An Optimized Sensor Array Identifies All Natural Amino Acids

Benhua Wang, Jinsong Han, N. Maximilian Bojanowski, Markus Bender, Chao Ma, Kai Seehafer, Andreas Herrmann, Uwe H. F. Bunz*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

30 Citations (Scopus)
2 Downloads (Pure)

Abstract

Wet-chemical discrimination of amino acids is still a challenge due to their structural similarity. Here, an optimized self-assembled eight-member sensor array is reported. The optimized sensor array stems from the combination of elements of different tongues, containing poly(para-phenyleneethynylene)s (PPE) and a supercharged green fluorescent protein (GFP) variant. The responsivity of the sensor dyes (PPEs and GFP) is enhanced in elements that contain adjuvants, such as metal salts but also cucurbit[7]uril (CB[7]) and acridine orange; a suitable and robust eight element array discriminates all of the 20 natural amino acids in water at 25 mM concentration with 100% accuracy. The results group well to the amino acid type, i.e., hydrophobic, polar, and aromatic ones.

Original languageEnglish
Pages (from-to)1562-1568
Number of pages13
JournalACS Sensors
Volume3
Issue number8
DOIs
Publication statusPublished - Aug-2018

Keywords

  • sensor array
  • amino acid
  • poly(para-phenyleneethynylene)s
  • cucurbiturils
  • acridine orange
  • green fluorescent protein
  • CONJUGATED POLYMERS
  • FLUORESCENT
  • RECOGNITION
  • COMPLEXES
  • PROTEINS
  • DISCRIMINATION
  • WATER
  • NOSE

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