Intelligent Computation for Optimal Fabrication Condition of a Protein Chip with Ni-Co Alloy-Coated Surface.

Abstract

Based on the principle of immobilized metal affinity chromatography (IMAC), it has been found that a Ni-Co alloy-coated protein chip is able to immobilize functional proteins with a His-tag attached. In this study, an intelligent computational approach was developed to promote the performance and repeatability of a Ni-Co alloy-coated protein chip. This approach was launched out of L18 experiments. Based on the experimental data, the fabrication process model of a Ni-Co protein chip was established by using an artificial neural network, and then an optimal fabrication condition was obtained using the Taguchi genetic algorithm. The result was validated experimentally and compared with a nitrocellulose chip. Consequentially, experimental outcomes revealed that the Ni-Co alloy-coated chip, fabricated using the proposed approach, had the best performance and repeatability compared with the Ni-Co chips of an L18 orthogonal array design and the nitrocellulose chip. Moreover, the low fluorescent background of the chip surface gives a more precise fluorescent detection. Based on a small quantity of experiments, this proposed intelligent computation approach can significantly reduce the experimental cost and improve the product's quality.