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Related Concept Videos

Intrinsically Disordered Proteins02:18

Intrinsically Disordered Proteins

Intrinsically disordered proteins are a group of proteins that do not fold into specific three-dimensional structures. Their structural flexibility allows them to complement ordered proteins to perform functions that are inaccessible to rigid structures. They are more common in eukaryotes than prokaryotes and may either be exclusively intrinsically disordered or hybrid proteins, consisting of a mix of ordered and disordered regions. The absence of a rigid structure in these proteins can be...
Intrinsically Disordered Proteins02:18

Intrinsically Disordered Proteins

Intrinsically disordered proteins are a group of proteins that do not fold into specific three-dimensional structures. Their structural flexibility allows them to complement ordered proteins to perform functions that are inaccessible to rigid structures. They are more common in eukaryotes than prokaryotes and may either be exclusively intrinsically disordered or hybrid proteins, consisting of a mix of ordered and disordered regions. The absence of a rigid structure in these proteins can be...
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...
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...
Conservation of Protein Domains02:26

Conservation of Protein Domains

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...
The Unfolded Protein Response01:37

The Unfolded Protein Response

The ER is the hub of protein synthesis in a cell. It has robust systems to quality control protein folding and also for degradation of terminally misfolded proteins. Under normal conditions, a small proportion of misfolded proteins that cannot be salvaged need to be transported to the cytoplasm by the ER-associated degradation or ERAD pathways. However, if the ERAD cannot handle the misfolded proteins, the cell activates the unfolded protein response or UPR to adjust the protein folding...

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Related Experiment Video

Updated: Jul 5, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

DPROT: prediction of disordered proteins using evolutionary information.

Deepti Sethi1, Aarti Garg, G P S Raghava

  • 1Scientist and Head Bioinformatics Centre, Institute of Microbial Technology, Sector 39A, Chandigarh, India.

Amino Acids
|April 22, 2008
PubMed
Summary
This summary is machine-generated.

Predicting disordered proteins is crucial for understanding diseases. This study developed a computational method using sequence and evolutionary data, achieving high accuracy and providing a web server for broader use.

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Last Updated: Jul 5, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Area of Science:

  • Computational Biology
  • Protein Science
  • Bioinformatics

Background:

  • Structurally disordered proteins are linked to various diseases, necessitating efficient study methods.
  • Accurate prediction of disordered proteins is vital for molecular-level research.

Purpose of the Study:

  • To develop a computational method for predicting disordered proteins.
  • To utilize sequence and profile compositions as input features for Support Vector Machine (SVM) models.
  • To create a user-friendly web server for disordered protein prediction.

Main Methods:

  • Developed SVM models using amino acid and dipeptide compositions.
  • Incorporated predicted secondary structure content (coil, sheet, helices) into SVM models.
  • Utilized evolutionary information from multiple sequence alignment profiles to enhance SVM model performance.

Main Results:

  • SVM models achieved sensitivities ranging from 73.2% to 78% and Matthew's Correlation Coefficient (MCC) values from 0.60 to 0.78.
  • The best performing SVM model, using evolutionary profiles, reached 78% sensitivity and 0.78 MCC.
  • An independent evaluation on partially disordered proteins showed a 86.6% correct prediction rate.
  • A web server, DPROT, was developed and is publicly available.

Conclusions:

  • Computational prediction of disordered proteins is feasible and effective.
  • Evolutionary information significantly improves prediction accuracy.
  • The developed DPROT web server provides a valuable tool for researchers studying disordered proteins and associated diseases.