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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

100
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
100
Molecular Models02:00

Molecular Models

40.0K
Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
40.0K
Chemical Shift: Internal References and Solvent Effects01:17

Chemical Shift: Internal References and Solvent Effects

739
In an NMR sample, precise measurement of the absolute absorption frequencies of nuclei is difficult. A standard internal reference compound is added, and the frequency difference between the reference signal and sample signals is measured.
The internal reference compound generally used in NMR spectroscopy is tetramethylsilane (TMS). TMS is preferred because it is chemically inert, soluble in NMR solvents, and easily removable. Also, the highly shielded methyl protons in TMS yield an intense...
739
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

673
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
673
Molecular Comparison of Gases, Liquids, and Solids02:26

Molecular Comparison of Gases, Liquids, and Solids

42.5K
Particles in a solid are tightly packed together (fixed shape) and often arranged in a regular pattern; in a liquid, they are close together with no regular arrangement (no fixed shape); in a gas, they are far apart with no regular arrangement (no fixed shape). Particles in a solid vibrate about fixed positions (cannot flow) and do not generally move in relation to one another; in a liquid, they move past each other (can flow) but remain in essentially constant contact; in a gas, they move...
42.5K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

81
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
81

You might also read

Related Articles

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

Sort by
Same author

Identification of chemical features for improved outer membrane permeation in mycobacteria using machine learning.

Nature microbiology·2026
Same author

Conformational variability of HIV-1 Env trimer and viral vulnerability.

eLife·2026
Same author

Dynamic architecture of mycobacterial outer membranes revealed by all-atom simulations.

eLife·2026
Same author

Coarse-Grained Simulations of Mycobacterial Outer Membranes Reveal Fluidity-Dependent PDIM Redistribution across Different Lipid Environments.

Biomacromolecules·2026
Same author

Influence of Lipomannan and Lipoarabinomannan Concentration on Mycobacterial Inner Membranes Characterized by All-atom Simulations.

bioRxiv : the preprint server for biology·2026
Same author

Structural basis of fungal β-1,3-glucan synthase inhibition by caspofungin.

Nature·2026
Same journal

The Role of Functional Groups in Substituted Benzoic Acids Used as Dopants in Liquid Crystal Mixtures on the Nematic-Isotropic Transitions.

The journal of physical chemistry. B·2026
Same journal

Hyperfine Coupling Quantifies Hole Delocalization in Triarylamine Radical Cations of D-χ-A Molecules.

The journal of physical chemistry. B·2026
Same journal

A Solvatochromic-Chemometric Framework to Resolve Subtle Polarity Microenvironment Differences in Cycloalkanes Driven by Molecular Conformation and Substituent Effects: A Proof-Of-Concept for Advanced Aviation Fuel Design.

The journal of physical chemistry. B·2026
Same journal

Selective Effects of Backbone Cyclization and Disulfide Bonding as Global Covalent Constraints on the Conformational Ensemble of Sunflower Trypsin Inhibitor-1.

The journal of physical chemistry. B·2026
Same journal

Europium Coordination Structure in Peptide Complexes Resolved with Simulation and X-ray Absorption Spectroscopy.

The journal of physical chemistry. B·2026
Same journal

Competitive Coordination and Structural Evolution of Phenylalanine-Mg<sup>2+</sup> Complexes in Microaqueous Environments: Insights from DFT and Molecular Dynamics Simulations.

The journal of physical chemistry. B·2026
See all related articles

Related Experiment Video

Updated: Aug 28, 2025

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches
07:31

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches

Published on: September 1, 2023

2.4K

CHARMM-GUI Implicit Solvent Modeler for Various Generalized Born Models in Different Simulation Programs.

Kye Won Wang1, Jumin Lee1, Han Zhang1

  • 1Departments of Biological Sciences, Chemistry, Bioengineering, and Computer Science and Engineering, Lehigh University, Bethlehem, Pennsylvania 18015, United States.

The Journal of Physical Chemistry. B
|September 19, 2022
PubMed
Summary
This summary is machine-generated.

Implicit solvent models speed up molecular simulations by reducing solvent complexity. The Implicit Solvent Modeler (ISM) in CHARMM-GUI offers a reliable tool for various generalized Born implicit solvent simulations.

More Related Videos

Deciphering the Structural Effects of Activating EGFR Somatic Mutations with Molecular Dynamics Simulation
15:05

Deciphering the Structural Effects of Activating EGFR Somatic Mutations with Molecular Dynamics Simulation

Published on: May 20, 2020

8.7K
Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs
05:00

Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs

Published on: August 9, 2024

1.4K

Related Experiment Videos

Last Updated: Aug 28, 2025

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches
07:31

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches

Published on: September 1, 2023

2.4K
Deciphering the Structural Effects of Activating EGFR Somatic Mutations with Molecular Dynamics Simulation
15:05

Deciphering the Structural Effects of Activating EGFR Somatic Mutations with Molecular Dynamics Simulation

Published on: May 20, 2020

8.7K
Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs
05:00

Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs

Published on: August 9, 2024

1.4K

Area of Science:

  • Computational chemistry
  • Molecular dynamics simulations
  • Biomolecular modeling

Background:

  • Implicit solvent models accelerate molecular simulations by reducing solvent degrees of freedom.
  • CHARMM-GUI is a web platform for setting up complex molecular systems and preparing input files.

Purpose of the Study:

  • To introduce the Implicit Solvent Modeler (ISM) within CHARMM-GUI.
  • To support generalized Born (GB) implicit solvent simulations across multiple molecular dynamics programs.
  • To validate ISM's utility for protein, DNA, RNA, glycan, and ligand systems.

Main Methods:

  • Developed an Implicit Solvent Modeler (ISM) integrated into CHARMM-GUI.
  • Implemented various generalized Born (GB) models (GB-HCT, GB-OBC, GB-neck, GBMV, GBSW).
  • Supported CHARMM and Amber force fields for diverse biomolecular systems and molecular dynamics packages (AMBER, CHARMM, GENESIS, NAMD, OpenMM, Tinker).

Main Results:

  • Implicit solvent simulations using ISM-generated files yielded consistent results across different simulation packages for protein, DNA, and RNA systems.
  • Protein-ligand simulations demonstrated that implicit solvent methods outperform docking for early-stage screening.
  • Calculations such as root-mean-square deviation (RMSD) and MM/GBSA validated ISM's performance.

Conclusions:

  • The Implicit Solvent Modeler (ISM) is a valuable and dependable tool for diverse implicit solvent simulation applications.
  • ISM facilitates efficient setup and execution of molecular dynamics simulations with implicit solvent models.
  • The tool aids in accelerating drug discovery and understanding biomolecular interactions.