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

Crystal Field Theory - Octahedral Complexes02:58

Crystal Field Theory - Octahedral Complexes

Crystal Field Theory
To explain the observed behavior of transition metal complexes (such as colors), a model involving electrostatic interactions between the electrons from the ligands and the electrons in the unhybridized d orbitals of the central metal atom has been developed. This electrostatic model is crystal field theory (CFT). It helps to understand, interpret, and predict the colors, magnetic behavior, and some structures of coordination compounds of transition metals.
CFT focuses on...
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.
Fischer Projections02:18

Fischer Projections

Learning to draw Fischer projections of molecules and understanding their relevance plays a crucial role in the visual depiction of organic molecules. A Fischer projection is a two-dimensional projection on a planar surface to simplify the three-dimensional wedge–dash representation of molecules. This is especially helpful in the case of molecules with multiple chiral centers that can be difficult to draw. Here, all the bonds of interest are represented as horizontal or vertical lines. While...
Ligand Binding Sites02:40

Ligand Binding Sites

Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
Ligand Binding Sites02:40

Ligand Binding Sites

Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
Two-Dimensional (2D) NMR: Overview01:12

Two-Dimensional (2D) NMR: Overview

The 1D NMR spectrum of large and complex molecules like natural products has complicated splitting patterns and overlapping signals, which can be easily interpreted using 2-dimensional (2D) NMR. Unlike 1D NMR, 2D NMR has two frequency axes that provide the coupling information between the nucleus A and nucleus B in a molecule. The process from which 2D spectra are obtained has four steps.
The first step is the preparation period, during which nucleus A is excited with a radiofrequency pulse.

You might also read

Related Articles

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

Sort by
Same author

PegaPlus─Interactive Machine Learning by Human Observation for Efficient Clustering and Analysis of Structure-Activity Data.

Journal of chemical information and modeling·2026
Same author

Enabling Automatic Generation of Protein-Ligand Complex Data Sets with Atomistic Detail.

Journal of chemical information and modeling·2026
Same author

Guiding Similarity Search in Chemical Fragment Spaces with Weighted Fingerprints.

Journal of chemical information and modeling·2026
Same author

ActivityFinder: Toward the Fully Automatic Integration of Structural and Binding Affinity Data.

Journal of chemical information and modeling·2026
Same author

A bottom-up approach to find lead compounds in expansive chemical spaces.

Communications chemistry·2025
Same author

Correction: SAVI Space-combinatorial encoding of the billion-size synthetically accessible virtual inventory.

Scientific data·2025
Same journal

Computational design of low-volatility lubricants for space using interpretable machine learning.

Journal of cheminformatics·2026
Same journal

OpenStats: how to combine statistics and research data management (RDM) to leverage efficient scientific data analysis by guided statistics.

Journal of cheminformatics·2026
Same journal

Unified heterogeneity-aware benchmark of drug synergy prediction: a cross-study analysis of traditional machine learning and graph deep learning models.

Journal of cheminformatics·2026
Same journal

Count your bits: fingerprint benchmarking to assess broad chemical space representation.

Journal of cheminformatics·2026
Same journal

Sampling out-of-distribution chemical spaces via Bayesian flow.

Journal of cheminformatics·2026
Same journal

Hold on tight: the kinetic profiling of opioid receptor ligands using the CORAL-MD.

Journal of cheminformatics·2026
See all related articles

Related Experiment Video

Updated: May 31, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

Consistent two-dimensional visualization of protein-ligand complex series.

Katrin Stierand1, Matthias Rarey

  • 1Center for Bioinformatics (ZBH), University of Hamburg, Bundesstraße 43, 20146 Hamburg, Germany. rarey@zbh.uni-hamburg.de.

Journal of Cheminformatics
|June 28, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces an automated method for consistently visualizing protein-ligand complexes. This approach enhances the analysis of large drug design datasets by improving layout legibility and comparability.

More Related Videos

Modeling an Enzyme Active Site using Molecular Visualization Freeware
14:37

Modeling an Enzyme Active Site using Molecular Visualization Freeware

Published on: December 25, 2021

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 31, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

Modeling an Enzyme Active Site using Molecular Visualization Freeware
14:37

Modeling an Enzyme Active Site using Molecular Visualization Freeware

Published on: December 25, 2021

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
  • Structural biology
  • Drug discovery

Background:

  • Comparative visualization of protein-ligand complexes aids in understanding binding mode differences.
  • Consistent residue placement in 2D representations improves legibility and comparability of complex series.
  • Automated layout generation is crucial for analyzing large datasets from computer-aided drug design (CADD).

Purpose of the Study:

  • To develop an automated approach for generating consistent 2D layouts of interacting residues in protein-ligand complex series.
  • To improve the visual analysis of large compound libraries in drug discovery.

Main Methods:

  • Developed an algorithm for automatic, consistent 2D layout generation of residues around a ligand.
  • Computed a global 2D layout based on 3D structural information and residue adjacencies.
  • Incorporated 2D ligand superposition and residue placement based on existing ligand positions.

Main Results:

  • Generated high-quality, mostly overlap-free 2D layouts for protein-ligand complex series.
  • Visualizations provide atomic detail of molecular interactions.
  • Demonstrated improved legibility compared to independently calculated layouts.

Conclusions:

  • The new method enhances complex series visualization by providing consistent graphical representations.
  • This approach simplifies the visual analysis of extensive compound series in drug discovery.
  • Extends current capabilities in visualizing molecular interactions for CADD.