Lowry method for protein quantification: Principles, protocols, and applications in biochemical analysis

Authors

Keshawanand Tripathi
Department of Biotechnology, Invertis University, Bareilly, Uttar Pradesh, India
Yashdeep Srivastava
Department of Biotechnology, Invertis University, Bareilly, Uttar Pradesh, India
Santosh Kumar Mishra
Department of Life Science, Sharda School of Bioscience and Technology, Sharda University, Greater Noida, U.P, India
Narendra Kumar
School of Biotechnology and Bioengineering, Institute of Advanced Research, Gandhinagar, Gujarat, India

Synopsis

The Lowry method, developed by Oliver H. Lowry and colleagues in 1951, is a classic and widely utilized technique for the quantification of protein concentration in biological samples. This assay is based on the principle of colorimetric detection of protein-bound copper ions resulting from the reduction of Folin-Ciocalteu reagent under alkaline conditions (Lowry et al., 1951). The assay offers high sensitivity and a broad dynamic range, making it suitable for both routine laboratory analyses and research applications (Kruger). By measuring the absorbance of the resulting chromogenic complex at 750 nm, the concentration of proteins in samples can be accurately determined (Hartree, 1972; Tripathi et al., 2013 a,b). Despite its effectiveness, the Lowry method requires meticulous attention to detail in sample preparation and handling due to its sensitivity to interfering substances. Overall, the Lowry method remains a cornerstone in protein quantification, providing researchers with a reliable and versatile tool for protein analysis in diverse biological contexts (Wilson, and Walker, 2010; Kruger 2009).

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Published

13 April 2025

How to Cite

Tripathi, K. ., Srivastava, Y. ., Mishra, S. K. ., & Kumar, N. . (2025). Lowry method for protein quantification: Principles, protocols, and applications in biochemical analysis. In K. . Tripathi, Y. . Srivastava, & N. . Kumar (Eds.), Biotechnology Lab Techniques: Culture Media, Microscopy, and Microbial Analysis (pp. 162-164). Deep Science Publishing. https://doi.org/10.70593/978-93-49307-52-0_33