatica , P . 2007 . Principles of QSAR models validation: Internal and external . QSAR Comb. Sci. , 26 : 694 – 701 .
   Google Scholar
• Golbraikh , A and Tropsha , A . 2002 . Beware of Q2 . J. Mol. Graph. Model. , 20 : 269 – 276 .
   PubMed Web of Science ®Google Scholar
• Tetko , IV , Sushko , I , Pandey , AK , Tropsha , A , Zhu , H , Papa , E , Öberg , T , Todeschini , R , Fourches , D and Varnek , A . 2008 . Critical assessment of QSAR Models to predict environmental toxicity against Tetrahymena pyriformis: Focusing on applicability domain and overfitting by variable selection . J. Chem. Inf. Model. , 48 : 1733 – 1746 .
   PubMed Web of Science ®Google Scholar
• Cramer , RD , Patterson , DI and Bunce , JD . 1988 . Comparative molecular field analysis (CoMFA). 1. Effect of shape binding to carrier proteins. . J. Am. Chem. Soc. , 110 : 5959 – 5967 .
   PubMed Web of Science ®Google Scholar
• Dearden , JC , Cronin , MTD , Schultz , TW and Lin , DT . 1995 . QSAR Study of the Toxicity of Nitrobenzenes to Tetrahymena pyriformis . Quant. Struct.-Act. Relat , 14 : 427 – 432 .
   Web of Science ®Google Scholar