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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 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 Organization

Protein Organization

Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence....

Protein-Protein Interfaces

Protein-Protein Interfaces

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...

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Related Experiment Video

Updated: Aug 6, 2025

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

PROT-ON: A structure-based detection of designer PROTein interface MutatiONs.

Mehdi Koşaca^1,2, İrem Yılmazbilek^1,3, Ezgi Karaca^1,2

¹Izmir Biomedicine and Genome Center, Dokuz Eylul Health Campus, Izmir, Türkiye.

Frontiers in Molecular Biosciences

|March 20, 2023

Summary

This summary is machine-generated.

PROT-ON identifies critical protein interface mutations for designing new protein binders. This computational framework analyzes mutations using EvoEF1 or FoldX, filtering for stability and evolutionary relevance to predict designer mutations.

Keywords:

EvoEF1 FoldX interface design interface mutation protein-protein interaction

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Published on: July 14, 2015

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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

Area of Science:

Computational biology
Protein engineering
Bioinformatics

Background:

Mutations at protein-protein interfaces can cause diseases.
Computational tools predict mutation impacts, with FoldX and EvoEF1 being efficient.
Existing tools can be expanded for targeted protein design.

Purpose of the Study:

To develop a computational framework, PROT-ON, for identifying critical protein interface mutations.
To enable the design of novel protein binders by predicting impactful mutations.
To provide a comprehensive analysis of the mutational energy landscape.

Main Methods:

PROT-ON utilizes 3D protein dimer coordinates as input.
It employs EvoEF1 or FoldX to probe all possible interface mutations.
Statistical analysis identifies enriching/depleting mutations, filtered by stability and evolutionary criteria.

Main Results:

PROT-ON generates a list of designer mutations based on energy landscape analysis.
The framework provides residue- and energy-based plots visualizing mutation effects.
Identified mutations are filtered for stability and optionally evolutionary conservation.

Conclusions:

PROT-ON offers a fast and comprehensive method for predicting designer mutations.
The framework aids in understanding protein-protein interface mutation impacts.
PROT-ON is available as a standalone tool and a web service.