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Related Concept Videos

Mutations01:35

Mutations

31.0K
Mutations are changes in the sequence of DNA. These changes can occur spontaneously or they can be induced by exposure to environmental factors. Mutations can be characterized in a number of different ways: whether and how they alter the amino acid sequence of the protein, whether they occur over a small or large area of DNA, and whether they occur in somatic cells or germline cells.
Chromosomal Alterations Are Large-Scale Mutations
While point mutations are changes in a single nucleotide in...
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Mutations01:39

Mutations

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Overview
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Mutations01:39

Mutations

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Point and Frameshift Mutations01:30

Point and Frameshift Mutations

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Point mutations are genetic alterations involving the change of a single nucleotide base pair in DNA. Depending on how the alteration affects protein synthesis, they can lead to various consequences.Point mutations fall into the following types:Silent mutations occur when a nucleotide change does not alter the amino acid sequence due to the redundancy of the genetic code. For instance, changing ACC to ACA still encodes threonine, leaving the protein function unaffected. This occurs because...
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Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

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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...
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Mutations in Microorganisms01:18

Mutations in Microorganisms

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Mutations are heritable changes in an organism’s genome involving alterations in the base sequence of DNA or RNA. These changes can influence cellular processes and phenotypic traits, potentially transforming the unaltered wild type into a mutant form. Such changes, termed forward mutations, are pivotal in shaping the genetic diversity of organisms.RNA viruses exhibit the highest mutation rates due to the absence of robust proofreading mechanisms during genome replication. In contrast,...
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Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
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Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

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Integrative visual analysis of protein sequence mutations.

Nadezhda T Doncheva1, Karsten Klein2, John H Morris3

  • 1Max Planck Institute for Informatics, 66123 Saarbücken, Germany ; University of California, San Francisco, 94143-2240 San Francisco, USA.

BMC Proceedings
|September 20, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces a novel visual approach to analyze protein mutations by integrating sequence, structure, and interaction data. This method enhances understanding of how amino acid changes impact protein function.

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Area of Science:

  • Biochemistry
  • Structural Biology
  • Bioinformatics

Background:

  • Understanding protein mutations is crucial for characterizing protein sequence, structure, and function.
  • Analyzing the functional impact of amino acid changes requires considering multiple biological properties of protein residues.

Purpose of the Study:

  • To present a novel visual approach for analyzing residue mutations.
  • To integrate diverse biological visualizations with external molecular data for comprehensive analysis.

Main Methods:

  • Developed a visual approach combining 1D sequence, 3D structure, and 2D residue interaction network views.
  • Linked and synchronized multiple views to minimize user cognitive load.
  • Mapped protein mutations with functional and structural information, analyzing residue interactions.

Main Results:

  • Presented a novel visual approach for analyzing protein mutations.
  • Integrated various biological visualizations (sequence, structure, interaction networks) with external molecular data.
  • Demonstrated effectiveness on BioVis 2013 data contest examples.

Conclusions:

  • The visual approach and software facilitate integrative and interactive analysis of protein mutations.
  • Complementary visualizations enriched with molecular properties and biological knowledge aid analysis.
  • The method enhances the understanding of protein mutation impacts.