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Related Concept Videos

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...
Protein Organization01:24

Protein Organization

Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence.
Protein Organization01:13

Protein Organization

Overview
Protein Organization01:13

Protein Organization

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Proteomics01:33

Proteomics

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.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term proteomics...
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...

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Related Experiment Video

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Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
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Published on: July 14, 2015

Mining protein loops using a structural alphabet and statistical exceptionality.

Leslie Regad1, Juliette Martin, Gregory Nuel

  • 1MTi, Inserm UMR-S 973, Université Paris Diderot- Paris 7, Paris, F-75205 Cedex 13, France. leslie.regad@univ-paris-diderot.fr

BMC Bioinformatics
|February 6, 2010
PubMed
Summary
This summary is machine-generated.

Researchers developed a new method to analyze protein loops using structural motifs, simplifying complex structures into manageable "words." This approach effectively describes both short and long loops, revealing conserved patterns and improving analysis.

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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Area of Science:

  • Structural biology
  • Bioinformatics
  • Computational biology

Background:

  • Protein loops constitute 50% of residues in 3D structures and are crucial for functions like binding and catalysis.
  • Analyzing protein loops is challenging due to their high variability in sequence and structure compared to regular secondary structures.
  • Long loops are particularly difficult to study systematically because of data sparsity and conventional analysis limitations.

Purpose of the Study:

  • To develop a method for systematic description and analysis of protein loop structures, irrespective of loop length.
  • To simplify the analysis of protein loops by representing them as strings of structural prototypes.
  • To identify and characterize recurrent structural motifs within protein loops.

Main Methods:

  • Developed a method based on the structural alphabet Hidden Markov Model-Structural Alphabet (HMM-SA).
  • Simplified 3D protein structures into 1D strings of four-residue prototype fragments termed 'structural letters'.
  • Extracted and grouped seven-residue fragments from 93,000 protein loops into 'structural words' for analysis.

Main Results:

  • Identified 3,310 highly recurrent structural words covering 73% of loop lengths, with low structural variability (0.85 Å RMSd).
  • Found that two-thirds of these motifs are shared between short (<12 residues) and long loops.
  • Observed significant amino-acid conservation in half of the recurrent motifs, with 87% of long loops containing at least one such word.
  • Detected 930 over-represented structural words (30% of total) covering 40% of loop lengths, exhibiting lower variability and higher sequential specificity.

Conclusions:

  • A novel method using recurrent structural motifs and HMM-SA effectively decomposes and studies protein loops.
  • This approach successfully extracts meaningful motifs common to both short and long loops, enhancing signal-to-noise ratio.
  • The findings simplify long-loop analysis and improve the description of protein loops, potentially revealing structural or functional constraints.