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

37.4K
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.
37.4K
Molecular Shapes01:18

Molecular Shapes

53.5K
Molecules have characteristic shapes that are crucial for their function. The arrangement of various electron groups around the central atom dictates their molecular geometry. Electron pairs in the valence shell of a central atom will adopt an arrangement that minimizes repulsions between the electron pairs by maximizing the distance between them. The valence electrons form either bonding pairs, located primarily between bonded atoms, or lone pairs.
Two regions of electron density in a diatomic...
53.5K
Structure of Amines01:19

Structure of Amines

2.5K
The hybridized nitrogen atom in amines possesses a lone pair of electrons and is bound to three substituents with a bond angle of around 108°, which is less than the tetrahedral angle of 109.5°. However, the C–N–H bond angle is slightly larger at 112°, with a carbon–nitrogen bond length of 147 pm. This carbon–nitrogen bond length of of amines is longer than the carbon–oxygen bond of alcohols (143 pm) but shorter than alkanes’...
2.5K
Newman Projections02:06

Newman Projections

16.8K
Different notations are used to represent the three-dimensional structure of molecules on two-dimensional surfaces. One of the most commonly used representations is the dash-wedge formula. The dashed wedges, solid wedges, and the plane lines indicate the groups situated behind the plane, coming out of the plane, and in the plane, respectively.
The organic molecules rotate across the single bonds leading to numerous temporary three-dimensional structures of varying energy known as...
16.8K
Cell Diagrams and IUPAC Conventions01:21

Cell Diagrams and IUPAC Conventions

143
Electrochemical cell notation is a standardized symbolic representation that communicates the structure and reaction pathway of galvanic and electrolytic cells. This notation plays a critical role in describing redox reactions and electrochemical cell configurations without the need for detailed diagrams.In electrochemical cell notation, a single vertical line “|” denotes a phase boundary, such as between a solid electrode and an aqueous solution. A double vertical line...
143
Structures of Carboxylic Acid Derivatives01:28

Structures of Carboxylic Acid Derivatives

3.1K
Structure of Carboxylic Acid Derivatives
Carboxylic acid derivatives contain an acyl group attached to a heteroatom such as chlorine, oxygen, or nitrogen. The carbonyl carbon and oxygen are both sp2-hybridized with an unhybridized p orbital.
The three sp2 orbitals of the carbonyl carbon form three σ bonds, one each with the carbonyl oxygen, the α carbon, and the heteroatom, whereas the other two sp2 orbitals of the carbonyl oxygen are occupied by the lone pairs. Further, the...
3.1K

You might also read

Related Articles

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

Sort by
Same author

Exploratory transcriptomic and network-based analysis of methylmercury exposure in human neuronal developmental models using GEO datasets and toxicogenomic resources.

Neurotoxicology·2026
Same author

Chemical profile of Thalassia testudinum under coastal pollution: Assessment of mercury, VOCs and secondary metabolites in the Colombian Caribbean.

Marine pollution bulletin·2026
Same author

Computational Identification of Potential Novel Allosteric IHF Inhibitors Using QSAR Modeling to Inhibit Plasmid-Mediated Antibiotic Resistance.

International journal of molecular sciences·2026
Same author

In silico discovery of thioglycoside analogues as donor-site inhibitors of glycosyltransferase LgtC.

Scientific reports·2026
Same author

A 2026 Update on Computational Approaches to the Discovery and Design of Antimicrobial Peptides.

Antibiotics (Basel, Switzerland)·2026
Same author

Hybrid Computational Framework Integrating Ensemble Learning, Molecular Docking, and Dynamics for Predicting Antimalarial Efficacy of Malaria Box Compounds.

International journal of molecular sciences·2026

Related Experiment Video

Updated: Apr 28, 2026

Author Spotlight: Exploring Cellular Processes by Modeling Ligands in Cryo-EM Maps
09:30

Author Spotlight: Exploring Cellular Processes by Modeling Ligands in Cryo-EM Maps

Published on: July 19, 2024

2.9K

N-linear algebraic maps for chemical structure codification: a suitable generalization for atom-pair approaches?

Cesar R Garcia-Jacas, Yovani Marrero-Ponce, Stephen J Barigye

  • 1Unit of Computer-Aided Molecular "Biosilico" Discovery and Bioinformatic Research (CAMD-BIR Unit), Faculty of Chemistry-Pharmacy. Universidad Central "Martha Abreu" de Las Villas, Santa Clara, 54830, Villa Clara, Cuba. ymarrero77@yahoo.es.

Current Drug Metabolism
|June 10, 2014
PubMed
Summary
This summary is machine-generated.

A novel 3D-QSAR alignment-free method, QuBiLS-MIDAS, uses tensor concepts for molecular descriptor calculation. This method shows superior performance in predicting binding affinity compared to existing chemoinformatics tools.

More Related Videos

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

2.5K
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

Related Experiment Videos

Last Updated: Apr 28, 2026

Author Spotlight: Exploring Cellular Processes by Modeling Ligands in Cryo-EM Maps
09:30

Author Spotlight: Exploring Cellular Processes by Modeling Ligands in Cryo-EM Maps

Published on: July 19, 2024

2.9K
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

2.5K
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

Area of Science:

  • Chemoinformatics
  • Computational Chemistry
  • Quantitative Structure-Activity Relationship (QSAR) studies

Background:

  • Traditional 3D-QSAR methods often require molecular alignment, which can introduce biases.
  • There is a need for alignment-free methods that can efficiently capture complex 3D molecular information.

Purpose of the Study:

  • Introduce QuBiLS-MIDAS, a novel alignment-free 3D-QSAR method based on tensor algebra.
  • Develop new molecular descriptors using n-tuple spatial (dis)similarity matrices.
  • Evaluate the performance of QuBiLS-MIDAS in predicting binding affinity.

Main Methods:

  • Defined three-tuple and four-tuple spatial-(dis)similarity matrices as tensors of order 3 and 4.
  • Utilized multi-metrics and normalization schemes for these tensors.
  • Introduced n-tuple path and length cut-off constraints to consider atomic interactions.
  • Performed variability analysis using Shannon's entropy and principal component analysis.
  • Conducted a QSAR study on corticosteroid-binding globulin affinity using Cramer's steroid database.

Main Results:

  • The ternary and quaternary measures, corresponding to bond and dihedral angles, showed optimal variability.
  • QuBiLS-MIDAS indices demonstrated superior entropy behavior compared to descriptors from DRAGON, PADEL, and Mold2.
  • Principal component analysis indicated that QuBiLS-MIDAS indices capture information comparable to and beyond DRAGON 3D-indices.
  • QSAR studies revealed superior statistical parameters for Bond Angle and Dihedral Angle approaches.
  • QuBiLS-MIDAS models outperformed existing 3D-QSAR methods in predicting steroid binding affinity.

Conclusions:

  • QuBiLS-MIDAS offers a robust, alignment-free approach for 3D-QSAR studies.
  • The novel n-tuple indices derived from tensor concepts are valuable for chemoinformatics.
  • The method provides enhanced predictive power for molecular binding affinities.