alexa Zipf’s Law in Proteomics
ISSN: 0974-276X

Journal of Proteomics & Bioinformatics
Open Access

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Research Article

Zipf’s Law in Proteomics

Stanislav Naryzhny1,2*, Maria Maynskova1, Victor Zgoda1 and Аlexander Archakov1

1Orekhovich Institute of Biomedical Chemistry of Russian Academy of Medical Sciences, Moscow, 119121, Russia

2B.P. Konstantinov Petersburg Nuclear Physics Institute, National Research Center “Kurchatov Institute”, Gatchina, 188300, Russia

*Corresponding Author:
Dr. Stanislav Naryzhny
B.P. Konstantinov Petersburg Nuclear Physics Institute
National Research Center “Kurchatov Institute”
Orlova Roscha, Gatchina
Leningrad Region, 188300, Russia
Tel: 79111764453
Fax: (+7) 8137132303
E-mail: [email protected]

Received Date: February 17, 2017; Accepted Date: March 03, 2017; Published Date: March 29, 2017

Citation: Naryzhny S, Maynskova M, Zgoda V, Archakov А (2017) Zipf’s Law in Proteomics. J Proteomics Bioinform 10:79-84. doi: 10.4172/jpb.1000427

Copyright: © 2017 Naryzhny S, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.



Human cells contain many thousands of protein components, protein species/proteoforms, whose cooperation provides the complicated functional mechanisms of the cellular proteome. Though recent methods still do not allow us to obtain the whole picture of this cooperation, they at least provide an opportunity to develop a representation of the proteome size and quantitative distribution of protein species inside the proteome. Using 2DE analysis followed by both protein staining and ESI LC-MS/MS analysis, we performed an analysis of the quantitative distribution of different protein species in human cells. We have analyzed several human cancer cell lines (HepG2, glioblastoma, MCF7) along with the primary liver cells from tissue samples and found that the dependence of the number of protein species on their abundance is described by Zipf’s law: y=ax-1 (1) Where y stands for the number of protein species (N), x stands for the abundance. In the case where the abundance is expressed as %V, and a=14, the final equation is: N=14/%V (2) It is very likely that this type of distribution reflects the fundamental functional organization of the human cellular proteome since it is the same in all types of cells analyzed.


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