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

Molecular Comparison of Gases, Liquids, and Solids02:26

Molecular Comparison of Gases, Liquids, and Solids

57.3K
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...
57.3K
Distribution of Molecular Speeds01:27

Distribution of Molecular Speeds

5.8K
The motion of molecules in a gas is random in magnitude and direction for individual molecules, but a gas of many molecules has a predictable distribution of molecular speeds. This predictable distribution of molecular speeds is known as the Maxwell-Boltzmann distribution. The distribution of molecular speeds in liquids is comparable to that of gases but not identical and can help to understand the phenomenon of the boiling and vapor pressure of a liquid. Consider that a molecule requires a...
5.8K
Molecular Models02:00

Molecular Models

44.9K
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.
44.9K
Molecular Kinetic Energy01:21

Molecular Kinetic Energy

5.8K
The word "gas" comes from the Flemish word meaning "chaos," first used to describe vapors by the chemist J. B. van Helmont. Consider a container filled with gas, with a continuous and random motion of molecules. During collisions, the velocity component parallel to the wall is unchanged, and the component perpendicular to the wall reverses direction but does not change in magnitude. If the molecule’s velocity changes in the x-direction, then its momentum is changed.
5.8K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

380
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...
380
Mean free path and Mean free time01:22

Mean free path and Mean free time

5.5K
Consider the gas molecules in a cylinder. They move in a random motion as they collide with each other and change speed and direction. The average of all the path lengths between collisions is known as the "mean free path."
5.5K

You might also read

Related Articles

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

Sort by
Same author

Transcatheter Mitral Valve-in-Valve Replacement With Microaxial Flow-Pump Support for Bioprosthetic Valve Failure.

JACC. Case reports·2026
Same author

Cytopenias and Functional Defects in a Novel Murine Model of VPS45 Severe Congenital Neutropenia.

bioRxiv : the preprint server for biology·2026
Same author

Transcatheter edge-to-edge mitral repair with a nitinol device in cardiogenic shock on micro-axial flow-pump support: a case report.

European heart journal. Case reports·2026
Same author

BIRC3 (Encoding Cellular Inhibitor of Apoptosis Protein 2) Variants Result in Dysregulated Receptor-Interacting Protein Kinase 1 Signaling Leading to Increased Epithelial Cell Death and Are Associated With Monogenic Crohn's Disease.

Gastroenterology·2026
Same author

A novel ELF4 gene variant disrupts T and NK cell function in a patient with immune thrombocytopenia (ITP).

Inflammation research : official journal of the European Histamine Research Society ... [et al.]·2026
Same author

Pediatric meningoencephalitis in the molecular diagnostic era: epidemiological insights from 1198 suspected cases in Germany between 2016 and 2024.

Infection·2026

Related Experiment Video

Updated: Mar 13, 2026

Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization
05:37

Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization

Published on: August 22, 2025

750

Lessons learned from comparing molecular dynamics engines on the SAMPL5 dataset.

Michael R Shirts1, Christoph Klein2, Jason M Swails3

  • 1Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder, CO, USA. michael.shirts@colorado.edu.

Journal of Computer-Aided Molecular Design
|October 28, 2016
PubMed
Summary

Preparing molecular simulation inputs for the SAMPL5 challenge revealed that while energies generally agree well across different programs, variations in Coulomb

Keywords:
Molecular dynamicsMolecular simulationSAMPL5Simulation validation

More Related Videos

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion
09:17

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

Published on: March 1, 2022

3.6K
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

2.0K

Related Experiment Videos

Last Updated: Mar 13, 2026

Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization
05:37

Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization

Published on: August 22, 2025

750
Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion
09:17

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

Published on: March 1, 2022

3.6K
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

2.0K

Area of Science:

  • Computational chemistry
  • Molecular dynamics simulations
  • Cheminformatics

Background:

  • Standardized input preparation is crucial for reproducible molecular simulations.
  • The SAMPL5 challenge requires diverse molecular simulation packages.

Purpose of the Study:

  • To automate the generation of common starting structures and models for the SAMPL5 blind prediction challenge.
  • To compare energy calculations across multiple molecular dynamics (MD) programs.

Main Methods:

  • Automated conversion of AMBER input files to GROMACS, LAMMPS, DESMOND, and CHARMM formats using ParmEd and InterMol.
  • Calculation of single-configuration potential energies for host-guest systems.
  • Analysis of energy discrepancies across different MD engines.

Main Results:

  • Energy calculations showed agreement better than 0.1% across MD engines with appropriate parameter choices.
  • Significant energy discrepancies were observed, primarily due to differing Coulomb's constant values between programs.
  • Program-specific default parameters also introduced notable energy differences.

Conclusions:

  • Automated conversion facilitates reproducible comparisons in molecular simulations.
  • Careful selection of simulation parameters, especially Coulomb's constant, is vital for inter-program energy agreement.
  • Understanding and addressing parameter variations are key to reliable blind prediction challenges.