Dependence of QSAR models on the selection of trial descriptor sets: A demonstration using nanotoxicity endpoints of decorated nanotubes

Journal of Chemical Information and Modeling

Volumn 53, Issue 1, 2013, Pages 142-158

  Shao, Chi Yu ^a   Chen, Sing Zuo ^a   Su, Bo Han ^a   Tseng, Yufeng J ^a   Esposito, Emilio Xavier ^b,c   Hopfinger, Anton J ^b,d  

^a NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^b Chem21 Group Inc ^*  (United States)

^c ExeResearch LLC ^*  (United States)

^d UNIVERSITY OF NEW MEXICO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL CHEMISTRY; MOLECULAR GRAPHICS; NANOTUBES;

COMBINATORIAL LIBRARY; DESCRIPTORS; NANOTOXICITY; QSAR ANALYSIS; QSAR MODEL; SURFACE-MODIFIED; TRAINING SETS; VOLSURF;

MULTIWALLED CARBON NANOTUBES (MWCN);

NANOTUBE; PROTEIN;

ANIMAL; ARTICLE; BIOASSAY; CATTLE; CHEMICAL STRUCTURE; CHEMISTRY; CONFORMATION; METABOLISM; QUANTITATIVE STRUCTURE ACTIVITY RELATION; TOXICITY TESTING;

ANIMALS; CATTLE; ENDPOINT DETERMINATION; MODELS, MOLECULAR; MOLECULAR CONFORMATION; NANOTUBES; PROTEINS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; TOXICITY TESTS;

MLCS; MLOWN;

EID: 84873050306     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci3005308     Document Type: Article

References (38)

1. Zhou, H.; Mu, Q.; Gao, N.; Liu, A.; Xing, Y.; Gao, S.; Zhang, Q.; Qu, G.; Chen, Y.; Liu, G.; Zhang, B.; Yan, B. A nano-combinatorial library strategy for the discovery of nanotubes with reduced protein-binding, cytotoxicity, and immune response Nano Lett. 2008, 8 (3) 859-865
2. Fourches, D.; Pu, D.; Tassa, C.; Weissleder, R.; Shaw, S. Y.; Mumper, R. J.; Tropsha, A. Quantitative nanostructure-activity relationship modeling ACS Nano 2010, 4 (10) 5703-5712
3. Fourches, D.; Pu, D.; Tropsha, A. Exploring quantitative nanostructure-activity relationships (QNAR) modeling as a tool for predicting biological effects of manufactured nanoparticles Comb. Chem. High Throughput Screening 2011, 14 (3) 217-225
4. Tejral, G.; Panyala, N. R.; Havel, J. Carbon nanotubes: Toxicological impact on human health and environment J. Appl. Biomed. 2009, 7 (2) 1-13
5. Jia, G.; Wang, H.; Yan, L.; Wang, X.; Pei, R.; Yan, T.; Zhao, Y.; Guo, X. Cytotoxicity of carbon nanomaterials: Single-wall nanotube, multi-wall nanotube, and fullerene Environ. Sci. Technol. 2005, 39 (5) 1378-1383
6. Kaiser, J.-P.; Krug, H. F.; Wick, P. Nanomaterial cell interactions: How do carbon nanotubes affect cell physiology? Nanomedicine (London) 2009, 4 (1) 57-63
7. Mu, Q.; Du, G.; Chen, T.; Zhang, B.; Yan, B. Suppression of human bone morphogenetic protein signaling by carboxylated single-walled carbon nanotubes ACS Nano 2009, 3 (5) 1139-1144
8. Zhang, B.; Xing, Y.; Li, Z.; Zhou, H.; Mu, Q.; Yan, B. Functionalized carbon nanotubes specifically bind to alpha-chymotrypsin's catalytic site and regulate its enzymatic function Nano Lett. 2009, 9 (6) 2280-2284
9. Mu, Q.; Broughton, D. L.; Yan, B. Endosomal leakage and nuclear translocation of multi-walled carbon nanotubes: Developing a model for cell uptake Nano Lett. 2009, 9 (12) 4370-4375
10. Zhou, H.; Jiao, P.; Yang, L.; Li, X.; Yan, B. Enhancing cell recognition by scrutinizing cell surfaces with a nanoparticle array J. Am. Chem. Soc. 2011, 133 (4) 680-682
11. Gao, N.; Zhang, Q.; Mu, Q.; Bai, Y.; Li, L.; Zhou, H.; Butch, E. R.; Powell, T. B.; Snyder, S. E.; Jiang, G.; Yan, B. Steering carbon nanotubes to scavenger receptor recognition by nanotube surface chemistry modification partially alleviates NFκB activation and reduces its immunotoxicity ACS Nano 2011, 5 (6) 4581-4591
12. Moyano, D. F.; Rotello, V. M. Nano meets biology: Structure and function at the nanoparticle interface Langmuir 2011, 27 (17) 10376-10385
13. Zhang, Y.; Yan, B. Cell cycle regulation by carboxylated multi-walled carbon nanotubes through p53-independent induction of p21 under the control of the BMP signaling pathway Chem. Res. Toxicol. 2012, 25 (6) 1212-1221
14. Baker, G. L.; Gupta, A.; Clark, M. L.; Valenzuela, B. R.; Staska, L. M.; Harbo, S. J.; Pierce, J. T.; Dill, J. A. Inhalation toxicity and lung toxicokinetics of C60 fullerene nanoparticles and microparticles Toxicol. Sci. 2008, 101 (1) 122-131
15. Weissleder, R.; Kelly, K.; Sun, E. Y.; Shtatland, T.; Josephson, L. Cell-specific targeting of nanoparticles by multivalent attachment of small molecules Nat. Biotechnol. 2005, 23 (11) 1418-1423
16. Zhou, H.; Du, F.; Li, X.; Zhang, B.; Li, W.; Yan, B. Characterization of organic molecules attached to gold nanoparticle surface using high resolution magic angle spinning 1H NMR J. Phys. Chem. C 2008, 112 (49) 19360-19366
17. Mu, Q.; Li, Z.; Li, X.; Mishra, S. R.; Zhang, B.; Si, Z.; Yang, L.; Jiang, W.; Yan, B. Characterization of protein clusters of diverse magnetic nanoparticles and their dynamic interactions with human cells J. Phys. Chem. C 2009, 113 (14) 5390-5395
18. Mahmoudi, M.; Lynch, I.; Ejtehadi, M. R.; Monopoli, M. P.; Bombelli, F. B.; Laurent, S. Protein-nanoparticle interactions: Opportunities and challenges Chem. Rev. 2011, 111 (9) 5610-5637
19. Myllynen, P.i. Damaging DNA from a distance Nat. Nanotechnol. 2009, 4 (12) 795-796
20. Panyala, N. R.; Pena-Mendez, E. M.; Havel, J. Silver or silver nanoparticles: A hazardous threat to the environment and human health? J. Appl. Biomed. 2008, 6 (3) 117-129
21. Panyala, N. R.; Pena-Mendez, E. M.; Havel, J. Gold and nano-gold in medicine: Overview, toxicology and perspectives J. Appl. Biomed. 2009, 7 (2) 75-91
22. Stern, S. T.; McNeil, S. E. Nanotechnology safety concerns revisited Toxicol. Sci. 2008, 101 (1) 4-21
23. Kipen, H. M.; Laskin, D. L. Smaller is not always better: Nanotechnology yields nanotoxicology Am. J. Physiol.: Lung Cell. Mol. Physiol. 2005, 289 (5) L696-L697
24. Kostarelos, K. The long and short of carbon nanotube toxicity Nat. Biotechnol. 2008, 26 (7) 774-776
25. Wörle-Knirsch, J. M.; Pulskamp, K.; Krug, H. F. Oops they did it again! Carbon nanotubes hoax scientists in viability assays Nano Lett. 2006, 6 (6) 1261-1268
26. 15N] nitrate in biological fluids Anal. Biochem. 1982, 126 (1) 131-138
27. Holland, J. H. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence; University of Michigan: Ann Arbor, MI, 1975.
28. Rogers, D.; Hopfinger, A. J. Application of genetic function approximation to quantitative structure-activity relationships and quantitative structure-property relationships J. Chem. Inf. Model. 1994, 34 (4) 854-866
29. Friedman, J. Multivariate Adaptive Regression Splines; Technical Report Number 102; Laboratory for Computational Statistics, Department of Statistics, Stanford University: Stanford, CA, 1990.
30. Golbraikh, A.; Tropsha, A. Beware of q2! J. Mol. Graphics Modell. 2002, 20 (4) 269-276
31. Shao, J. Linear model selection by cross-validation J. Am. Stat. Assoc. 1993, 88 (422) 486-494
32. Molecular Operating Environment (MOE); Chemical Computing Group, Inc.: Montreal, Quebec, Canada. http://www.chemcomp.com (accessed October 30, 2012).
33. Cruciani, G.; Crivori, P.; Carrupt, P.; Testa, B. Molecular fields in quantitative structure-permeation relationships: The VolSurf approach J. Mol. Struct.: THEOCHEM 2000, 503 (1-2) 17-30
34. Cruciani, G.; Pastor, M.; Guba, W. VolSurf: A new tool for the pharmacokonetic optimization of lead compounds Eur. J. Pharm. Sci. 2000, 11, S29-S39
35. Cruciani, G.; Pastor, M.; Mannhold, R. Suitability of molecular descriptors for database mining. A comparative analysis J. Med. Chem. 2002, 45 (13) 2685-2694
36. Senese, C. L.; Duca, J.; Pan, D.; Hopfinger, A. J.; Tseng, Y. J. 4D-fingerprints, universal QSAR and QSPR descriptors J. Chem. Inf. Model. 2004, 44 (5) 1526-1539
37. Lin, A. QuaSAR-Descriptor. http://www.chemcomp.com/journal/descr.htm (accessed Nov. 1, 2012).
38. Wildman, S. A.; Crippen, G. M. Prediction of physiochemical parameters by atomic contributions J. Chem. Inf. Model. 1999, 39 (5) 868-873