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Related Concept Videos

Two-dimensional Gel Electrophoresis01:22

Two-dimensional Gel Electrophoresis

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Two-dimensional gel electrophoresis is a high-resolution protein separation method first introduced by O' Farrell and Klose in 1975. This method involves protein separation by two dimensions, mass and charge, making it more accurate than one-dimensional gel electrophoresis.
The first dimension separation uses the isoelectric focusing or IEF technique performed on immobilized pH gradient (IPG) strips that separate proteins according to their isoelectric points.
Biological samples, such...
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Proteomics01:33

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A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
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Proteome-pI 2.0: proteome isoelectric point database update.

Lukasz Pawel Kozlowski1

  • 1Institute of Informatics, Faculty of Mathematics, Informatics, and Mechanics, University of Warsaw, Warsaw, Mazovian Voivodeship 02-097, Poland.

Nucleic Acids Research
|October 31, 2021
PubMed
Summary
This summary is machine-generated.

Proteome-pI 2.0 enhances protein analysis by providing predicted isoelectric points and pKa values for over 61 million protein sequences. This updated database aids researchers in various proteomics techniques and data retrieval.

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Area of Science:

  • Biochemistry
  • Proteomics
  • Bioinformatics

Background:

  • The isoelectric point (pI) is crucial for protein separation and analysis.
  • Accurate pI and pKa values are essential for understanding protein behavior.
  • Existing databases lacked comprehensive pI and pKa data for large-scale proteome analysis.

Purpose of the Study:

  • To update and expand the Proteome-pI database with predicted isoelectric points and pKa values.
  • To provide a comprehensive resource for proteomics researchers.
  • To facilitate in silico analysis of proteomes and peptides.

Main Methods:

  • Prediction of isoelectric points using 21 methods and pKa values using one method.
  • In silico digestion of proteomes with common proteases.
  • Calculation of isoelectric points and molecular weights for millions of protein sequences and peptides.

Main Results:

  • Proteome-pI 2.0 now includes data for over 61 million protein sequences from 20,115 proteomes.
  • The database offers predicted pI for proteins and peptides, aiding bottom-up proteomics.
  • Virtual 2D-PAGE plots and customized proteome fractions are available.

Conclusions:

  • Proteome-pI 2.0 is a significantly expanded resource for researchers.
  • The database facilitates advanced proteomic analyses through comprehensive pI and pKa data.
  • Accessible data formats (CSV, FASTA) enhance usability for diverse research needs.