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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...
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...
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-Drug Binding: Determination Methods01:22

Protein-Drug Binding: Determination Methods

Determining protein-drug binding can be achieved through indirect and direct methods, each providing valuable insights into the interaction between proteins and drugs.
Indirect methods involve isolating the bound drug from its free form in biological samples such as blood, serum, or plasma. These techniques aim to measure the percentage of drugs bound to proteins. Equilibrium dialysis is a commonly used method where the free drug concentration at equilibrium is measured by separating the bound...
The Equilibrium Binding Constant and Binding Strength02:18

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:

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Related Experiment Video

Updated: May 22, 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

Computational methods for DNA-binding protein and binding residue prediction.

Yao Lu1, Xiang Wang, Xuesong Chen

  • 1Shanghai Jiao Tong University Children's Hospital, Shanghai Institute of Medical Genetics, Shanghai 200040, China.

Protein and Peptide Letters
|May 18, 2012
PubMed
Summary
This summary is machine-generated.

Computational methods, particularly machine learning, are crucial for predicting protein-DNA interactions. This review covers recent advances in predicting DNA-binding proteins and residues, highlighting common features and future directions.

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Last Updated: May 22, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
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16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Computational Biology

Background:

  • Protein-DNA interactions are fundamental to essential biological processes like transcription, replication, and DNA repair.
  • Experimental methods for identifying these interactions are often costly, time-consuming, and labor-intensive.
  • The growing number of suspected interactions necessitates efficient computational prediction strategies.

Purpose of the Study:

  • To review recent advancements in machine learning-based computational methods for predicting DNA-binding proteins and their binding sites.
  • To discuss commonly employed features, classifier comparisons, and evaluation metrics in this field.
  • To identify current challenges and outline future research directions in computational prediction of protein-DNA interactions.

Main Methods:

  • Focuses on a review of existing literature on machine learning approaches for protein-DNA interaction prediction.
  • Analyzes commonly used features for predicting DNA-binding proteins and residues.
  • Compares different machine learning classifiers and evaluation methodologies.

Main Results:

  • Machine learning has become the dominant approach for in silico prediction of protein-DNA interactions.
  • Identifies key features and methodologies driving recent progress in the field.
  • Highlights areas for improvement and future research in computational prediction.

Conclusions:

  • Machine learning offers a powerful and efficient alternative to experimental methods for studying protein-DNA interactions.
  • Continued development in feature engineering and algorithm selection is crucial for enhancing prediction accuracy.
  • Addressing current limitations will pave the way for more comprehensive understanding of these vital biological interactions.