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Surface-enhanced Raman Spectroscopy (SERS): Protein Application

Raman Spectroscopy

  1. Lei Chen,
  2. Linjun Cai,
  3. Weidong Ruan,
  4. Bing Zhao

Published Online: 9 JAN 2014

DOI: 10.1002/9780470027318.a9277

Encyclopedia of Analytical Chemistry

Encyclopedia of Analytical Chemistry

How to Cite

Chen, L., Cai, L., Ruan, W. and Zhao, B. 2014. Surface-enhanced Raman Spectroscopy (SERS): Protein Application. Encyclopedia of Analytical Chemistry. 1–23.

Author Information

  1. Jilin University, Changchun, China

Publication History

  1. Published Online: 9 JAN 2014


This article outlines the recent progress in surface-enhanced Raman spectroscopy (SERS)-based biological applications, especially in the study of proteins. SERS is a specific Raman spectroscopic technique that provides enhanced Raman signals (several orders of magnitude greater than normal) for numerous Raman-active analyte molecules adsorbed onto rough metal surfaces. SERS is a sensitive, selective, and versatile technique, and it lends itself readily to fast data acquisition. Therefore, SERS has undergone rapid development because of numerous technical advances in both instrumentation and methods of data analysis and a vast proliferation and combination of basic techniques for its multiple biological applications. This article highlights several representative areas in biology where SERS could be employed. Some of the biological applications of SERS are more developed, whereas others are in their initial stages of development (in laboratories). This article discusses the recent developments in SERS-based quantitative analysis: (i) directly with different substrates (e.g. biomolecules on electrodes, colloidal particles, and periodic pattern structure and tip-based substrates) and (ii) indirectly with different types of sensors (e.g. immunogold-, enzymatic-, reagent-, and Raman-active nanomaterial-based sensors). Furthermore, SERS-based techniques are advantageous for obtaining valuable information on protein–protein, protein–ligand, and protein–drug recognitions via spectral differences among molecular bridges. SERS-based techniques show considerable promise for qualitative and/or quantitative analyses of biological systems.