Artificial neural networks for qualitative and quantitative analysis of target proteins with polymerized liposome vesicles

GOICOECHEA, HÉCTOR C; MARINA SANTOS,; SUAD NADI,; SANKU MALIK,; M HALDAR,; ANDRES CAMPIGLIA,

ANALYTICAL BIOCHEMISTRY

Elsevier

Año: 2007 vol. 361 p. 109 - 119

0003-2697

We investigate the feasibility to using the luminescence response of polymerized liposomes incorporating EDTA-Eu3+ for monitoring protein concentrations in aqueous media. Quantitative analysis is based on the linear relationship between the luminescence enhancement of the lanthanide ion and protein concentration. Excellent analytical figures of merit are presented for carbonic anhydrase, human serum albumin, g-globulin and thermolysin. Qualitative analysis is based on the luminescence lifetime of the liposome sensor. This parameter - which follows well-behaved single exponential decays and provides characteristic values for each one of the four studied proteins – demonstrates the selective potential for protein identification. Partial least squares and artificial neural networks are then compared towards the quantitative and qualitative analysis of human serum albumin and carbonic anhydrase in binary mixtures without previous separation at the concentration levels found in aqueous humor