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 Experiment Videos

Computational alanine scanning mutagenesis--an improved methodological approach.

Irina S Moreira1, Pedro A Fernandes, Maria J Ramos

  • 1REQUIMTE/Departamento de Química, Faculdade de Ciências da Universidade do Porto, Rua do Campo Alegre 687, 4169-007 Porto, Portugal.

Journal of Computational Chemistry
|December 30, 2006
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Binding Mechanism of UAMC-1110 to Fibroblast Activation Protein.

Journal of chemical information and modeling·2026
Same author

The GPCR Connection: Linking Alzheimer's Disease and Glioblastoma.

Journal of cellular and molecular medicine·2026
Same author

Mechanism of Polyester Hydrolysis by Marine Bacterium PE-H Enzyme: an Atomistic and Thermodynamic Characterization.

Journal of chemical information and modeling·2026
Same author

Mechanism of Hyaluronic Acid Hydrolysis Catalyzed by Snake Venom Hyaluronidase.

Journal of chemical information and modeling·2026
Same author

Revealing the rationale behind the differential neutralization of phospholipase A<sub>2</sub> (PLA<sub>2</sub>) enzymes in snake and bee venom by varespladib (LY-315920), a small molecule PLA<sub>2</sub> inhibitor.

Journal of biomolecular structure & dynamics·2025
Same author

Artificial intelligence in rare diseases: toward clinical impact.

Trends in pharmacological sciences·2025

This study introduces a faster, accurate computational method to predict changes in protein binding energy after alanine mutations. The approach successfully guides experimental mutagenesis by identifying key binding residues.

Area of Science:

  • Computational Biology
  • Structural Biology
  • Biophysics

Background:

  • Alanine scanning mutagenesis is crucial for understanding protein-protein interactions and identifying critical binding residues (hot-spots).
  • Existing methods for estimating binding free energy differences (DeltaDeltaG(binding)), like MM-PBSA, FEP, and TI, can be computationally expensive.

Purpose of the Study:

  • To develop a computationally efficient yet accurate method for predicting DeltaDeltaG(binding) from alanine scanning mutagenesis.
  • To validate the new method's performance against experimental data for protein complexes.

Main Methods:

  • A novel computational approach using Molecular Dynamics simulations in a continuum Generalized Born solvent model.
  • Employing three distinct internal dielectric constants to account for interfacial relaxation upon mutation.

Related Experiment Videos

  • Application to three protein complexes involving 46 alanine mutations.

    • Main Results:

    • Achieved a mean unsigned error of 0.80 kcal/mol for DeltaDeltaG(binding) predictions.
    • Demonstrated an 80% overall success rate and an 82% success rate for mutations significantly impacting binding energy (> 2.0 kcal/mol).
    • The method accurately predicted experimental mutagenesis outcomes.

    Conclusions:

    • The developed computational method offers a cost-effective and accurate alternative for analyzing protein-protein interfaces.
    • This approach can guide experimental mutagenesis studies by reliably identifying hot-spot residues.
    • Enables systematic scanning mutagenesis of protein interfaces, accelerating the discovery of binding determinants.