Integrating statistical and experimental protocols to model and design novel Gemini surfactants with promising critical micelle concentration and low environmental risk

Chemosphere

Volumn 84, Issue 11, 2011, Pages 1608-1616

  Guo, Chunwei ^a   Zhou, Peng ^a   Shao, Jin ^b   Yang, Xinchang ^b   Shang, Zhicai ^a  

^a ZHEJIANG UNIVERSITY   (China)

^b Sino light Chemicals Co Ltd   (China)

Author keywords

Computer aided surfactant design; Critical micelle concentration; Environmental risk; Gemini surfactant; Machine learning

Indexed keywords

COMPUTER AIDED INSTRUCTION; CRITICAL MICELLE CONCENTRATION; GENETIC ALGORITHMS; HEURISTIC METHODS; LEARNING SYSTEMS; MASS SPECTROMETRY; MEAN SQUARE ERROR; MICELLES;

COEFFICIENT OF DETERMINATION; COMPUTER AIDED; CRITICAL MICELLE CONCENTRATION (CMC); ELECTROSTATIC DESCRIPTORS; ENVIRONMENTAL RISKS; GEMINI SURFACTANT; ROOT-MEAN-SQUARE ERROR OF PREDICTIONS; VARIABLE SELECTION METHODS;

RISK ASSESSMENT;

QUATERNARY AMMONIUM DERIVATIVE; SURFACTANT;

COMPUTER AIDED DESIGN; ENVIRONMENTAL RISK; EXPERIMENTAL STUDY; GENETIC ALGORITHM; HEURISTICS; PARADIGM SHIFT; SURFACTANT;

ARTICLE; CALIBRATION; CARBON NUCLEAR MAGNETIC RESONANCE; CONTROLLED STUDY; CRITICAL MICELLE CONCENTRATION; ENVIRONMENT; EXPERIMENTAL MODEL; GENETIC ALGORITHM; MASS SPECTROMETRY; MEMBRANE STRUCTURE; METHODOLOGY; PARTIAL LEAST SQUARES REGRESSION; PROTON NUCLEAR MAGNETIC RESONANCE; STATIC ELECTRICITY; STATISTICAL MODEL; SUPPORT VECTOR MACHINE;

EID: 80051666672     PISSN: 00456535     EISSN: 18791298     Source Type: Journal    
DOI: 10.1016/j.chemosphere.2011.05.031     Document Type: Article

References (46)

1. Absalana G., Hemmateenejad B., Soleimani M., Akhond M., Miri R. Quantitative structure-micellization relationship study of Gemini surfactants using genetic-PLS and genetic-MLR. QSAR Comb. Sci. 2004, 23:416-425.
2. Breiman L. Random forest. Mach. Learn. 2001, 45:5-32.
3. Bunton C.A., Robinson L. Catalysis of nucleophilic substitutions by micelles of dicationic detergent. J. Org. Chem. 1971, 36:2346-2352.
4. Burrows H.D., Tapia M.J., Silva C.L., Pais A.C.C. Interplay of electrostatic and hydrophobic effects with binding of cationic Gemini. J. Phys. Chem. B 2007, 111:4401-4410.
5. Cortes C., Vapnik V. Support vector networks. Mach. Learn. 1995, 20:273-293.
6. Danino D., Talmon Y., Zana R. Alkanediyl-alpha, omega-Bis (dimethylalkylammonium bromide) surfactants (dimeric Surfactants). 5 Aggregation and microstructure in aqueous solutions. Langmuir 1995, 11:1448-1456.
7. Din K.U., Koya P.A. Micellar properties and related thermodynamic parameters of the 14-6-14, 2Br gemini surfactant in water organic solvent mixed media. J. Chem. Eng. Data. 2010, 55:1921-1929.
8. Dreja M., Hintzen W.P., Mays H., Tieke B. Cationic gemini surfactants with oligo (oxyethylene) spacer groups and their use in the olymerization of styrene in ternary microemulsion. Langmuir 1999, 15:391-399.
9. Golbraikh A., Tropsha A. Beware of q2! J. Mol. Graphics. Modell. 2002, 20:269-276.
10. Hagmann M. Computers aid vaccine design. Science 2000, 290:80-82.
11. Hait S.K., Moulik S.P. Gemini surfactants: a distinct class of self-assembling molecules. Curr. Sci. 2002, 82:1101-1111.
12. Hemmateenejad B., Miri B., Akhona M., Shamsipur M. QSAR study of the calcium channel antagonist activity of some recently synthesized dihydropyridine derivatives. An application of genetic algorithm for variable selection in MLR and PLS methods. Chemom. Intell. Lab. Syst. 2002, 64:91-99.
13. Hu J.W., Zhang X.Y., Wang Z.W. A review on progress in QSPR studies for surfactants. Int. J. Mol. Sci. 2010, 11:1020-1047.
14. Huibers P.D.T., Jacobs P.T. The effect of polar head charge delocalization on micellar aggregation numbers of decylpyridinium salts, revisited. J. Colloid Interface Sci. 1998, 206:342-344.
15. Huibers P.D.T., Lobanov V.S., Katritzky A.R., Shah D.O., Karelson M. Prediction of critical micelle concentration using a quantitative structure-property relationship approach. 1. Nonionic surfactants. Langmuir 1996, 12:1462-1470.
16. Huibers P.D.T., Lobanov V.S., Katritzky A.R., Shah D.O., Karelson M. Predicting surfactant cloud point from molecular structure. J. Colloid Interface Sci. 1997, 187:113-120.
17. Joshi V.Y., Kadam M.M., Sawant M.R. Comparison of QSAR and QSPR based aquatic toxicity for mixed surfactants. J. Surfactants Deterg. 2007, 10:25-34.
18. Karaborni S., Esselink K., Hilbers P.A.J., Smit B., Karthauser J., van Os N.M., Zana R. Simulating the self-assembly of Gemini (dimeric) surfactants. Science 1994, 266:254-256.
19. Kardanpour Z., Hemmateenejad B., Khayamian T. Wavelet neural network-based QSPR for prediction of critical micelle concentration of Gemini surfactants. Anal. Chim. Acta. 2005, 531:285-291.
20. Katritzky, A.R., Lobanov, V.S., Karelson, M., 2002. CODESSA Vers. 2.7, Reference Manual, University of Florida, Gainesville, FL.
21. Katritzky A.R., Pacureanu L., Dobchev D., Karelson M. QSPR study of critical micelle concentration of anionic surfactants using computational molecular descriptors. J. Chem. Inf. Model. 2007, 47:782-793.
22. Katritzky A.R., Pacureanu L.M., Slavov S.H., Dobchev D.A., Karelson M. QSPR study of critical micelle concentrations of nonionic surfactants. Ind. Eng. Chem. Res. 2008, 47:9687-9695.
23. Katritzky A.R., Pacureanu L.M., Slavov S.H., Dobchev D.A., Shah D.O., Karelson M. QSPR study of the first and second critical micelle concentrations of cationic surfactants. Comput. Chem. Eng. 2009, 33:321-332.
24. Kumar A., Alami E., Holmberg K., Seredyuk V., Menger F.M. Branched zwitterionic gemini surfactants micellization and interaction with ionic surfactants. Colloids Surf A: Physicochem. Eng. Aspects 2003, 228:197-207.
25. Menger F.M., Keiper J.S. Gemini surfactants. Angew. Chem. Int. Ed. 2000, 39:1906-1920.
26. Menger F.M., Littau C.A. Gemini surfactants: synthesis and properties. J. Am. Chem. Soc. 1991, 113:1451-1452.
27. Obrezanova O., Csanyi G., Gola J.M.R., Segall M.D. Gaussian processes: a method for automatic QSAR modeling of ADME properties. J. Chem. Inf. Model. 2007, 47:1847-1857.
28. Ooms F. Molecular modeling and computer aided drug design. Examples of their applications in medicinal chemistry. Curr. Med. Chem. 2000, 7:141-158.
29. Rasmussen C.E., Williams C.K.I. Gaussian Processes for Machine Learning 2006, The MIT Press, Massachusetts.
30. Ravey J.C., Gherbi A., Stebe M. Comparative study of fluorinated and hydrogenated nonionic surfactants I. Surface activity properties and critical concentrations. Prog. Colloid Polym. Sci. 1988, 76:234-241.
31. Roberts D.W., Costello J. QSAR and mechanism of action for aquatic toxicity of cationic surfactants. QSAR Comb. Sci. 2003, 22:220-225.
32. Rosen M.J. The relationship of structure to properties in surfactants IV. Effectiveness in surface or interfacial tension reduction. J. Colloid Interface Sci. 1976, 56:320-327.
33. Rosen M.J. Surfactants and Interfacial Phenomena 2004, Wiley, Hoboken, NJ. third ed.
34. Rosen M.J., Liu L. Surface activity and premicellar aggregation of some novel diquaternary Gemini surfactants. J. Am. Oil Chem. Soc. 1996, 73:885-890.
35. Rosena M.J., Fei L., Zhu Y.P., Morrall S.W. The relationship of the environmental effect of surfactants to their interfacial properties. J. Surfactants Deterg. 1999, 2:343-347.
36. Sekhon B.S. Gemini (dimeric) surfactants. Resonance 2004, 9:42-49.
37. Selvam P., Peguin R.P.S., Chokshi U., da Rocha S.R.P. Surfactant design for the 1,1,1,2-tetrafluoroethane water interface. ab initio calculations and in situ high-pressure tensiometry. Langmuir 2006, 22:8675-8683.
38. Stanton D.T., Jurs P.C. Development and use of charged partial surface area structural descriptors in computer-assisted quantitative structure-property relationship studies. Anal. Chem. 1990, 62:2323-2329.
39. Stevanovic, J.S., Mosorinac, T., Krstic, S.B., Beric, R.D., 2007. Computer aided operation and design of the cationic surfactants production. In: 17th Eur. Sym. Comput. Aided Process Eng. pp. 1-6.
40. Suykens J.A.K., Vandewalle J. Least squares support vector machine classifiers. Neural Process. Lett. 1999, 9:293-300.
41. Wold S., Sjostrom M., Eriksson L. PLS-regression: a basic tool of chemometrics. Chemom. Intell. Lab. Syst. 2001, 58:109-130.
42. Zana R., Benrraou M., Rueff R. Alkanediyl-α, ω-bis(dimethylalkyl- ammonium bromide) surfactants. 1 Effect of the spacer chain length on the critical micelle concentration and micelle ionization degree. Langmuir 1991, 7:1072-1075.
43. Zhou P., Tian F., Li Z. A structure-based, quantitative structure-activity relationship approach for predicting HLA-A*0201-restricted cytotoxic T lymphocyte epitopes. Chem. Biol. Drug Des. 2007, 69:56-67.
44. Zhou L.M., Jiang X.H., Li Y.T., Chen Z., Hu X.Q. Synthesis and properties of a novel class of Gemini pyridinium surfactants. Langmuir 2007, 23:11404-11408.
45. Zhou P., Tian F., Lv F., Shang Z. Comprehensive comparison of eight statistical modelling methods used in quantitative structure-retention relationship studies for liquid chromatographic retention times of peptides generated by protease digestion of the Escherichia coli proteome. J. Chromatogr. A 2009, 1216:3107-3116.
46. Zhou P., Chen X., Wu Y., Shang Z. Gaussian process: an alternative approach for QSAM modeling of peptides. Amino Acids 2010, 38:199-212.