Genetic Algorithm Applied to the Selection of Factors in Principal Component: ASQR Study of Aromatic Hydrocarbons Toxicity to Chlorella Vulgaris

Abstract:

Marine ecosystems are affected by aromatic hydrocarbons. The predicting ability based on the quantitative structureactivity relationships (QSAR) model of unknown aromatic hydrocarbons toxicity is one of the tasks of security precaution. To establish the QSAR model between the physical and chemical properties of aromatic hydrocarbons and the inhibited activity of Chlorella vulgaris(C. Vulgaris), the optimized geometries, based on the 96 hr-EC₅₀ of 25 aromatic hydrocarbons with C. Vulgaris were carried out at the B3LYP/6-311G** level by density functional theory (DFT) calculation. With matlab2 010(a) software, genetic algorithm principal components regression (GAPCR) methods was used to develop the QSAR model and compared to traditional PCR model. PC1+PC3+PC5+PC6+PC8 were finally selected by GAPCR method. The of training, prediction data set and LOO cross validation are 0.918, 0.956 and 0.933, respectively. Meanwhile, the results of PCR were 0.949, 0.755 and 0.825, respectively. The results of this work showed that the GAPCR method has great results and good generalization capability. Comparing two motheds results indicting that GAPCR gives superior results to traditional PCR procedure.

• Periodical: Applied Mechanics and Materials (Volumes 321-324)
• Pages: 2065-2070
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.321-324.2065
• Online since: June 2013
• Authors: Sheng Long Yang, Yang Wu, Cui Hua Wang*, Hong Xia Yu, Lian Sheng Wang
• Keywords: Aromatic Hydrocarbons, Chlorella vulgaris, Genetic Algorithm (GA), PCR

References

[1] X. M. Lin, W. X. Liu, J. L. Chen, S. S. Xu, and P. Tao.Distribution and ecological risk assessment of polycyclic aromatic hydrocarbons in surface sediments from Bohai Sea, China.Acta Secintiae Circumstantiae.,25(2005),pp.70-75（In Chinese）.

[2] K.A. Bocskay, D. Tang, M.A. Orjuela and X. Liu, Chromosomal aberrations in cord blood are associated with prenatal exposure to carcinogenic polycyclic aromatic hydrocarbons. Cancer Epidemiology Biomarkers Pre., 14(2005), pp.506-511.

DOI: 10.1158/1055-9965.epi-04-0566

[3] J. Y. Ma, L. G. Xu, S. F. Wang, R. Q. Zheng, S. H. Jin, S.Q. Huang,Y. J. Huang, Toxicity of 40 herbicides to the green alga. Ecotox. Environ. Saf., 51(2002),p.128–132.

DOI: 10.1006/eesa.2001.2113

[4] M. Smiesko, E. Benfenati, Predictive models for aquatic toxicity of aldehydes designed for various model chemistries. J. Chem. Inf. Comput. Sci., 44(2004),p.976–984.

DOI: 10.1021/ci034219j

[5] K. Knauer, C. Lampert, J. Gonzalez-Valero.Comparison of in vitro and in vivo acute fish toxicity in relation to toxicant mode of action. Chemosphere., 68(2007),p.1434–1441.

DOI: 10.1016/j.chemosphere.2007.04.009

[6] . S.L. Yang, . Y. Wu, ang, H.X. Yu, and L.S. Wang. Toxicity of aromatic hydrocarbons on algal based on GLM model and neural networks,Acta Scientiae ircumstantiae. 32(2012) 1487-1496 (In Chinese) .

[7] M. J. Frisch, G. W. Trucks, H. B. Schlegel, G. E. Scuseria, M. A. Robb, J. R. Cheeseman J R, Zakrzewski V G, Montgomery Jr J A, Stratmann R E, Burant , S. Dapprich, J. M. Millam, A. D. Daniels, K. N. Kudin, M. C. Strain, O. Farkas, J. Tomasi, V. Barone, M. Cossi, R. Cammi, B. Mennucci, C. Pomelli, C. Adamo, S. Clifford, J. Ochterski, G. A. Petersson, P. Y. Ayala, Q. Cui, K. Morokuma, D. K. Malick, A. D. Rabuck, K. Raghavachari, J. B. Foresman, J. Cioslowski, J. V. Ortiz, A. G. Baboul, B. B. Stefanov, G. Liu, A. Liashenko, P. Piskorz, I. Komaromi, R. Gomperts, R. L. Martin, D. J. Fox,T. Keith, M. A. Al-Laham, C. Y. Peng, A. Nanayakkara, M. Challacombe, P. M. W. Gill, B. Johnson, W. Chen, M. W. Wong, J. L. Andres, C. Gonzalez, M. Head-Gordon, E. S. Replogle, J. A. Pople. Raghava-03, Revision A1, Gaussian, Inc., Pittsburgh., 2003.

[8] W. Y. Zhao.Econometrics tutorial. Shanghai university of financial and economical press., 2010, pp.107-121 (In Chinese).