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Related Concept Videos

Mutations01:39

Mutations

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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.
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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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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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Organisms are capable of detecting and fixing nucleotide mismatches that occur during DNA replication. This sophisticated process requires identifying the new strand and replacing the erroneous bases with correct nucleotides. Mismatch repair is coordinated by many proteins in both prokaryotes and eukaryotes.
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intDesc-AbMut: A Tool for Describing and Understanding How Antibody Mutations Impact Their Environmental

Shuntaro Chiba1, Masateru Ohta1, Tsutomu Yamane1,2

  • 1HPC- and AI-driven Drug Development Platform Division, RIKEN Center for Computational Science, Yokohama 230-0045, Japan.

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|April 29, 2026
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Summary

A new computational tool, intDesc-AbMut, automates the analysis of residue interactions in antibody structures. This enables systematic characterization for antibody engineering and protein design applications.

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Area of Science:

  • Structural Biology
  • Computational Biology
  • Protein Engineering

Background:

  • Structure-based antibody engineering demands detailed analysis of residue interactions.
  • Manual inspection of these interactions is labor-intensive and limits reproducibility.

Purpose of the Study:

  • To develop a computational tool, intDesc-AbMut, for automated, residue-centric interaction analysis in antigen-antibody complexes.
  • To enable systematic characterization of interactions for antibody engineering and protein design.

Main Methods:

  • Developed intDesc-AbMut, a software tool for automated extraction, classification, and descriptor generation of residue interactions.
  • Defined 36 interaction types, including conventional, weak hydrogen bonds, and multipolar interactions.
  • Integrated interaction descriptors into a machine learning framework to assess their structural relevance.

Main Results:

  • The tool automates the analysis of residue-level interactions within antigen-antibody complexes.
  • Interaction descriptors quantitatively represent local packing, weak hydrogen bonding, and electrostatic features.
  • Machine learning analysis confirmed that descriptors capture meaningful structural signals for side-chain conformations.

Conclusions:

  • intDesc-AbMut provides a systematic and extendable framework for mutation-focused interaction analysis.
  • The tool facilitates quantitative insights into antibody structural studies.
  • Enables advancements in antibody engineering and related protein design applications.