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Related Concept Videos

Mutations01:39

Mutations

94.5K
Overview
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Mutations01:35

Mutations

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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
While point mutations are changes in a single nucleotide in...
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Cancers Originate from Somatic Mutations in a Single Cell02:21

Cancers Originate from Somatic Mutations in a Single Cell

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Cancer arises from mutations in the critical genes that allow healthy cells to escape cell cycle regulation and acquire the ability to proliferate indefinitely. Though originating from a single mutation event in one of the originator cells, cancer progresses when the mutant cell lines continue to gain more and more mutations, and finally, become malignant. For example, chronic myelogenous leukemia (CML) develops initially as a non-lethal increase in white blood cells, which progressively...
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Viral Mutations00:36

Viral Mutations

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A mutation is a change in the sequence of bases of DNA or RNA in a genome. Some mutations occur during replication of the genome due to errors made by the polymerase enzymes that replicate DNA or RNA. Unlike DNA polymerase, RNA polymerase is prone to errors because it is not capable of “proofreading” its work. Viruses with RNA-based genomes, like HIV, therefore accrue mutations faster than viruses with DNA-based genomes. Because mutation and recombination provide the raw material...
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Protein-protein Interfaces02:04

Protein-protein Interfaces

14.7K
Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
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Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

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In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
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Related Experiment Video

Updated: Feb 1, 2026

A Strategy to Identify de Novo Mutations in Common Disorders such as Autism and Schizophrenia
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Identifying Driver Interfaces Enriched for Somatic Missense Mutations in Tumors.

Kivilcim Ozturk1,2, Hannah Carter3,4,5,6

  • 1Division of Medical Genetics, Department of Medicine, University of California San Diego, La Jolla, CA, USA.

Methods in Molecular Biology (Clifton, N.J.)
|December 14, 2018
PubMed
Summary

Identifying driver mutations in human cancers is key. This study maps somatic mutations to protein structures to find "driver interfaces," highlighting proteins crucial for tumor growth.

Keywords:
Driver interfacesMissense mutationProtein 3D structureProtein-protein interactionSomatic cancer mutationStructurally resolved network

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Area of Science:

  • Genomics
  • Structural Biology
  • Cancer Research

Background:

  • Human cancers accumulate numerous somatic mutations.
  • Only a fraction of these mutations drive tumor growth.
  • Identifying driver mutations is crucial for understanding cancer progression.

Purpose of the Study:

  • To develop a method for identifying driver mutations in cancer.
  • To pinpoint critical protein interaction sites targeted by cancer-driving mutations.

Main Methods:

  • Mapping somatic mutations onto 3D protein structures.
  • Analyzing protein-interaction interfaces for mutation bias.
  • Identifying interfaces with an excess of nonsynonymous mutations.

Main Results:

  • A novel approach to identify potential driver mutations was developed.
  • The study identified specific protein-interaction interfaces as
  • driver interfaces
  • .

Conclusions:

  • Unexpected mutation bias at protein interfaces suggests positive selection.
  • This method implicates interacting proteins as candidate drivers of tumorigenesis.
  • The findings offer a new strategy for cancer driver gene discovery.