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

Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses 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...
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...
Protein-protein Interfaces02:04

Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a polypeptide...
The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

The equilibrium binding constant (Kb) quantifies the strength of a protein-ligand interaction. Kb can be calculated as follows when the reaction is at equilibrium:

You might also read

Related Articles

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

Sort by
Same author

5,5'-Methylenedisalicylic Acid Derivatives as Inhibitors of the Protein Phosphatase CppA in <i>Chlamydia trachomatis</i>.

ACS medicinal chemistry letters·2026
Same author

Factors Driving Amyloid Beta Fibril Recognition by Cell Surface Receptors: A Computational Study.

Molecules (Basel, Switzerland)·2025
Same author

Elucidating structural and molecular requirements of somatostatin subtype-4 agonist bound complexes using quantum mechanics approaches.

Organic & biomolecular chemistry·2025
Same author

3-Thio-3,4,5-trisubstituted-1,2,4-triazoles: high affinity somatostatin receptor-4 agonist synthesis and structure-activity relationships.

RSC medicinal chemistry·2024
Same author

Equilibrium landscape of ingress/egress channels and gating residues of the Cytochrome P450 3A4.

PloS one·2024
Same author

Library size in virtual screening: is it truly a number's game?

Expert opinion on drug discovery·2022
Same journal

Correction to "AstraMEV (AI-Guided Structural Assembly of Multi-Epitope Vaccines) Against Infectious Bronchitis Virus".

Journal of chemical information and modeling·2026
Same journal

MolPy: A Large Language Model-Friendly Toolkit for Reactive Topology Editing in Polymer Simulations.

Journal of chemical information and modeling·2026
Same journal

Molecular Mechanisms of KIT Receptor Dimerization and Oncogenic Activation Revealed by Multiscale Simulations.

Journal of chemical information and modeling·2026
Same journal

Structural and Thermodynamic Discrimination between Agonists and Antagonists of Retinoic Acid Receptor γ and the Vitamin D Receptor.

Journal of chemical information and modeling·2026
Same journal

PACEff Builder: An Efficient Platform for Constructing PACE Hybrid-Resolution Models for Molecular Dynamics Simulations of Aqueous Protein, Peptide Assembly, and Membrane Protein Systems.

Journal of chemical information and modeling·2026
Same journal

TransKla: A Local-Global Cross-Attention Based Transformer Approach for Prediction of Lysine Lactylation Sites.

Journal of chemical information and modeling·2026
See all related articles

Related Experiment Video

Updated: May 24, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Functional prediction of binding pockets.

Maria Kontoyianni1, Christopher B Rosnick

  • 1Department of Pharmaceutical Sciences, Southern Illinois University Edwardsville, Edwardsville, Illinois 62026, USA. mkontoy@siue.edu

Journal of Chemical Information and Modeling
|February 23, 2012
PubMed
Summary
This summary is machine-generated.

Predicting protein function is challenging. This study introduces a novel method using ligand-binding cavity properties and statistical analysis to accurately classify protein function, improving upon traditional sequence and structure comparisons.

More Related Videos

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Protein Target Prediction and Validation of Small Molecule Compound
10:21

Protein Target Prediction and Validation of Small Molecule Compound

Published on: February 23, 2024

Related Experiment Videos

Last Updated: May 24, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Protein Target Prediction and Validation of Small Molecule Compound
10:21

Protein Target Prediction and Validation of Small Molecule Compound

Published on: February 23, 2024

Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Protein Function Prediction

Background:

  • Traditional methods for predicting protein function rely on sequence and structural homology, which have limitations in accuracy and scope.
  • Determining functional similarity based on sequence identity percentages or global structural folds can be unreliable.
  • There is a need for robust methods to predict the function of proteins lacking known ligands.

Purpose of the Study:

  • To develop and validate a novel computational approach for classifying protein function.
  • To predict the putative function of proteins, particularly those without known ligands.
  • To assess the efficacy of using ligand-binding cavity properties for protein classification.

Main Methods:

  • Calculated structural, physicochemical, and geometric descriptors for ligand-binding cavities across 434 protein complexes from 17 protein families.
  • Employed statistical methods, specifically discriminant function analysis (DFA), to analyze these descriptors.
  • Validated the best DFA model using classification rates and cross-validation.

Main Results:

  • The optimal discriminant function analysis model, utilizing 371 proteins from 15 families, achieved a 90% correct classification rate and 86% cross-validation accuracy.
  • Testing DFA with a single protein against a random sample of others resulted in 100% correct prediction of putative function for 10 out of 15 protein families.
  • The study demonstrates that ligand-binding cavity properties are effective predictors of protein function.

Conclusions:

  • The developed method based on ligand-binding cavity analysis offers a more accurate and reliable approach to protein function prediction.
  • This approach overcomes limitations of traditional sequence and structure-based methods, especially for proteins with unknown ligands.
  • The findings have significant implications for annotating protein function in large-scale biological datasets and drug discovery.