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

44.7K
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.
44.7K
Experimental Determination of Chemical Formula02:37

Experimental Determination of Chemical Formula

48.4K
The elemental makeup of a compound defines its chemical identity, and chemical formulas are the most concise way of representing this elemental makeup. When a compound’s formula is unknown, measuring the mass of its constituent elements is often the first step in determining the formula experimentally.
48.4K
Chemical Shift: Internal References and Solvent Effects01:17

Chemical Shift: Internal References and Solvent Effects

1.5K
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...
1.5K
Predicting Molecular Geometry02:27

Predicting Molecular Geometry

46.6K
VSEPR Theory for Determination of Electron Pair Geometries
46.6K

You might also read

Related Articles

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

Sort by
Same author

Synthesis of 1,3-Disubstituted 3-Azabicyclo[3.2.0]heptane Libraries for Fragment-Based Drug Discovery.

Organic letters·2026
Same author

A Systematic Benchmark Study of Free Energy Methods for Quantifying Light-Responsive Binding Affinities of Photoswitchable Antagonists of Beta-Adrenergic Receptors.

Journal of medicinal chemistry·2026
Same author

Leveraging fragment-based drug discovery to advance 3D scaffolds into potent ligands: application to the histamine H<sub>1</sub> receptor.

RSC medicinal chemistry·2026
Same author

Optical control of H<sub>1</sub> receptor signaling with a BODIPY-photocaged antihistamine.

Biochemical pharmacology·2026
Same author

Correction to "Fragment-to-Lead Medicinal Chemistry Publications in 2024: A Tenth Annual Perspective".

Journal of medicinal chemistry·2026
Same author

The Concise Guide to PHARMACOLOGY 2025/26: G protein-coupled receptors.

British journal of pharmacology·2025

Related Experiment Video

Updated: Mar 8, 2026

Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods
05:34

Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods

Published on: June 6, 2025

1.8K

3D-e-Chem-VM: Structural Cheminformatics Research Infrastructure in a Freely Available Virtual Machine.

Ross McGuire1,2, Stefan Verhoeven3, Márton Vass4

  • 1Centre for Molecular and Biomolecular Informatics (CMBI), Radboudumc , 6525 GA Nijmegen, The Netherlands.

Journal of Chemical Information and Modeling
|January 27, 2017
PubMed
Summary

3D-e-Chem-VM is an open-source virtual machine integrating cheminformatics and bioinformatics tools for analyzing protein-ligand interactions. It facilitates novel approaches in virtual screening, metabolism prediction, and ligand design using structural and pharmacological data.

More Related Videos

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

8.8K
Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids
08:21

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

3.1K

Related Experiment Videos

Last Updated: Mar 8, 2026

Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods
05:34

Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods

Published on: June 6, 2025

1.8K
Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

8.8K
Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids
08:21

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

3.1K

Area of Science:

  • * Cheminformatics and Bioinformatics
  • * Computational Chemistry
  • * Structural Biology

Background:

  • * Analyzing protein-ligand interactions is crucial for drug discovery and understanding biological processes.
  • * Existing tools often lack integration, hindering comprehensive analysis of complex structural and pharmacological data.
  • * Proteome-wide databases and specialized information systems provide vast amounts of relevant data.

Purpose of the Study:

  • * To present 3D-e-Chem-VM, an integrated open-source virtual machine for analyzing protein-ligand interaction data.
  • * To provide a platform that combines cheminformatics and bioinformatics tools within a graphical programming environment.
  • * To enable new approaches in virtual ligand screening, metabolism prediction, and ligand design.

Main Methods:

  • * Development of an open-source Virtual Machine (3D-e-Chem-VM) integrating cheminformatics and bioinformatics software libraries.
  • * Incorporation of database and workflow tools for analyzing and combining small molecule and protein structural information.
  • * Creation of new data analytics tools and workflows for exploiting data from proteomewide databases (ChEMBLdb, PDB) and specialized systems (GPCRdb, KLIFS).

Main Results:

  • * 3D-e-Chem-VM offers a unified research infrastructure for structural cheminformatics.
  • * The platform supports novel applications including virtual ligand screening (Chemdb4VS), ligand-based metabolism prediction (SyGMa), and structure-based binding site analysis for ligand design (KRIPOdb).
  • * Enables efficient exploitation of diverse structural and pharmacological protein-ligand interaction data.

Conclusions:

  • * 3D-e-Chem-VM provides a powerful, integrated environment for advanced analysis of protein-ligand interactions.
  • * The developed tools and workflows facilitate innovative drug discovery and design strategies.
  • * This open-source platform enhances the accessibility and utility of complex biological and chemical data.