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

Mismatch Repair01:20

Mismatch Repair

4.8K
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.
The Mutator Protein Family Plays a Key Role in DNA Mismatch Repair
The human genome has more than 3 billion base pairs of DNA per cell. Prior to cell division, that vast amount of genetic...
4.8K
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

7.0K
The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
7.0K

You might also read

Related Articles

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

Sort by
Same author

Adaptive Normal Mode Sampling (aMDeNM) Enhances Exploration of Protein Conformational Space and Reveals the Functional Role of Frequency Coupling.

Journal of chemical theory and computation·2026
Same author

Benchmarking Machine Learning Models for HIV-1 Protease Inhibitor Resistance Prediction: Impact of Data Set Construction and Feature Representation.

Journal of chemical information and modeling·2025
Same author

Structural and dynamic properties of guanosine-analog binding to 2'-deoxyguanosine-II riboswitch: a computational study.

Journal of biomolecular structure & dynamics·2025
Same author

Computational Structural Comparison of Toxoplasma gondii CDPK1 and Human BUB1 kinases: Implications for Selective Inhibitor Design.

ACS omega·2025
Same author

Structure and dynamics of GAD65 in complex with an autoimmune polyendocrine syndrome type 2-associated autoantibody.

Nature communications·2025
Same author

Estimating Absolute Protein-Protein Binding Free Energies by a Super Learner Model.

Journal of chemical information and modeling·2025

Related Experiment Video

Updated: Jun 3, 2025

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

17.0K

Engineering Protein Dynamics through Mutational Energy Landscape Traps.

Lucas de Almeida Machado1,2, João Sartori2,3, Paula Fernandes da Costa Franklin2,3

  • 1Instituto Nacional de Saúde da Mulher, da Criança e do Adolescente - Fiocruz, Rio de Janeiro, Brazil 22250-020.

Journal of Chemical Information and Modeling
|January 8, 2025
PubMed
Summary

We developed Mutational Energy Landscape Trap (MELT), a new method to control protein dynamics. MELT uses computational analysis and mutagenesis to engineer proteins with specific dynamic behaviors for advanced protein engineering.

More Related Videos

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

914
Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches
05:56

Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches

Published on: October 13, 2022

1.3K

Related Experiment Videos

Last Updated: Jun 3, 2025

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

17.0K
Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

914
Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches
05:56

Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches

Published on: October 13, 2022

1.3K

Area of Science:

  • Biochemistry
  • Structural Biology
  • Computational Biology

Background:

  • Protein dynamics are crucial for biological functions like enzyme activity and signal transduction.
  • Conventional protein engineering methods often overlook the manipulation of dynamic protein behaviors.
  • Precisely controlling protein dynamics remains a challenge in protein engineering.

Purpose of the Study:

  • To develop a novel computational method for precisely controlling protein dynamics.
  • To introduce a technique that combines Normal Mode Analysis (NMA) and in silico mutagenesis.
  • To engineer proteins with desired dynamic properties for various applications.

Main Methods:

  • Developed Mutational Energy Landscape Trap (MELT), integrating Normal Mode Analysis (NMA) and in silico mutagenesis.
  • Displaced protein structures along low-frequency normal modes and introduced mutations to modulate dynamics.
  • Validated the method using hen-egg lysozyme as a model system, monitoring collective coordinates via molecular dynamics simulations.

Main Results:

  • MELT successfully generated new protein sequences exhibiting desired dynamical behaviors in simulations.
  • The method demonstrated the ability to either stabilize or enhance protein dynamics along specific normal modes.
  • Validation confirmed the effectiveness of MELT in manipulating protein collective movements.

Conclusions:

  • Mutational Energy Landscape Trap (MELT) offers an unprecedented approach to manipulate protein dynamics.
  • This method has significant potential for advancing protein engineering by enabling precise control over protein features.
  • MELT provides a powerful tool for designing proteins with tailored dynamic properties for biological applications.