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

Metal-Ligand Bonds02:51

Metal-Ligand Bonds

20.8K
The hemoglobin in the blood, the chlorophyll in green plants, vitamin B-12, and the catalyst used in the manufacture of polyethylene all contain coordination compounds. Ions of the metals, especially the transition metals, are likely to form complexes.
In these complexes, transition metals form coordinate covalent bonds, a kind of Lewis acid-base interaction in which both of the electrons in the bond are contributed by a donor (Lewis base) to an electron acceptor (Lewis acid). The Lewis acid in...
20.8K
Complexometric Titration: Ligands00:43

Complexometric Titration: Ligands

961
Different monodentate and polydentate ligands are used as complexing agents in complexometric titration reactions. The formation of complexes by mono- and bidentate ligands involves two or more intermediate steps, limiting their use as complexing agents. In comparison, polydentate ligands can form complexes with metal ions in a single-step process, facilitating sharper end points. This means polydentate ligands, such as amino carboxylic acid derivatives, are most commonly employed in...
961
Valence Bond Theory02:42

Valence Bond Theory

8.6K
Coordination compounds and complexes exhibit different colors, geometries, and magnetic behavior, depending on the metal atom/ion and ligands from which they are composed. In an attempt to explain the bonding and structure of coordination complexes, Linus Pauling proposed the valence bond theory, or VBT, using the concepts of hybridization and the overlapping of the atomic orbitals. According to VBT, the central metal atom or ion (Lewis acid) hybridizes to provide empty orbitals of suitable...
8.6K
Ligand Binding Sites02:40

Ligand Binding Sites

12.9K
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...
12.9K
Complexation Equilibria: Factors Influencing Stability of Complexes01:09

Complexation Equilibria: Factors Influencing Stability of Complexes

376
In complexation reactions, metal cations are the electron pair acceptors, and the ligands are the electron pair donors. The stability of the metal complexes depends primarily on the complexing ability of the central metal ion and the nature of the ligands. Generally, the complexing ability of the metal ion depends on the size and charge of the ion. As the metal ion size increases, the stability of the metal complexes decreases, provided that the valency of the metal ion and the ligands remain...
376
Complexation Equilibria: The Chelate Effect01:19

Complexation Equilibria: The Chelate Effect

520
In complexation reactions, metal atoms or cations interact with ligands to form donor-acceptor adducts called metal complexes. Ligands that bind through one donor site are monodentate, ligands with two donor sites are bidentate, and those with more than two donor sites are polydentate ligands. For example, ethylene diamine is a bidentate ligand that binds through two nitrogen donor atoms, forming a five-membered ring. EDTA is a polydentate ligand that binds through four oxygen and two nitrogen...
520

You might also read

Related Articles

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

Sort by
Same author

Side-Chain-Based Cross-Linking of Amorphous Iono-Electronic Conductive Polymers for Thermo-Chemical Stability in Electrochemical Devices.

ACS applied materials & interfaces·2026
Same author

High-Throughput Discovery of Conformation-Switching Mechanophores with Enhanced Reactivity and Stability.

Inorganic chemistry·2026
Same author

Mechanophore cross-linking enhances ballistic energy dissipation of polymers.

Nature·2026
Same author

QuantumPDB: A Workflow for High-Throughput Quantum Cluster Model Generation from Protein Structures.

Journal of chemical information and modeling·2026
Same author

Mammalian-like steroidogenesis in plants gives rise to endocrine-mimetic cardenolides.

Science advances·2026
Same author

pyEF: A Python Framework for QM and QM/MM Atom-Wise Electric Field Analysis.

Journal of chemical theory and computation·2026

Related Experiment Video

Updated: Jul 9, 2025

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
10:21

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA

Published on: February 23, 2024

2.6K

Discovering Molecular Coordination Environment Trends for Selective Ion Binding to Molecular Complexes Using Machine

Shuwen Yue1, Aditya Nandy1,2, Heather J Kulik1,2

  • 1Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.

The Journal of Physical Chemistry. B
|December 1, 2023
PubMed
Summary
This summary is machine-generated.

Designing ion-selective materials is crucial. This study found that chemical interactions, not just ion size, dictate selectivity in molecular complexes, guiding the development of better membranes.

More Related Videos

Structure and Coordination Determination of Peptide-metal Complexes Using 1D and 2D 1H NMR
14:44

Structure and Coordination Determination of Peptide-metal Complexes Using 1D and 2D 1H NMR

Published on: December 16, 2013

9.6K
Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
08:49

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

196

Related Experiment Videos

Last Updated: Jul 9, 2025

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
10:21

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA

Published on: February 23, 2024

2.6K
Structure and Coordination Determination of Peptide-metal Complexes Using 1D and 2D 1H NMR
14:44

Structure and Coordination Determination of Peptide-metal Complexes Using 1D and 2D 1H NMR

Published on: December 16, 2013

9.6K
Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
08:49

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

196

Area of Science:

  • Materials Science
  • Computational Chemistry
  • Physical Chemistry

Background:

  • Developing effective ion-selective materials is essential for various applications, but current technologies face limitations.
  • Understanding ion binding within confined spaces, like membrane ion channels, is key to improving selectivity.
  • Small molecular complexes can serve as simplified models for studying ion channel behavior.

Purpose of the Study:

  • To investigate design features in molecular complexes that influence ion selectivity.
  • To understand the energetic basis for preferential binding of alkali metal ions (Li+, Na+, K+).
  • To identify key chemical and geometric factors governing ion selectivity.

Main Methods:

  • Curated a dataset of 563 alkali metal coordinating molecular complexes from the Cambridge Structural Database.
  • Calculated differential ion binding energies using density functional theory (DFT).
  • Employed machine learning models to analyze geometric and electronic features influencing ion binding.

Main Results:

  • Energetic preferences for ion binding are primarily driven by chemical interactions, not solely by ion size or structural changes.
  • Identified specific trends favoring Lithium ion (Li+) selectivity: presence of Nitrogen coordination atoms, planar geometry, and small ring sizes.
  • Machine learning models successfully predicted selective ion binding based on identified features.

Conclusions:

  • Chemical interactions, particularly coordination environment, are critical for achieving ion selectivity in molecular systems.
  • These findings provide insights for designing advanced ion-selective membranes.
  • The data-driven approach offers a pathway for optimizing materials for specific ion separations.