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 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.
Protein Diffusion in the Membrane01:24

Protein Diffusion in the Membrane

Proteins show rotational as well as lateral diffusion across the membrane. The lateral diffusion of proteins was confirmed through the cell fusion experiment where mouse and human cells were fused, resulting in hybrid cells. When the human and mouse cells fused, the specific membrane proteins on human and mouse cells were marked with the red and green-fluorescent markers, respectively. Initially, the red and green fluorescence was located on the respective hemisphere of the cell. As time...
Distribution of Molecular Speeds01:27

Distribution of Molecular Speeds

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...
Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion03:48

Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion

Although gaseous molecules travel at tremendous speeds (hundreds of meters per second), they collide with other gaseous molecules and travel in many different directions before reaching the desired target. At room temperature, a gaseous molecule will experience billions of collisions per second. The mean free path is the average distance a molecule travels between collisions. The mean free path increases with decreasing pressure; in general, the mean free path for a gaseous molecule will be...
Predicting Molecular Geometry02:27

Predicting Molecular Geometry

VSEPR Theory for Determination of Electron Pair Geometries
Molecular Geometry and Dipole Moments02:36

Molecular Geometry and Dipole Moments

The VSEPR theory can be used to determine the electron pair geometries and molecular structures as follows:

You might also read

Related Articles

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

Sort by
Same author

MISSTE: a multiscale integrative spatial simulator for understanding the mechanisms underlying tissue ecosystems.

Computers in biology and medicine·2026
Same author

Functionalization Enhanced Phase Separation in PS-b-PVP Derived Polyzwitterionic Block Copolymers.

Macromolecular rapid communications·2026
Same author

SIMCROST: A Simulator for Understanding the Spatial Regulation in Cross-Membrane Signal Transduction.

Chembiochem : a European journal of chemical biology·2026
Same author

Inferring dynamic information from protein structures by Gaussian integrals and deep learning.

Bioinformatics (Oxford, England)·2026
Same author

Galectin-8 Modulates Membrane CD44v Localization and Tempers STAT3 Signaling in Gastric Metaplasia.

bioRxiv : the preprint server for biology·2026
Same author

Galectin-3 is Necessary for Selective Cathartocytosis, which Expedites the Development of Proliferative Gastric SPEM.

bioRxiv : the preprint server for biology·2026

Related Experiment Video

Updated: Jul 17, 2026

New Features in Visual Dynamics 3.0
05:00

New Features in Visual Dynamics 3.0

Published on: August 9, 2024

EvoDiffMol: evolutionary diffusion framework for 3D molecular design with optimized properties.

Xiaobo Lin1, Logan T Kearney2, Zhaoqian Su3

  • 1Carbon and Composites Group, Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA. linx1@ornl.gov.

Journal of Cheminformatics
|July 16, 2026
PubMed
Summary

EvoDiffMol generates novel molecules using 3D diffusion models and evolutionary algorithms. This computational framework achieves top drug-likeness scores and optimizes multiple properties for drug discovery.

Keywords:
3D molecular generationDiffusion modelsGenetic algorithmsInverse molecular designProperty optimizationStructural constraints

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

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis
11:29

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

Published on: December 18, 2014

Related Experiment Videos

Last Updated: Jul 17, 2026

New Features in Visual Dynamics 3.0
05:00

New Features in Visual Dynamics 3.0

Published on: August 9, 2024

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

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis
11:29

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

Published on: December 18, 2014

Area of Science:

  • Computational Chemistry
  • Molecular Modeling
  • Artificial Intelligence in Chemistry

Background:

  • Designing molecules with desired properties is a key challenge.
  • Existing methods often use 2D representations, missing crucial 3D geometric data.

Purpose of the Study:

  • Introduce EvoDiffMol, a novel framework for property-driven molecular generation.
  • Integrate evolutionary algorithms with 3D diffusion models for enhanced molecular design.

Main Methods:

  • Utilize adaptive evolutionary optimization with population-based selection.
  • Incorporate three-dimensional diffusion models for molecular generation.
  • Support both unconstrained and scaffold-constrained molecular design.

Main Results:

  • Achieved the highest drug-likeness score (0.94) among state-of-the-art methods.
  • Demonstrated excellent validity, uniqueness, and novelty in generated molecules.
  • Successfully performed single and multi-property optimization, including ADMET endpoints.

Conclusions:

  • EvoDiffMol offers a powerful, adaptable approach for molecular generation.
  • The 3D representation enhances structural validity and has potential in materials science and drug discovery.
  • The framework precisely controls target property values for practical pharmaceutical applications.