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Related Concept Videos

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...
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...
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence the...
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence 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...
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...

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Updated: May 21, 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

DeepAlloWeb: a web server for interactive allosteric pockets prediction using protein language model.

Moaaz Khokhar1, Ozlem Keskin2, Attila Gursoy3

  • 1Department of Computer Engineering, Koç University, Istanbul 34450, Turkey; KUIS AI Center, Koç University, Istanbul 34450, Turkey.

Journal of Molecular Biology
|May 19, 2026
PubMed
Summary
This summary is machine-generated.

DeepAlloWeb is a new tool that accurately predicts allosteric pockets using advanced protein language models. This web server enhances drug discovery by providing interactive visualizations for better biological interpretability.

Keywords:
allosteric pocket predictionallosterymultitask learningprotein language model

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Area of Science:

  • Computational biology
  • Drug discovery
  • Structural bioinformatics

Background:

  • Allosteric regulation is crucial for protein function and offers a promising avenue for targeted drug development with potentially fewer side effects.
  • Existing computational methods for predicting allosteric sites often lack the sophistication to fully leverage modern machine learning techniques.
  • DeepAllo previously established an advanced computational approach for allosteric pocket prediction.

Purpose of the Study:

  • To introduce DeepAlloWeb, an interactive web server designed to enhance the usability and practical application of the DeepAllo allosteric site prediction method.
  • To improve user engagement for computational biologists and drug discovery researchers through an intuitive web interface.
  • To provide deeper biological insights into allosteric mechanisms via visualization of model interpretability.

Main Methods:

  • Utilized a fine-tuned protein language model (ProtBERT-BFD) within a multitask learning framework.
  • Integrated features extracted by FPocket for accurate allosteric pocket prediction.
  • Developed an interactive web server (DeepAlloWeb) featuring visualizations of residue-level attention mechanisms.

Main Results:

  • DeepAlloWeb demonstrates superior prediction performance for allosteric pockets compared to existing servers lacking protein language model integration.
  • Interactive visualizations of attention mechanisms offer unprecedented biological interpretability, highlighting known allosteric communication pathways in proteins.
  • A comprehensive dataset analysis provides practical guidance on interpreting the layer/head combinations within the model.

Conclusions:

  • DeepAlloWeb represents a significant advancement in computational prediction of allosteric sites, offering enhanced accuracy and interpretability.
  • The web server facilitates detailed exploration of protein allostery, aiding drug discovery efforts.
  • The integration of protein language models and attention visualization marks a new direction for understanding and targeting allosteric regulation.