QSPR studies on refractive indices of structurally heterogeneous polymers
We developed a predictive Quantitative Structure-Property Relationship (QSPR) for the refractive indices of 234 structurally diverse polymers. The model involves a single molecular descriptor and a conformation-independent approach. The most appropriate polymer structure representation was investiga...
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Elsevier
2015
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| 003 | AR-BaUEN | ||
| 005 | 20230518204358.0 | ||
| 008 | 190411s2015 xx ||||fo|||| 00| 0 eng|d | ||
| 024 | 7 | |2 scopus |a 2-s2.0-84912082658 | |
| 024 | 7 | |2 cas |a polyethylene, 9002-88-4; polysulfone, 25135-51-7; polyvinyl alcohol, 37380-95-3, 9002-89-5 | |
| 040 | |a Scopus |b spa |c AR-BaUEN |d AR-BaUEN | ||
| 030 | |a CILSE | ||
| 100 | 1 | |a Duchowicz, P.R. | |
| 245 | 1 | 0 | |a QSPR studies on refractive indices of structurally heterogeneous polymers |
| 260 | |b Elsevier |c 2015 | ||
| 270 | 1 | 0 | |m Fioressi, S.E.; Departamento de Química, Facultad de Ciencias Exactas y Naturales, Universidad de Belgrano, Villanueva 1324, Argentina |
| 506 | |2 openaire |e Política editorial | ||
| 504 | |a Knoll, W., Interfaces and thin films as seen by bound electromagnetic waves (1998) Ann. Rev. Phys. Chem., 49, pp. 569-638 | ||
| 504 | |a Samuels, R.J., Application of refractive index measurements to polymer analysis (1981) J. Appl. Polym. Sci., 26, pp. 1383-1412 | ||
| 504 | |a Hu, R., Lam, J.W.Y., Tang, B.Z., Recent progress in the development of new acetylenic polymers (2013) Macromol. Chem. Phys., 214, pp. 175-187 | ||
| 504 | |a Schraub, M., Soll, S., Hampp, N., High refractive index coumarin-based photorefractive polysiloxanes (2013) Eur. Polym. J., 49, pp. 1714-1721 | ||
| 504 | |a Sydlik, S.A., Chen, Z., Swager, T.M., Triptycene polyimides: soluble polymers with high thermal stability and low refractive indices (2011) Macromolecules, 44, pp. 976-980 | ||
| 504 | |a van Krevelen, D.W., te Nijenhuis, K., (2009) Properties of Polymers: Their Correlation with Chemical Structure; Their Numerical Estimation and Prediction from Additive Group Contributions, , Elsevier, New York | ||
| 504 | |a Hansch, C., Leo, A., Exploring QSAR (1995) Fundamentals and Applications in Chemistry and Biology, , American Chemical Society, Washington, D. C | ||
| 504 | |a Kubinyi, H., (2008) QSAR: Hansch Analysis and Related Approaches, , Wiley-Interscience, New York | ||
| 504 | |a (2010) Recent Advances in QSAR Studies: Methods and Applications, , Springer Science&Business Media B.V., Netherlands, T. Puzyn, J. Leszczynski, M.T.D. Cronin (Eds.) | ||
| 504 | |a Katritzky, A.R., Goordeva, E.V., Traditional topological indexes vs electronic, geometrical, and combined molecular descriptors in QSAR/QSPR research (1993) J. Chem. Inf. Comput. Sci., 33, pp. 835-857 | ||
| 504 | |a Diudea, M.V.E., (2001) QSPR/QSAR Studies by Molecular Descriptors, , Nova Science Publishers, New York | ||
| 504 | |a Todeschini, R., Consonni, V., (2009) Molecular Descriptors for Chemoinformatics (Methods and Principles in Medicinal Chemistry), , Wiley-VCH, Weinheim | ||
| 504 | |a Golbraikh, A., Tropsha, A., Beware of q 2! (2002) J. Mol. Graphics Modell., 20, pp. 269-276 | ||
| 504 | |a Hawkins, D.M., Basak, S.C., Mills, D.J., Assessing model fit by cross-validation (2003) Chem. Inf. Model., 43, pp. 579-586 | ||
| 504 | |a Putz, M.V., Putz, A.-M., Lazea, M., Ienciu, L., Chiriac, A., Quantum-SAR extension of the spectral-SAR algorithm. Application to polyphenolic anticancer bioactivity (2009) Int. J. Mol. Sci., 10, pp. 1193-1214 | ||
| 504 | |a Putz, M.V., Ionascu, C., Putz, A.-M., Ostafe, V., Alert-QSAR. Implications for electrophilic theory of chemical carcinogenesis (2011) Int. J. Mol. Sci., 12, pp. 5098-5134 | ||
| 504 | |a Bicerano, J., (1996) Prediction of Polymer Properties, , Marcel Dekker Inc., New York | ||
| 504 | |a García-Domenech, R., de Julián-Ortiz, J.V., Prediction of indices of refraction and glass transition temperatures of linear polymers by using graph theoretical indices (2002) J. Phys. Chem. B, 106, pp. 1501-1507 | ||
| 504 | |a Hawkins, D.M., The problem of overfitting (2004) J. Chem. Inf. Comput. Sci., 44, pp. 1-12 | ||
| 504 | |a Katritzky, A.A., Sild, S., Karelson, M., Correlation and prediction of the refractive indices of polymers by QSPR (1998) J. Chem. Inf. Comput. Sci., 38, pp. 1171-1176 | ||
| 504 | |a Xu, J., Chen, B., Zhang, Q.J., Guo, B., Prediction of refractive indices of linear polymers by a four-descriptor QSPR model (2004) Polymer, 45, pp. 8651-8659 | ||
| 504 | |a Astray, G., Cid, A., Moldes, O., Ferreiro-Lage, J.A., Gálvez, J.F., Mejuto, J.C., Prediction of refractive index of polymers using artificial neural networks (2010) J. Chem. Eng. Data, 55, pp. 5388-5393 | ||
| 504 | |a Duchowicz, P.R., Comelli, N.C., Ortiz, E.V., Castro, E.A., QSAR study for carcinogenicity in a large set of organic compounds (2012) Curr. Drug Saf., 7, pp. 282-288 | ||
| 504 | |a Talevi, A., Bellera, C.L., Ianni, M.D., Duchowicz, P.R., Bruno-Blanch, L.E., Castro, E.A., An integrated drug development approach applying topological descriptors (2012) Curr. Comput. Aided Drug Des., 8, pp. 172-181 | ||
| 504 | |a Toropov, A.A., Toropova, A.P., Benfenati, E., Gini, G., OCWLGI descriptors: theory and praxis (2013) Curr. Comput. Aided Drug Des., 9, pp. 226-232 | ||
| 504 | |a Mullen, L.M.A., Duchowicz, P.R., Castro, E.A., QSAR treatment on a new class of triphenylmethyl-containing compounds as potent anticancer agents (2011) Chemom. Intell. Lab. Syst., 107, pp. 269-275 | ||
| 504 | |a García, J., Duchowicz, P.R., Rozas, M.F., Caram, J.A., Mirífico, M.V., Fernández, F.M., Castro, E.A., A comparative QSAR on 1, 2, 5-thiadiazolidin-3-one 1, 1-dioxide compounds as selective inhibitors of human serine proteinases (2011) J. Mol. Graphics Modell., 31, pp. 10-19 | ||
| 504 | |a Ibezim, E., Duchowicz, P.R., Ortiz, E.V., Castro, E.A., QSAR on aryl-piperazine derivatives with activity on malaria (2012) Chemom. Intell. Lab. Syst., 110, pp. 81-88 | ||
| 504 | |a Toropov, A.A., Toropova, A.P., Prediction of heteroaromatic amine mutagenicity by means of correlation weighting of atomic orbital graphs of local invariants (2001) J. Mol. Struct. Theochem, 538, pp. 287-293 | ||
| 504 | |a Toropov, A.A., Nesterov, I.V., Nabiev, O.M., QSAR modeling of dihydrofolate reductase inhibitory activity by correlation weighting of nearest neighboring codes (2003) J. Mol. Struct. Theochem, 622, pp. 269-273 | ||
| 504 | |a Toropov, A.A., Leszczynska, D., Leszczynski, J., Predicting water solubility and octanol water partition coefficient for carbon nanotubes based on the chiral vector (2007) J. Comput. Biol. Chem., 31, pp. 127-128 | ||
| 504 | |a Toropov, A.A., Leszczynska, D., Leszczynski, J., Predicting thermal conductivity of nanomaterials by correlation weighting technological attributes codes (2007) Mater. Lett., 61, pp. 4777-4780 | ||
| 504 | |a Toropov, A.A., Benfenati, E., Additive, E., SMILES-based optimal descriptors in QSAR modelling bee toxicity: using rare SMILES attributes to define the applicability domain (2008) Bioorg. Med. Chem., 26, pp. 4801-4809 | ||
| 504 | |a Toropov, A.A., Toropova, A.P., Benfenati, E., Gini, G., Puzyn, T., Leszczynska, D., Leszczynski, J., Novel application of the CORAL software to model cytotoxicity of metal oxide nanoparticles to bacteria Escherichia coli (2012) Chemosphere, 89, pp. 1098-1102 | ||
| 504 | |a Toropov, A.A., Toropova, A.P., Martyanov, S.E., Benfenati, E., Gini, G., Leszczynska, D., Leszczynski, J., Comparison of SMILES and molecular graphs as the representation of the molecular structure for QSAR analysis for mutagenic potential of polyaromatic amines (2011) Chemom. Intell. Lab. Syst., 109, pp. 94-100 | ||
| 504 | |a Toropova, A.P., Toropov, A.A., Martyanov, S.E., Benfenati, E., Gini, G., Leszczynska, D., Leszczynski, J., CORAL: QSAR modeling of toxicity of organic chemicals towards Daphnia magna (2012) Chemom. Intell. Lab. Syst., 110, pp. 177-181 | ||
| 504 | |a Brandrup, J., Immergut, E.H., Grulke, E.A., (1975) Polymer Handbook, , John Wiley and Sons | ||
| 504 | |a http://www.insilico.eu/CORAL, (Accessed: 04-Aug-2014); Milano chemometrics and QSAR research group. VCCLAB, virtual computational chemistry laboratory, , http://michem.disat.unimib.it/chm, (Accessed: 24-July-2014) | ||
| 504 | |a Katritzky group, , http://www.ark.chem.ufl.edu/, (Accessed: 24-July-2014) | ||
| 504 | |a Rücker, C., Rücker, G., Meringer, M., Y-Randomization and its variants in QSPR/QSAR (2007) J. Chem. Inf. Model., 47, pp. 2345-2357 | ||
| 504 | |a Gramatica, P., Principles of QSAR models validation: internal and external (2007) QSAR Comb. Sci., 26, pp. 694-701 | ||
| 504 | |a Eriksson, L., Jaworska, J., Worth, A.P., Cronin, M.T., McDowell, R.M., Gramatica, P., Methods for reliability and uncertainty assessment and for applicability evaluations of classification-and regression-based QSARs (2003) Environ. Health Perspect., 111, pp. 1361-1375 | ||
| 504 | |a Mercader, A.G., Duchowicz, P.R., Fernández, F.M., Castro, E.A., Advances in the replacement and enhanced replacement method in QSAR and QSPR theories (2011) J. Chem. Inf. Model., 51, pp. 1575-1581 | ||
| 504 | |a Roy, K., On some aspects of validation of predictive quantitative structure-activity relationship models (2007) Expert Opin. Drug Discovery, 2, pp. 1567-1577 | ||
| 520 | 3 | |a We developed a predictive Quantitative Structure-Property Relationship (QSPR) for the refractive indices of 234 structurally diverse polymers. The model involves a single molecular descriptor and a conformation-independent approach. The most appropriate polymer structure representation was investigated by considering 1-5 monomeric repeating units. The established equations were validated and tested through various well-known techniques, such as the use of an external test set of compounds, the Cross-Validation method, Y-Randomization and Applicability Domain, and finally a comparison was also performed to published results from the li terature. The developed QSPR could be useful for assisting the development of new polymeric materials. © 2014 Elsevier B.V. |l eng | |
| 536 | |a Detalles de la financiación: Ministerio de Ciencia, Tecnología e Innovación Productiva | ||
| 536 | |a Detalles de la financiación: National Council for Scientific Research | ||
| 536 | |a Detalles de la financiación: European Commission, 309837 | ||
| 536 | |a Detalles de la financiación: Consejo Nacional de Investigaciones Científicas y Técnicas, PIP11220100100151 | ||
| 536 | |a Detalles de la financiación: PRD acknowledges the financial support from the National Research Council of Argentina (CONICET) PIP11220100100151 project and to Ministerio de Ciencia, Tecnología e Innovación Productiva for the electronic library facilities. APT and AAT acknowledge support from EC project NANOPUZZLES (Project Reference: 309837). PRD, SEF and DEB are members of the scientific researcher career of CONICET. Appendix A | ||
| 593 | |a Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas INIFTA, (CCT La Plata-CONICET UNLP), Diag. 113 y 64, Sucursal 4, C.C. 16, La Plata, 1900, Argentina | ||
| 593 | |a Departamento de Química, Facultad de Ciencias Exactas y Naturales, Universidad de Belgrano, Villanueva 1324, Buenos Aires, CP 1426, Argentina | ||
| 593 | |a Cátedra de Química Teórica y Computacional, Departamento de Química, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, Calle 115 y 47, La Plata, 1900, Argentina | ||
| 593 | |a IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19, Milano, 20156, Italy | ||
| 690 | 1 | 0 | |a CORAL SOFTWARE |
| 690 | 1 | 0 | |a GRAPH THEORY |
| 690 | 1 | 0 | |a MONTE CARLO METHOD |
| 690 | 1 | 0 | |a POLYMER |
| 690 | 1 | 0 | |a QSPR THEORY |
| 690 | 1 | 0 | |a REFRACTIVE INDEX |
| 690 | 1 | 0 | |a POLY(1 METHYLETHYLENE) |
| 690 | 1 | 0 | |a POLY(1,1 DICHLOROETHYLENE) |
| 690 | 1 | 0 | |a POLY(2,3 DIBROMOPROPYL METHACRYLATE) |
| 690 | 1 | 0 | |a POLY(ETHYLMETHYLENE) |
| 690 | 1 | 0 | |a POLY(PARA XYLYLENE) |
| 690 | 1 | 0 | |a POLY(PENTABROMOPHENYL METHACRYLATE) |
| 690 | 1 | 0 | |a POLY(PENTADECAFLUOROOCTYL ACRYLATE) |
| 690 | 1 | 0 | |a POLYETHYLENE |
| 690 | 1 | 0 | |a POLYMER |
| 690 | 1 | 0 | |a POLYSULFONE |
| 690 | 1 | 0 | |a POLYVINYL ALCOHOL |
| 690 | 1 | 0 | |a UNCLASSIFIED DRUG |
| 690 | 1 | 0 | |a ARTICLE |
| 690 | 1 | 0 | |a CONFORMATION |
| 690 | 1 | 0 | |a CONTROLLED STUDY |
| 690 | 1 | 0 | |a MATHEMATICAL MODEL |
| 690 | 1 | 0 | |a PREDICTIVE VALUE |
| 690 | 1 | 0 | |a QUANTITATIVE STRUCTURE PROPERTY RELATION |
| 690 | 1 | 0 | |a REFRACTION INDEX |
| 690 | 1 | 0 | |a STRUCTURE ANALYSIS |
| 690 | 1 | 0 | |a VALIDATION STUDY |
| 700 | 1 | |a Fioressi, S.E. | |
| 700 | 1 | |a Bacelo, D.E. | |
| 700 | 1 | |a Saavedra, L.M. | |
| 700 | 1 | |a Toropova, A.P. | |
| 700 | 1 | |a Toropov, A.A. | |
| 773 | 0 | |d Elsevier, 2015 |g v. 140 |h pp. 86-91 |p Chemometr. Intelligent Lab. Syst. |x 01697439 |w (AR-BaUEN)CENRE-4169 |t Chemometrics and Intelligent Laboratory Systems | |
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