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

Distance and exposure dependent effective dielectric function.

Buddhadeb Mallik1, Artem Masunov, Themis Lazaridis

  • 1Department of Chemistry, City College of CUNY, Convent Avenue & 138th Street, New York, New York 10031, USA.

Journal of Computational Chemistry
|July 13, 2002
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

Membrane Curvature Generation by the Caveolin 8S Complex and the Role of Cholesterol.

bioRxiv : the preprint server for biology·2026
Same author

Seeking the Membrane-Bound Structure of the Caveolin 8S Complex.

The journal of physical chemistry. B·2025
Same author

Seeking the Membrane-Bound Structure of the Caveolin 8S Complex.

bioRxiv : the preprint server for biology·2025
Same author

Classical Models of Hydroxide for Proton Hopping Simulations.

The journal of physical chemistry. B·2024
Same author

CHARMM at 45: Enhancements in Accessibility, Functionality, and Speed.

The journal of physical chemistry. B·2024
Same author

Transmembrane β-Barrel Models of α-Synuclein Oligomers.

Journal of chemical information and modeling·2023
Same journal

PES2MP: A Python Application for Automating Collisional Dynamics of Linear Rigid-Rotors.

Journal of computational chemistry·2026
Same journal

The Anionic States of Ubiquinone Characterized by Second-Order Approximate Coupled-Cluster Theory.

Journal of computational chemistry·2026
Same journal

Hydrogen Bond Energy Estimation in Large Molecular Clusters via the Method of Synergistic Cyclic Cooperativity: A Software Update H-BEE 2.0.

Journal of computational chemistry·2026
Same journal

The Intricate Mechanism of Nitric Oxide Synthase.

Journal of computational chemistry·2026
Same journal

A Molecular "Thermometer" for Measuring Effective Non-Local Exchange.

Journal of computational chemistry·2026
Same journal

Insights to Orientation Dependence of Molecular Conduction Modeled by High-Level Quantum Embedding.

Journal of computational chemistry·2026
See all related articles

This study introduces a new dielectric screening function for molecular dynamics simulations of biomolecules. The function accurately calculates effective dielectric constants, improving electrostatic energy predictions in implicit solvent models.

Area of Science:

  • Computational Chemistry
  • Biophysics
  • Molecular Modeling

Background:

  • Accurate dielectric screening is crucial for molecular dynamics (MD) simulations of biomolecules in implicit solvent.
  • Existing models like Generalized Born (GB) have limitations in representing complex dielectric environments.

Purpose of the Study:

  • To develop a novel, empirically derived dielectric screening function for MD simulations.
  • To improve the accuracy of electrostatic interaction energy calculations in implicit solvent models.

Main Methods:

  • Continuum electrostatics calculations to determine effective dielectric constants (D(eff)) for atom pairs in globular proteins.
  • Fitting D(eff) values to an empirical, analytical function based on intercharge distance, dielectric boundary proximity, and solvent exposure.

Related Experiment Videos

  • Comparison of the new function's performance against Generalized Born and linear distance-dependent models using mean square deviation of electrostatic energies.

    • Main Results:

    • The developed function provides a sigmoidal relationship for D(eff) based on key physical parameters.
    • It significantly reduces the mean square deviation of electrostatic interaction energies (0.48 kcal/mol) compared to existing models.
    • The function demonstrates superior performance across various protein sizes and compactness levels, except for unfolded polypeptide chains.

    Conclusions:

    • The new empirical dielectric screening function offers improved accuracy for biomolecular simulations in implicit solvent.
    • This advancement is particularly beneficial for modeling folded proteins, enhancing the reliability of MD simulations.
    • Further refinement may be needed for highly flexible or unfolded biomolecular systems.