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

Rigid Body Equilibrium Problems - II01:21

Rigid Body Equilibrium Problems - II

A rigid body is in static equilibrium when the net force and the net torque acting on the system are equal to zero.
Consider two children sitting on a seesaw, which has negligible mass. The first child has a mass (m1) of 26 kg and sits at point A, which is 1.6 meters (r1) from the pivot point B; the second child has a mass (m2) of 32 kg and sits at point C. How far from the pivot point B should the second child sit (r2) to balance the seesaw?
Rigid Body Equilibrium Problems - I00:49

Rigid Body Equilibrium Problems - I

A rigid body is said to be in static equilibrium when the net force and the net torque acting on the system is equal to zero. To solve for rigid body equilibrium problems, do the following steps.
Stability of structures01:14

Stability of structures

In mechanical engineering, the stability of systems under various forces is critical for designing durable and efficient structures. One fundamental way to explore these concepts is by analyzing systems like two rods connected at a pivot point, O, with a torsional spring of spring constant k at the pivot point. This system is similar in appearance to a scissor jack used to change tires on a car. In this case, the arms of the linkage (equivalent to the rods in this system) are entirely vertical,...
Virtual Work for a System of Connected Rigid Bodies01:06

Virtual Work for a System of Connected Rigid Bodies

Virtual work is a powerful method used to solve problems involving several connected rigid bodies. When the system is in equilibrium, virtual work is zero. This allows the calculation of the resulting forces when a system undergoes a virtual displacement. When attempting to analyze such a system, first, use a free-body diagram, where an independent coordinate represents the configuration of the links, and mark its deflected position resulting from the positive virtual displacement.
Next,...
Stability of Equilibrium Configuration01:23

Stability of Equilibrium Configuration

Understanding the stability of equilibrium configurations is a fundamental part of mechanical engineering. In any system, there are three distinct types of equilibrium: stable, neutral, and unstable.
A stable equilibrium occurs when a system tends to return to its original position when given a small displacement, and the potential energy is at its minimum. An example of a stable equilibrium is when a cantilever beam is fixed at one end and a weight is attached to the other end. If the weight...
Molecular Models02:00

Molecular Models

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.

You might also read

Related Articles

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

Sort by
Same author

FeSseqdb: a curated sequence-level database and interpretable machine learning framework for identifying iron-sulfur proteins.

BMC bioinformatics·2026
Same author

Machine Learning-Driven Drug Repurposing for KRAS G12C and KRAS G12D Inhibition.

ACS omega·2026
Same author

Functional dynamics of water in New Delhi metallo-β-lactamase catalysis.

Protein science : a publication of the Protein Society·2026
Same author

Multiscale machine learning molecular mechanics for mechanism and stereoselectivity of Diels-Alderase catalysis.

Nature communications·2026
Same author

Comparison of Protein-Glycosaminoglycan Interactions in ff14sb/GLYCAM06j-1 and CHARMM36m Force Fields.

Journal of chemical information and modeling·2026
Same author

Unlocking efficient near-infrared circularly polarized phosphorescence reaching 800 nm in cyclometalated Pt(II) complexes.

Chemical communications (Cambridge, England)·2026
Same journal

Anharmonic phonons via quantum thermal bath simulations.

The Journal of chemical physics·2026
Same journal

Quantum simulation of alignment dependent differential cross sections in co-propagating molecular beams at cold collision energies.

The Journal of chemical physics·2026
Same journal

Non-additive ion effects on the coil-globule equilibrium of a generic polymer in aqueous salt solutions.

The Journal of chemical physics·2026
Same journal

Insights into the unexpected small reduction of the temperature of maximum density of water by lithium chloride addition.

The Journal of chemical physics·2026
Same journal

Optical frequency comb double-resonance spectroscopy of the 9030-9175 cm-1 states of ethylene.

The Journal of chemical physics·2026
Same journal

Time reversal breaking of colloidal particles in cells.

The Journal of chemical physics·2026
See all related articles

Related Experiment Video

Updated: May 18, 2026

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

Maintain rigid structures in Verlet based cartesian molecular dynamics simulations.

Peng Tao1, Xiongwu Wu, Bernard R Brooks

  • 1Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.

The Journal of Chemical Physics
|October 9, 2012
PubMed
Summary
This summary is machine-generated.

A new algorithm, SHAPE, maintains rigid structures in molecular dynamics (MD) simulations efficiently. This method offers greater applicability and speed compared to existing techniques like SHAKE.

More Related Videos

Modeling Ligands into Maps Derived from Electron Cryomicroscopy
09:30

Modeling Ligands into Maps Derived from Electron Cryomicroscopy

Published on: July 19, 2024

Related Experiment Videos

Last Updated: May 18, 2026

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

Modeling Ligands into Maps Derived from Electron Cryomicroscopy
09:30

Modeling Ligands into Maps Derived from Electron Cryomicroscopy

Published on: July 19, 2024

Area of Science:

  • Computational chemistry
  • Molecular dynamics simulations
  • Biophysics

Background:

  • Maintaining rigid structures is crucial in molecular dynamics (MD) simulations for accuracy and efficiency.
  • Existing methods like SHAKE can be computationally intensive and have limitations in applicability.
  • Cartesian-based MD simulations require robust algorithms for handling constraints.

Purpose of the Study:

  • To introduce a novel algorithm, SHAPE, for preserving rigid structures in Cartesian-based MD simulations.
  • To develop an efficient and broadly applicable alternative to the SHAKE algorithm.
  • To demonstrate the accuracy and reliability of the SHAPE method in complex systems.

Main Methods:

  • An iterative procedure using rotation matrix computation corrects particle coordinates after each unconstrained MD step.
  • The SHAPE algorithm is implemented within the CHARMM program suite.
  • It avoids Lagrange multipliers, ensuring computational complexity is independent of the number of particles in a rigid structure.

Main Results:

  • SHAPE demonstrates accuracy and reliability comparable to the SHAKE method in numerical tests.
  • The algorithm shows significantly greater applicability, especially for large linear and planar rigid bodies.
  • Tests on proteins and other model systems confirm SHAPE's efficiency.

Conclusions:

  • The SHAPE algorithm provides an efficient and versatile method for maintaining rigid structures in MD simulations.
  • It offers a valuable alternative to SHAKE, particularly for complex molecular systems.
  • SHAPE's design allows easy integration into existing MD simulation frameworks.