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

The Equilibrium Binding Constant and Binding Strength

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:

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...

Ligand Binding Sites

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...

You might also read

Related Articles

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

Sort by

Same author

Restraining Interproton Angular and Distance Dynamics with KEnRef.

The journal of physical chemistry. B·2026

Same author

Deamidation and isomerization to elusive isoaspartate in a computationally designed miniprotein.

Protein science : a publication of the Protein Society·2026

Same author

Braess' Paradox in Enzyme Kinetics: Asymmetry from Population Balance without Direct Cooperativity.

Journal of chemical theory and computation·2026

Same author

Deep learning-guided design of dynamic proteins.

Science (New York, N.Y.)·2025

Same author

Heat-induced structural and chemical changes to a computationally designed miniprotein.

Protein science : a publication of the Protein Society·2024

Same author

Effects of Xylanase A double mutation on substrate specificity and structural dynamics.

Journal of structural biology·2024

Same journal

Engineered HSP90-MP65 Bivalent Fusion Antigen: A Novel Vaccine Candidate Against Invasive Candidiasis.

Proteins·2026

Same journal

Physics-Based Energy Functions for Computational Protein Design.

Proteins·2026

Same journal

Impact of Stabilizing Osmolytes on the Conformational Dynamics of Human and Rat Islet Amyloid Polypeptides.

Proteins·2026

Same journal

Stabilization of Bone Morphogenetic Protein-2 at Physiological pH: Contrasting Roles of CHAPS and Arginine in Aggregation Inhibition.

Proteins·2026

Same journal

Structural Insights Into the Function of Leishmania major Adenylosuccinate Lyase.

Proteins·2026

Same journal

Generalizing the Gaussian Network Model: Spanning-Tree Thermodynamics Shows Entropy-Driven KRAS Activation.

Proteins·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Aug 11, 2025

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Published on: May 9, 2025

Predicting binding affinity changes from long-distance mutations using molecular dynamics simulations and Rosetta.

Nicholas G M Wells¹, Colin A Smith¹

¹Department of Chemistry, Wesleyan University, Middletown, Connecticut, USA.

|February 9, 2023

Summary

This summary is machine-generated.

We developed a new computational method to predict how mutations impact protein binding, even those far from the interaction site. This advance improves protein design and understanding of molecular interactions.

Keywords:

allosteric molecular dynamics simulations mutations protein binding

More Related Videos

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

Deciphering the Structural Effects of Activating EGFR Somatic Mutations with Molecular Dynamics Simulation

Deciphering the Structural Effects of Activating EGFR Somatic Mutations with Molecular Dynamics Simulation

Published on: May 20, 2020

Related Experiment Videos

Last Updated: Aug 11, 2025

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Published on: May 9, 2025

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

Deciphering the Structural Effects of Activating EGFR Somatic Mutations with Molecular Dynamics Simulation

Deciphering the Structural Effects of Activating EGFR Somatic Mutations with Molecular Dynamics Simulation

Published on: May 20, 2020

Area of Science:

Computational biology
Biophysics
Protein engineering

Background:

Predicting mutation effects on protein-protein binding is crucial for understanding molecular interactions and protein design.
Current methods struggle to model long-distance mutations due to complexities in predicting their structural impact.
Accurate modeling of long-distance mutations offers greater control and flexibility in protein engineering applications.

Purpose of the Study:

To develop and validate a novel computational method for accurately predicting the impact of mutations on protein-protein binding.
To enable the accurate prediction of long-distance mutational effects, expanding the scope of computational protein design.
To improve the understanding of the biophysics underlying protein interface modulation by mutations.

Main Methods:

Combined high-throughput Rosetta-based side-chain optimization with classical molecular dynamics simulations.
Utilized an analytical framework based on alchemical free energy calculations.
Explored a significantly larger sequence space compared to traditional methods.

Main Results:

Achieved significant improvements in accurately predicting long-distance mutational effects on protein binding.
Demonstrated accuracy comparable to traditional methods for interface mutations when predicting internal long-distance perturbations.
Validated predictions against experimental data, confirming the method's efficacy.

Conclusions:

The developed method offers a generalizable approach for optimizing protein free energy landscapes.
This work enhances the ability to computationally model and design protein interactions with greater precision.
The findings pave the way for more sophisticated protein engineering and functional optimization.