Chiral gold nanorod vertical arrays for enantioselective chemiluminescence recognition of naproxen and mechanism revealing

Chirality recognition by monitoring electrochemiluminescence/chemiluminescence (CL) signals of probes altered by enantiomers is considered a promising method in the fields of pharmaceuticals and biotechnology. However, improving the sensitivity of chiral recognition and accurately elucidating its chiral recognition mechanism are still two major challenges. Herein, L-Cys-modified chiral Au nanorod (L-GNR) vertical arrays-enhanced CL sensing is proposed for improving the sensitivity of chiral naproxen recognition and accurately elucidating its chiral recognition mechanism. The resulting L-GNR vertical arrays exhibited a strong local electric field and improved electron transfer efficiency, thereby enhancing the CL signal of the luminol-H2O2 system. More importantly, such L-GNR vertical arrays exhibited markedly different CL intensities toward chiral drug R/S-naproxen (R/S-NPx) due to the different affinity between L-Cys and R/S-NPx, which was confirmed by molecular dynamics simulation. Thus, an ultrasensitive enantioselective recognition of R/S-NPx was achieved by the L-GNR vertical arrays exhibiting a CL signal for S-NPx that was approximately 2.5-fold higher than that of R-NPx, with a limit of detection as low as 0.14 pM for R-NPx and 0.097 pM for S-NPx, respectively. The mechanism of the stereospecific interaction between the naproxen enantiomers and the chiral GNR vertical arrays was investigated by scanning electrochemical microscopy (SECM). We found that the electron transfer rate of identification system determined strength of the CL signals. The electron transfer rate of L-GNR vertical arrays + R-NPx was faster than that of the L-GNR vertical arrays + S-NPx due to the weaker interaction between L-GNR vertical arrays and R-NPx compared to L-GNR vertical arrays and S-NPx. This study not only provides a novel strategy for the detection of enantiomers but also reveals the mechanism of enantioselective recognition through SECM.