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Related Concept Videos

Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
Signal Sequences and Sorting Receptors01:41

Signal Sequences and Sorting Receptors

Signal sequences are short amino acid sequences that guide newly synthesized proteins to their proper location within the cell. Classical signal sequences are fifteen to sixty amino acids long and present at the N-terminus of a polypeptide chain. Each signal sequence has a conserved segment of basic residues towards their N terminus, a hydrophobic core, and a C-terminus rich in polar residues. The C-terminus also contains a signal cleavage site and features a -3 -1 sequence motif. The -3-1...
Nuclear Localization Signals and Import01:46

Nuclear Localization Signals and Import

Proteins targeted to the nucleus carry short stretches of amino acid sequences called the nuclear localization signal or NLS. Classical nuclear localization signals are of two types: monopartite and bipartite NLS. Monopartite classical NLS (cNLS) consists of a single cluster of 4-8 amino acids. Bipartite cNLS consists of two clusters of  2-3 amino acids and a 9-12 residue long proline-rich linker bridging the two clusters. Signal clusters are rich in positively charged amino acids such as...
Nuclear Protein Sorting01:34

Nuclear Protein Sorting

Nuclear protein sorting is the selective trafficking of histones, polymerases, gene regulatory proteins into the nucleus and exporting RNAs and ribosomes to the cytosol. It is a tightly controlled process that regulates gene expression within a cell.
Proteins targeted to the nucleus carry nuclear localization signals or NLS recognized by import receptors in the cytosol. Similarly, proteins with nuclear export signals are recognized by export receptors. Import and export receptors are...
Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to form...
Directing Proteins to the Rough Endoplasmic Reticulum01:34

Directing Proteins to the Rough Endoplasmic Reticulum

The organelle-specific signaling sequences direct proteins synthesized in the cytosol to their final destination like ER, mitochondria, peroxisomes, etc. Some of the proteins directed to ER are then trafficked via vesicles to other organelles within the cell or the extracellular environment through the Golgi complex. For example, the rough ER synthesizes soluble proteins for transportation to the lysosomes or secretion out of the cell. It can also synthesize transmembrane proteins that can...

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Discriminative motif finding for predicting protein subcellular localization.

Tien-ho Lin1, Robert F Murphy, Ziv Bar-Joseph

  • 1Carnegie Mellon University, Pittsburgh, Pittsburgh, PA 15213, USA. thlin@cs.cmu.edu

IEEE/ACM Transactions on Computational Biology and Bioinformatics
|January 15, 2011
PubMed
Summary

This study introduces a new method using discriminative hidden Markov models (HMMs) to predict protein subcellular locations. This approach effectively identifies protein targeting motifs, improving accuracy and aiding in database error correction.

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Molecular Biology

Background:

  • Predicting protein subcellular localization from sequence is crucial for understanding protein function.
  • Existing methods often rely on global sequence features or predefined motifs, limiting their predictive power.
  • A need exists for novel computational approaches that can identify novel targeting signals and improve localization accuracy.

Purpose of the Study:

  • To develop and evaluate a novel computational method for predicting protein subcellular localization.
  • To identify potential protein targeting motifs using a discriminative approach based on hidden Markov models (HMMs).
  • To leverage a hierarchical model structure that mimics cellular protein sorting mechanisms.

Main Methods:

  • Development of discriminative hidden Markov models (discriminative HMMs) to identify compartment-specific protein targeting motifs.
  • Utilizing a hierarchical model structure to represent the protein sorting pathway.
  • Testing the method on a benchmark dataset of yeast proteins to assess prediction accuracy.

Main Results:

  • The discriminative HMM approach significantly improved protein localization prediction accuracy compared to existing methods.
  • The hierarchical structure further enhanced prediction performance by mimicking biological sorting processes.
  • Identified motifs were conserved and could be mapped to known targeting signals, revealing potential annotation errors in public databases.

Conclusions:

  • The novel discriminative HMM-based method provides an effective strategy for predicting protein subcellular localization.
  • The identified motifs offer insights into protein targeting mechanisms and can help refine protein annotations.
  • This approach has implications for improving the quality of protein databases and advancing systems biology research.