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Related Concept Videos

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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Spontaneous and Induced Mutations01:30

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Spontaneous mutations arise infrequently during DNA replication due to errors in the process. A key factor behind these errors is tautomeric shifts in nitrogenous bases, where bases transition from keto to enol forms or amino to imino forms. This shift can alter base-pairing rules, leading to mutations. Additionally, reactive oxygen species (ROS) arising from aerobic metabolism can damage DNA, resulting in depurination (loss of a purine base) or depyrimidination (loss of a pyrimidine base).
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Mutations01:39

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Mutations01:35

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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
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Mutations in Microorganisms01:18

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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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Protein Folding Quality Check in the RER01:29

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ER is the primary site for the maturation and folding of soluble and transmembrane secretory proteins. The calnexin cycle is a specific chaperone system that folds and assesses the confirmation of N-glycosylated proteins before they can exit the ER lumen. The primary players of this quality check pipeline are the lectins, ER-resident chaperones, and a glucosyl transferase enzyme. In case the calnexin system in the lumen fails to salvage a misfolded protein, it is transported to the cytoplasm...
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Updated: Dec 10, 2025

Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms
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DynaMut2: Assessing changes in stability and flexibility upon single and multiple point missense mutations.

Carlos H M Rodrigues1,2, Douglas E V Pires1,2,3, David B Ascher1,2,4

  • 1Structural Biology and Bioinformatics, Department of Biochemistry, Bio21 Institute, University of Melbourne, Melbourne, Victoria, Australia.

Protein Science : a Publication of the Protein Society
|September 4, 2020
PubMed
Summary

DynaMut2 predicts how missense variations affect protein stability and dynamics using Normal Mode Analysis and graph signatures. This tool accurately forecasts single and multiple point mutation impacts, aiding disease variant studies.

Keywords:
dynamicsgraph-based signaturesmissense mutationsstability changes

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Area of Science:

  • Biochemistry and Molecular Biology
  • Computational Biology
  • Structural Biology

Background:

  • Predicting missense variant effects on protein stability and dynamics is crucial for understanding disease mechanisms and protein function.
  • Existing methods often focus on single-point mutations or static protein states, and dynamic-incorporating methods can be computationally intensive.

Purpose of the Study:

  • To develop and present DynaMut2, a web server for predicting the impact of single and multiple point mutations on protein stability and dynamics.
  • To integrate Normal Mode Analysis (NMA) for protein motion capture with graph-based signatures for wildtype environment representation.

Main Methods:

  • Utilized Normal Mode Analysis (NMA) to capture protein dynamics.
  • Employed graph-based signatures to represent the wildtype protein environment.
  • Developed a web server and API for accessibility and usability.

Main Results:

  • DynaMut2 achieved high accuracy in predicting missense mutation effects on protein stability (Pearson's correlation up to 0.72 for single-point, 0.64 for multiple-point mutations).
  • Performance was validated through 10-fold cross-validation and independent blind tests.
  • Demonstrated comparable performance to existing methods for predicting changes in Gibbs Free Energy (ΔΔG) and melting temperature (ΔTm).

Conclusions:

  • DynaMut2 accurately predicts the effects of missense mutations on protein stability and dynamics.
  • The tool is valuable for protein flexibility analysis and studying the role of variants in disease.
  • DynaMut2 is available as a free web server and API.