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

"New-version-fast-multipole-method" accelerated electrostatic interactions in biomolecular systems.

Benzhuo Lu1, Xiaolin Cheng, J Andrew McCammon

  • 1Howard Hughes Medical Institute, Center for Theoretical Biological Physics, University of California at San Diego, La Jolla, California 92093-0365.

Journal of Computational Physics
|April 2, 2008
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

Modeling Ion Transport and Selectivity via a Lennard-Jones Modified Poisson-Nernst-Planck Approach.

The journal of physical chemistry. B·2026
Same author

An Unfitted Finite Element Poisson-Boltzmann Solver with Automatic Resolving of Curved Molecular Surface.

The journal of physical chemistry. B·2024
Same author

Interface Engineering of Carrier-Protein-Dependent Metabolic Pathways.

ACS chemical biology·2023
Same author

Multiscale computational modeling of the effects of 2'-deoxy-ATP on cardiac muscle calcium handling.

Journal of applied physics·2023
Same author

Parameter-Efficient Densely Connected Dual Attention Network for Phonocardiogram Classification.

IEEE journal of biomedical and health informatics·2023
Same author

PERIOD phosphorylation leads to feedback inhibition of CK1 activity to control circadian period.

Molecular cell·2023
Same journal

HeartSimSage: Attention-Enhanced Graph Neural Networks for Accelerating Cardiac Mechanics Modeling.

Journal of computational physics·2026
Same journal

Composite B-spline regularized delta functions for the immersed boundary method: Divergence-free interpolation and gradient-preserving force spreading.

Journal of computational physics·2026
Same journal

Improving the robustness of the immersed interface method through regularized velocity reconstruction.

Journal of computational physics·2025
Same journal

Laplacian Eigenfunction-Based Neural Operator for Learning Nonlinear Reaction-Diffusion Dynamics.

Journal of computational physics·2025
Same journal

An efficient adaptive algorithm for photon-electron coupled Boltzmann equation in radiation therapy.

Journal of computational physics·2025
Same journal

On generalizing the induced surface charge method to heterogeneous Poisson-Boltzmann models for electrostatic free energy calculation.

Journal of computational physics·2025
See all related articles

This study introduces an efficient numerical algorithm for biomolecular electrostatics using boundary integral equations and fast multipole methods. The approach offers O(N) computational scaling for large systems like protein interactions.

Area of Science:

  • Computational biology
  • Biophysics
  • Biomolecular modeling

Background:

  • Calculating electrostatic interactions is crucial for understanding biomolecular systems.
  • Existing methods face challenges with large-scale systems and computational efficiency.

Purpose of the Study:

  • To develop an efficient and accurate numerical algorithm for biomolecular electrostatics.
  • To enable the study of large-scale systems, including protein-protein interactions and nanoparticle assembly.

Main Methods:

  • Discretization of the linearized Poisson-Boltzmann equation using a boundary integral equation (BIE) approach.
  • Efficient solution using Krylov subspace iterative methods (GMRES, BiCGStab).
  • Acceleration of matrix-vector multiplications via a fast multipole method (FMM).

Related Experiment Videos

Main Results:

  • The algorithm achieves asymptotically optimal O(N) CPU time and memory usage.
  • The method is well-conditioned for both single and multiple macromolecule systems.
  • Demonstrated applications include the nicotinic acetylcholine receptor and protein-DNA interactions.

Conclusions:

  • The developed algorithm significantly enhances computational capabilities for biomolecular electrostatics.
  • It provides an efficient tool for studying complex biological systems and processes.
  • This work advances the field of computational biophysics and molecular modeling.