Quantitative detection of acyclovir by surface enhanced Raman spectroscopy using a portable Raman spectrometer coupled with multivariate data analysis
Graphical abstract
Introduction
Acyclovir (ACV), a typical nucleoside antiviral agent derived from guanosine, due to its remarkable therapeutic effect, is generally chosen as the first-line clinical treatment against herpes simplex virus, hepatitis B virus, varicella zoster virus [1]. The drug has its potential in the prophylaxis of cytomegalovirus infections in immunologically compromised patients [2]. Accordingly, tens of millions of patients worldwide have received these antivirals.
Unfortunately, neither the parenteral nor the oral administration of the currently available formulations of ACV is able to result in suitable concentrations of the agent reaching at target sites therefore require the administration of high doses, up to 1.2 g/day [3]. This administration will result in several adverse events and systemic toxicity such as nephrotoxicity. The side effect caused by improper dosage or overdose of ACV is getting more and more attention. Therefore, methods for the quantitative detection of ACV are in great need.
In view of the prominence of ACV in clinical applications, various methods have been developed to determine ACV, including high performance liquid chromatography [4] spectrophotometry [5] and liquid chromatography-tandem mass spectrometry [6]. Although chromatography-based analytical methods have high separation power, sensitivity and/or selectivity, those approaches have several limitations which include lengthy and tedious sample preparation procedures, cumbersome analysis process, difficulties in real-time monitoring and expensive equipment. The colorimetric analysis method is faster, but is more likely to destroy the sample [7]. In the field of spectroscopic methods, our research group used near-infrared spectroscopy coupled with multivariate data analysis methods such as PLS regression and ANN in quantitation and fast measurement of blood glucose in vivo [8,9]. Another possible method is Raman detection which has been used widely to investigate the structural variations in macromolecules [10]. Although it performed outstandingly in providing “fingerprint-like” details about numerous components in a multifaceted system [11], due to only one photon out of one million photons undergoes Raman scattering, the standard Raman scattering signal is too weak to reach the ultra-low concentration of detection. Hence, surface-enhanced Raman spectroscopy (SERS) technique is introduced as an efficacious method to analyze ACV selectively and sensitively.
SERS can maximally enhance the Raman signal of the analyte, even the detailed vibration modes of molecules adsorbed on the noble metal surface can be detected, which greatly extends the application of Raman spectroscopy [[12], [13], [14]]. There are several monographs and reviews that introduced the mechanism of SERS, two principles have been widely recognized so far —— electromagnetic (EM) enhancement and chemical enhancement (CE) [15,16]. In the abovementioned work, metal colloids, in particular Ag and Au, were most commonly used as substrates in SERS. At present, SERS has been widely pursued in various fields such as: explosive detection [17], pesticide and veterinary drug residues in foods [18], additives [19], and drug metabolites in biological samples [20].
Due to the complex nature of SERS phenomena, there is no universal substrate that can be applied for detection of all different chemicals. In this study, AgNPs (Ag nanoparticles) and AuNPs (Au nanoparticles) which prepared by different chemical reduction were investigated. The temporal stability, uniformity and reproducibility of the substrate were evaluated. Secondly, density functional theory (DFT) calculations are engaged to help with the ACV assignments of vibrational modes and to complement the study of ACV adsorption onto nanoparticle surface. Furthermore, SERS coupling with PLS and ANN was applied to build forecast model and explore the feasibility of predicting trace ACV. The results could be considered as a basis for further development of rapid and highly sensitive SERS imaging for non-destructive investigation of drug metabolites in biological fluids.
Section snippets
Reagents and chemicals
Gold(III) chloride hydrate (99.999%, HAuCl4 ·xH2O, FW 339.79), silver nitrate (99.9999%, AgNO3, FW 169.87), sodium hydroxide (99.99%, NaOH, FW 40.00), Sodium citrate dihydrate (≥99%, Na3C6H5O7·2H2O, FW 294.11), hydroxylamine hydrochloride (≥99%, NH2OH·HCl, FW 69.49) were obtained from Sigma-Aldrich Chemical Reagent Co., Ltd. (Shanghai, China). Acyclovir (98%, ACV, FW 225.21) was purchased from Aladdin Chemistry Co., Ltd. (Shanghai, China). All glassware was rigorously cleaned before use by
Characterization of AgNPs and AuNPs
SERS active substrates with uniform surfaces prepared by deposition of similar size and shape metal nanoparticles could circumvent the phenomenon which poor reproducibility of Raman signal. Therefore, UV–vis spectroscopy was used to characterize the morphology of the produced colloids. The absorption maximum of the measured UV–vis spectrum of the colloidal solution provides information on the average particle size, whereas its full width at half-maximum (FWHM) can be used to estimate particle
Conclusion
Because of the wide use of ACV, possible adverse effect related to the human health should be attracted highly attention. In this study, a cost efficient portable Raman spectrometer and SERS spectroscopy are firstly proposed for the identification and quantification of ACV. Different prepared ways of Ag/Au nanoparticles had been investigated and the good reproducibility, uniformity and high temporal stability of the substrate indicate their potential for other routine analysis. Quantification
Conflict of interest
The authors declare that they have no conflict of interest.
Acknowledgements
The authors graciously acknowledge the financial support provided by the National Sciences Foundation of PR China (No.81373969) and the University Key Research Projects of Henan Province (No. 17A360026).
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