Application of artificial neural networks for the determination of proteins with CPA-pI by rayleigh light scattering technique
Application of artificial neural networks for the determination of proteins with CPA-pI by rayleigh light scattering technique
Received 9 April 2005; revised 14 January 2006; accepted 3 February 2006. Available online 23 March 2006.
Lijun Donga, Xingguo Chen, a, and Zhide Hua
Journal of Luminescence
Volume 124, Issue 1 , May 2007
ScienceDirect
Copyright ? 2006 Elsevier B.V. All rights reserved.
aDepartment of Chemistry, Lanzhou University, Lanzhou 730000, PR China
Abstract
The determination of proteins with 2-(4-chloro-2-phosphonophenylazo)-7-(4-iodophenylazo)-1,8-dihydroxynaphthalene-3,6-disulfonic acid (CPA-pI) by Rayleigh light scattering (RLS) was studied in this paper. The weak RLS of CPA-pI and BSA can be enhanced greatly by the addition of Al3+ at the pH 5.6 and an enhanced RLS signal was produced at 365?385 nm. Based on the reaction of CPA-pI, Al3+ and proteins, a new quantitative determination method for proteins has been developed. The effect of three variables for the determination of proteins was optimized by means of artificial neural networks (ANNs) using extended delta-bar-delta (EDBD) algorithms with the optimal network structure of 3-5-1. This method is very sensitive (2.5?35.4 ?g/ml for bovine serum albumin (BSA)), rapid (<2 min), simple (one step) and tolerance of most interfering substances. Six samples of protein in human serum were determined and the maximum relative error is no more than 2% and the recovery is between 95% and 105%.
Keywords: Rayleigh light scattering; Artificial neural networks; Proteins; CPA-pI
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