Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

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.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to form...
Conservation of Protein Domains02:26

Conservation of Protein Domains

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 form...
Convergent Evolution01:54

Convergent Evolution

Evolution shapes the features of organisms over time, ensuring that they are suited for the environments in which they live. Sometimes, selection pressure leads to the rise of similar but unrelated adaptations in organisms with no recent common ancestors, a process known as convergent evolution.The structures that arise from convergent evolution are called analogous structures. They are similar in function even if they are dissimilar in structure. Further, structures can be analogous while also...
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

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...
Eukaryotic Evolution01:24

Eukaryotic Evolution

The endosymbiont theory is the most widely accepted theory of eukaryotic evolution; however, its progression is still somewhat debated. According to the nucleus-first hypothesis, the ancestral prokaryote first evolved a membrane to enclose DNA and form the nucleus. Conversely, the mitochondria-first hypothesis suggests that the nucleus was formed after endosymbiosis of mitochondria.
Contrary to the endosymbiont theory, the eukaryote-first hypothesis proposes that the simpler prokaryotic and...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Cellular and molecular basis of PfCoronin function in artemisinin resistance in Plasmodium falciparum.

Nature communications·2026
Same author

Cellular and molecular basis of <i>Pf</i> Coronin function in artemisinin resistance in <i>Plasmodium falciparum</i>.

bioRxiv : the preprint server for biology·2025
Same author

MalKinID: A classification model for identifying malaria parasite genealogical relationships using identity-by-descent.

Genetics·2024
Same author

MalKinID: A Likelihood-Based Model for Identifying Malaria Parasite Genealogical Relationships Using Identity-by-Descent.

bioRxiv : the preprint server for biology·2024
Same author

Two decades of molecular surveillance in Senegal reveal rapid changes in known drug resistance mutations over time.

Malaria journal·2024
Same author

Universal signatures of transposable element compartmentalization across eukaryotic genomes.

bioRxiv : the preprint server for biology·2024

Related Experiment Video

Updated: Jun 19, 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

Colloquium papers: Adaptive landscapes and protein evolution.

Maurício Carneiro1, Daniel L Hartl

  • 1Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA.

Proceedings of the National Academy of Sciences of the United States of America
|October 7, 2009
PubMed
Summary

Protein evolution under strong selection is key to understanding resistance. Real protein mutations are more additive than random, suggesting smoother adaptive landscapes.

More Related Videos

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

Related Experiment Videos

Last Updated: Jun 19, 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

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

Area of Science:

  • Evolutionary biology
  • Molecular evolution
  • Biochemistry

Background:

  • Understanding protein evolution under strong selection is crucial due to widespread resistance to insecticides, antibiotics, and vaccines.
  • Studies of mutant proteins and their combinations explore evolutionary pathways to resistance.
  • Protein function or fitness proxies are measured for engineered proteins.

Purpose of the Study:

  • To examine empirical fitness landscapes of proteins.
  • To compare real protein fitness landscapes with simulated random landscapes.
  • To investigate the additivity of mutations in protein evolution.

Main Methods:

  • Engineering mutant proteins and assessing their fitness.
  • Creating empirical fitness landscapes.
  • Generating simulated landscapes with randomly assigned fitnesses.
  • Comparing additivity and landscape roughness between empirical and simulated data.

Main Results:

  • Mutant sites in real proteins exhibit significantly higher additivity compared to random simulations.
  • Empirical fitness landscapes show a high degree of additivity.
  • The 'roughness' statistic for actual proteins examined falls within the lowest 0.5% tail of random landscapes.

Conclusions:

  • Real protein evolution under strong selection demonstrates a high degree of mutational additivity.
  • This additivity results in smoother adaptive landscapes than predicted by random models.
  • Findings have implications for understanding and predicting the evolution of resistance.