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Related Concept Videos

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...
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...
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...
Protein Networks02:26

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 Organization01:24

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.

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Related Experiment Video

Updated: May 27, 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

Predicting nucleic acid binding interfaces from structural models of proteins.

Iris Dror1, Shula Shazman, Srayanta Mukherjee

  • 1Faculty of Biology, Technion - Israel Institute of Technology, Haifa, Israel 32000.

Proteins
|November 17, 2011
PubMed
Summary
This summary is machine-generated.

Predicting protein function is enhanced by identifying DNA/RNA binding interfaces. This study presents a computational pipeline using structural models to accurately locate these functional electrostatic patches, even with low-resolution data.

Keywords:
electrostatic patchesfunction predictionnucleic acid bindingprotein surfacestructural models

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Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
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Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

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Analyzing and Building Nucleic Acid Structures with 3DNA
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Analyzing and Building Nucleic Acid Structures with 3DNA

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Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
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Published on: January 26, 2024

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
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Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

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Analyzing and Building Nucleic Acid Structures with 3DNA
16:24

Analyzing and Building Nucleic Acid Structures with 3DNA

Published on: April 26, 2013

Area of Science:

  • Structural Biology
  • Computational Biology
  • Bioinformatics

Background:

  • Predicting nucleic acid binding interfaces is crucial for understanding protein function.
  • Existing structure-based methods are limited by the availability of high-resolution protein structures.

Purpose of the Study:

  • To develop a computational pipeline for predicting functional electrostatic patches on protein surfaces using structural models.
  • To assess the accuracy of this pipeline in identifying nucleic acid binding interfaces.

Main Methods:

  • Utilized the I-TASSER protein structure predictor to generate protein structural models.
  • Employed the patchfinder algorithm to extract the largest positive electrostatic patches from protein surfaces.
  • Developed a combined patch approach using an ensemble of structural models.

Main Results:

  • Functional electrostatic patches from ensembles of structural models highly overlap those from high-resolution structures.
  • The pipeline accurately identified nucleic acid binding interfaces on structural models for 55 known binding proteins.
  • A combined patch approach using multiple models improved prediction accuracy compared to individual models.

Conclusions:

  • Combining information from low-resolution structural models is a valuable approach for functional annotation of proteins.
  • The developed method shows promise for predicting other functional protein surfaces, particularly for proteins with unknown structures.