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Related Concept Videos

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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.
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Multi-species Conserved Sequences02:51

Multi-species Conserved Sequences

Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale  studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved DNA...
Conservation of Protein Domains02:26

Conservation of Protein Domains

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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...
Conserved Binding Sites01:49

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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

Updated: May 21, 2026

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
16:02

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation

Published on: February 10, 2023

Protein sequence alignment analysis by local covariation: coevolution statistics detect benchmark alignment errors.

Russell J Dickson1, Gregory B Gloor

  • 1Department of Biochemistry, The University of Western Ontario, London, Canada.

Plos One
|June 21, 2012
PubMed
Summary
This summary is machine-generated.

Local covariation analysis helps identify errors in protein sequence alignments, a common challenge in computational biology. This method, integrated into the LoCo tool, improves alignment accuracy and aids in understanding protein families.

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A Protocol for Computer-Based Protein Structure and Function Prediction
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A Protocol for Computer-Based Protein Structure and Function Prediction

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Related Experiment Videos

Last Updated: May 21, 2026

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
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Published on: February 10, 2023

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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

Area of Science:

  • Computational Biology
  • Molecular Biology
  • Bioinformatics

Background:

  • Accurate protein sequence alignments are crucial for understanding protein families, structure, function, and evolution.
  • Building high-quality alignments is a significant challenge in computational biology, with misalignments leading to erroneous biological inferences.
  • Current validation methods rely on sequence conservation, which can obscure alignment errors.

Purpose of the Study:

  • To introduce and demonstrate the utility of a novel alignment curation tool, LoCo.
  • To showcase how local covariation analysis can identify systematic misalignments independently of sequence conservation.
  • To improve the accuracy and reliability of protein sequence alignments for downstream biological analyses.

Main Methods:

  • Development of the LoCo (Local Covariation) alignment curation tool.
  • Integration of LoCo with the Jalview alignment editor.
  • Application of local covariation analysis to benchmark alignments (BAliBASE 3) and real-world datasets.
  • Validation of identified misalignments using structural evidence and biological function (active sites).

Main Results:

  • Local covariation successfully identifies regions of systematic misalignments, indicated by reduced positional independence.
  • Analysis of three BAliBASE 3 alignments revealed specific regions with high local covariation due to sequential and structural shifts.
  • Realignment of misaligned segments, guided by local covariation, resulted in reduced covariation scores and was supported by structural data.
  • Local covariation analysis effectively identified active site residues in an alignment of paralogous proteins.

Conclusions:

  • Local covariation is a powerful, conservation-independent method for detecting and correcting errors in protein sequence alignments.
  • The LoCo tool provides a practical means to integrate local covariation analysis into routine alignment curation workflows.
  • Improved protein alignments through LoCo enhance the accuracy of inferring protein structure, function, and evolutionary relationships.