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...
Calmodulin-dependent Signaling01:16

Calmodulin-dependent Signaling

Calmodulin (CaM) is a calcium-binding protein in eukaryotes that controls various calcium-regulated cellular processes. It has four calcium-binding sites that bind calcium to form the calcium-calmodulin ( Ca2+-CaM) complex. GPCR stimulation increases the calcium levels in the cells that bind to CaM and induces a conformational change.
The Ca2+-CaM complex does not have enzymatic activity by itself. Instead, the complex binds downstream target proteins, including membrane proteins or enzymes,...
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence the...

You might also read

Related Articles

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

Sort by
Same author

GATSBI: improving context-aware protein embeddings through biologically motivated data splits.

Bioinformatics (Oxford, England)·2026
Same author

Atrial fibrillation type-specific prediction of recurrence after catheter ablation: the pivotal role of right atrial remodeling revealed by explainable machine learning.

Frontiers in cardiovascular medicine·2026
Same author

Effect of occupational therapy on upper limb function and related rehabilitation outcomes after stroke: a systematic review and meta-analysis.

Frontiers in neurology·2026
Same author

TikTok is a valuable data source for tracking the opioid crisis.

NPJ digital medicine·2026
Same author

Drug-Target Interaction Prediction with PIGLET.

bioRxiv : the preprint server for biology·2026
Same author

GATSBI: Improving context-aware protein embeddings through biologically motivated data splits.

bioRxiv : the preprint server for biology·2026

Related Experiment Video

Updated: Jun 17, 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

Prediction of calcium-binding sites by combining loop-modeling with machine learning.

Tianyun Liu1, Russ B Altman

  • 1Department of Genetics, Stanford University, Stanford, CA, USA. tianyunl@stanford.edu

BMC Structural Biology
|December 17, 2009
PubMed
Summary

This study introduces a hybrid method combining loop modeling and machine learning to identify calcium-binding sites in disordered protein regions. The approach successfully recovers binding sites often missed in apo structures, revealing potential cryptic sites.

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

Related Experiment Videos

Last Updated: Jun 17, 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

Area of Science:

  • Structural Biology
  • Computational Biology
  • Biochemistry

Background:

  • Protein structures, particularly in the apo state, exhibit flexibility, leading to missing electron density in critical ligand-binding regions like surface loops.
  • Recognizing functional sites within these disordered or missing loop regions is crucial for comprehensive functional analysis of proteins.

Purpose of the Study:

  • To develop and validate a hybrid computational approach for identifying calcium-binding sites within disordered protein regions.
  • To assess the efficacy of combining loop modeling with machine learning for structure-based site recognition.

Main Methods:

  • A hybrid approach integrating loop modeling techniques with the FEATURE machine learning method for structure-based site recognition was employed.
  • The method was validated by comparing its performance on known calcium-binding sites using both holo and apo protein structures.

Main Results:

  • The hybrid method successfully identified 14 out of 20 known calcium-binding sites in apo structures after loop rebuilding, significantly outperforming recognition in initial apo structures (7 out of 20).
  • Application to unstructured loops in calcium-binding proteins yielded 102 predictions of potential cryptic calcium-binding sites, with 10 confirmed by independent experiments and 14 supported by indirect evidence.
  • Novel predictions included an enrichment of beta-sheet folds with calcium-binding sites in connecting loops, suggesting roles in calcium-mediated function switching.

Conclusions:

  • Missing loops in protein crystal structures can obscure vital functional information, including binding and active sites.
  • Limited loop modeling (under 17 residues) coupled with pattern recognition algorithms can effectively recover lost functional insights and propose relevant conformations.