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Related Concept Videos

Mitochondrial Protein Sorting01:39

Mitochondrial Protein Sorting

Mitochondria are double-membrane organelles of the eukaryotes involved in cellular metabolism, signaling, ATP synthesis, and programmed cell death.  Each of these processes requires specific proteins and enzymes that must be correctly sorted to the right mitochondrial subcompartment for the proper functioning of the organelle.
Most of these mitochondrial proteins are encoded by the nucleus and imported to the mitochondria as unfolded or loosely folded precursors. Mitochondrial precursors...
Translocation of Proteins into the Mitochondria01:19

Translocation of Proteins into the Mitochondria

Mitochondrial precursors are translocated to the internal subcompartments via independent mechanisms involving distinct protein machineries called translocases.
Sorting of outer membrane proteins:
Mitochondrial outer membrane proteins are of two types: the transmembrane, beta-barrel porins, and the membrane-anchored, alpha-helical proteins. Beta-barrel porin precursors are translocated by the TOM complex and inserted into the outer mitochondrial membrane by the SAM complex. In contrast,...
Overview of Protein Sorting and Transport01:45

Overview of Protein Sorting and Transport

Eukaryotic cells have different membrane-bound organelles with distinct protein requirements. The process by which proteins are targeted to a specific organelle is called protein sorting.
Protein sorting can be of two types: signal-based sorting and vesicle-based trafficking. In signal-based sorting, specific amino acid sequences called sorting signals target proteins to the proper location inside the cell either via gated transport or by protein translocation.  In gated transport, folded...
Cotranslational Protein Translocation01:20

Cotranslational Protein Translocation

Translocation of proteins across membranes is an ancient process that occurs even in bacteria and archaebacteria. In fact, the components of the translocation machinery are still conserved between prokaryotes and eukaryotes.
Sec61 channel partners for cotranslational translocation
During cotranslational translocation, the Sec61 channel partners with the signal recognition particle (SRP), the signal recognition particle receptor (SR), and the ribosomes to transport the nascent polypeptide chain...
Tail-anchoring of Proteins in the ER Membrane01:45

Tail-anchoring of Proteins in the ER Membrane

Tail-anchored, or TA, proteins are estimated to make up to 3-5% of membrane proteins found in the eukaryotic cell. Such proteins have a single transmembrane domain located approximately 30 amino acid residues upstream from the C-terminal end. As a result, the signal recognition particle (SRP) cannot guide a TA protein to the ER membrane for cotranslational insertion. Hence, they are integrated into the ER membrane post-translationally using their C-terminal end as the anchor. TA proteins...
Energy to Drive Translocation01:37

Energy to Drive Translocation

Mitochondrial protein import is powered by two distinct energy sources: ATP hydrolysis and electrochemical potential across the inner membrane. Newly synthesized precursors are bound by cytosolic chaperones of the Hsp70 family, which guide them to the import receptors on the mitochondrial surface. Utilizing the energy of ATP hydrolysis, Hsp70 chaperones transfer these precursors to the TOM receptors on the mitochondrial outer membrane.
Generally, polypeptides are unfolded by two distinct...

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Assessment of Submitochondrial Protein Localization in Budding Yeast Saccharomyces cerevisiae
08:55

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Published on: July 19, 2021

Multi-kernel transfer learning based on Chou's PseAAC formulation for protein submitochondria localization.

Suyu Mei1

  • 1Software College, Shenyang Normal University, Shenyang, China. 061021053@fudan.edu.cn

Journal of Theoretical Biology
|November 1, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a new computational method, multi-kernel transfer learning (MK-TLM), to predict protein sub-organelle localization, specifically within mitochondria. MK-TLM effectively uses homologous gene ontology (GO) information to improve predictions for novel or poorly annotated proteins.

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Visualization and Quantification of Endogenous Intra-Organelle Protein Interactions at ER-Mitochondria Contact Sites by Proximity Ligation Assays

Published on: October 20, 2023

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Molecular Biology

Background:

  • Determining protein sub-organelle localization, such as within mitochondria, is challenging due to limitations in imaging techniques.
  • Existing computational methods for protein submitochondria localization often show unsatisfactory performance, especially for novel proteins.
  • Gene Ontology (GO) information is effective for subcellular localization but may be unavailable for new or sparsely annotated proteins.

Purpose of the Study:

  • To develop an improved computational model for predicting protein localization within mitochondria.
  • To address the challenge of limited GO information for novel or poorly characterized proteins.
  • To enhance the accuracy and reliability of protein sub-organelle localization predictions.

Main Methods:

  • Proposed a multi-kernel transfer learning model (MK-TLM) for protein submitochondria localization.
  • Transferred Gene Ontology (GO) information from homologous proteins to target proteins.
  • Conducted performance evaluations across optimistic, moderate, and pessimistic cases based on GO information availability.

Main Results:

  • The MK-TLM model significantly outperformed existing baseline models for protein submitochondria localization.
  • The model demonstrated excellent performance for novel mitochondria proteins.
  • The MK-TLM showed robust accuracy for mitochondria proteins belonging to poorly understood subfamilies.

Conclusions:

  • The developed MK-TLM offers a powerful and accurate computational approach for protein sub-organelle localization.
  • Transfer learning using homologous GO data effectively overcomes limitations of missing annotations.
  • This method advances the field of predicting protein localization within organelles, particularly for challenging cases.