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Published on: December 17, 2012
Annotating proteins from endoplasmic reticulum and Golgi apparatus in eukaryotic proteomes
1CUBIC, Department of Biochemistry and Molecular Biophysics, Columbia University, 650 West 168th Street BB217, New York, NY 10032, USA.
This study analyzes protein localization signals, finding specific endoplasmic reticulum (ER) and Golgi retrieval motifs. It provides estimates for inferring protein localization via homology transfer, annotating thousands of ER and Golgi proteins.
Area of Science:
- Cell Biology
- Bioinformatics
- Proteomics
Background:
- Protein sub-cellular localization is crucial for function and often regulated by sequence motifs.
- Endoplasmic reticulum (ER) and Golgi apparatus are key organelles involved in protein processing and transport.
- Homology transfer is a method used to infer protein function or localization based on sequence similarity.
Purpose of the Study:
- To analyze the accuracy of experimentally characterized ER/Golgi retrieval motifs.
- To investigate the reliability of homology transfer for inferring protein localization.
- To estimate the probability of protein localization given specific retrieval motifs.
Main Methods:
- Analysis of experimentally validated ER/Golgi retrieval motifs.
- Estimation of motif specificity and localization probability.
- Rigorous assessment of homology transfer accuracy and coverage using sequence similarity.
- Proteome-wide annotation of ER and Golgi proteins.
Main Results:
- C-terminal ER retrieval motifs KDEL, HDEL, and AIAKE showed high specificity.
- Provided probability estimates for localization based on motif presence.
- Annotated 3304 ER (3182 membrane) and 1853 Golgi (759 membrane) proteins across proteomes.
- Identified additional putative 5157 globular and 3941 membrane ER or Golgi proteins.
- Each experimental annotation yielded 1-3 high-accuracy and 5-6 low-accuracy homology transfers.
Conclusions:
- Specific C-terminal motifs enhance the accuracy of predicting ER localization.
- Homology transfer, combined with motif analysis, is a powerful tool for large-scale protein localization prediction.
- The number of annotated proteins is expected to grow with new experimental data.
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