Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Protein-protein Interfaces

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...

Protein-Protein Interfaces

Protein-Protein Interfaces

Protein Networks

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

Protein Networks

Protein Networks

Conserved Binding Sites

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...

Physiological Pharmacokinetic Models: Assumption with Protein Binding

Physiological Pharmacokinetic Models: Assumption with Protein Binding

Physiological models with protein binding in pharmacokinetics offer a sophisticated approach to understanding drug disposition. These models consider drug-protein interactions, enabling them to effectively predict drug concentrations in different organs and tissues. This precision aids in accurate drug dosing, providing a significant advantage over conventional models. A key process within these models is equilibration, which ensures that drug concentrations achieve a steady state within the...

You might also read

Related Articles

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

Sort by

Same author

How to think about designing smart antibodies in the age of genAI: integrating biology, technology, and experience.

mAbs·2025

Same author

Recent advances in generative biology for biotherapeutic discovery.

Trends in pharmacological sciences·2024

Same author

Development of in silico models to predict viscosity and mouse clearance using a comprehensive analytical data set collected on 83 scaffold-consistent monoclonal antibodies.

mAbs·2023

Same author

Identifying promising sequences for protein engineering using a deep transformer protein language model.

Proteins·2023

Same author

Building the foundation for a community-generated national research blueprint for inherited bleeding disorders: facilitating research through infrastructure, workforce, resources and funding.

Expert review of hematology·2023

Same author

Unifying cardiovascular modelling with deep reinforcement learning for uncertainty aware control of sepsis treatment.

PLOS digital health·2023

Search research articles

Related Experiment Video

Updated: Apr 12, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

Learning sequence determinants of protein:protein interaction specificity with sparse graphical models.

Hetunandan Kamisetty¹, Bornika Ghosh², Christopher James Langmead³

¹1Facebook Inc., Seattle, Washington.

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology

|May 15, 2015

Summary

This summary is machine-generated.

We developed DgSpi, a data-driven method to predict protein-protein binding strength and specificity. This approach accurately forecasts interaction outcomes and identifies key amino acid residues driving specificity.

Keywords:

PDZ graphical model protein:protein interaction specificity ΔG prediction

More Related Videos

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

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

Published on: July 14, 2015

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells

Published on: January 5, 2024

Related Experiment Videos

Last Updated: Apr 12, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

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

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

Published on: July 14, 2015

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells

Published on: January 5, 2024

Area of Science:

Computational Biology
Biochemistry
Structural Biology

Background:

Understanding protein-protein interactions is crucial for deciphering biological processes.
Key questions involve identifying interacting partners, quantifying binding affinity, and elucidating the molecular basis of specificity.
Large-scale interaction data provides an opportunity to develop predictive models.

Purpose of the Study:

To develop a novel method, DgSpi (data-driven graphical models of specificity in protein:protein interactions), for predicting the strength (ΔG of binding) and specificity of protein-protein interactions.
To explicitly represent the amino acid basis for interaction specificity.
To extend existing classification methods to predict binding affinity.

Main Methods:

Development of DgSpi, a graphical model approach.
Application of DgSpi to analyze interactions between 82 PDZ domains and 217 peptide partners.
Validation using experimental data from MacBeath and colleagues.

Main Results:

DgSpi accurately predicts the ΔG of binding, achieving correlation coefficients of 0.69 in 10-fold cross-validation and 0.63 in leave-one-PDZ-out cross-validation.
The model provides insights into residue-level constraints that determine protein-level interaction specificity.
Designed novel interacting partners (ligands) with diverse structures.

Conclusions:

DgSpi is an effective method for predicting protein-protein interaction strength and specificity.
The model elucidates the amino acid determinants of interaction specificity.
DgSpi facilitates the rational design of new protein interaction partners.