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Related Concept Videos

Conserved Binding Sites01:49

Conserved Binding Sites

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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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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.
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Protein-protein Interfaces

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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...
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Ligand Binding and Linkage00:49

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

Protein-Drug Binding: Determination Methods

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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...
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Protein Networks02:26

Protein Networks

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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.
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Updated: Sep 5, 2025

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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ProB-Site: Protein Binding Site Prediction Using Local Features.

Sharzil Haris Khan1, Hilal Tayara2, Kil To Chong1,3

  • 1Department of Electronics and Information Engineering, Jeonbuk National University, Jeonju 54896, Korea.

Cells
|July 9, 2022
PubMed
Summary
This summary is machine-generated.

A new deep neural network model, ProB-site, accurately predicts protein-protein interaction sites using sequential data. This computational approach enhances drug discovery by identifying crucial binding sites more efficiently than current methods.

Keywords:
deep neural networksevolutionary informationlocal featuresmachine learningprotein binding sitesstructural information

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Area of Science:

  • Computational biology
  • Bioinformatics
  • Molecular biology

Background:

  • Protein-protein interactions (PPIs) are vital for biological processes and represent therapeutic targets.
  • Experimental methods for PPI site identification are costly and time-consuming.
  • Computational methods, particularly those using protein sequence data, offer a viable alternative.

Purpose of the Study:

  • To develop an advanced computational model for predicting protein-protein interaction sites.
  • To improve the efficiency and accuracy of interaction site prediction compared to existing methods.

Main Methods:

  • A deep neural network model, ProB-site, was developed.
  • ProB-site utilizes sequential, evolutionary, and predicted structural information from protein sequences.
  • Three unique feature sets are generated per amino acid and processed through sub-CNN architectures.
  • Features are concatenated and classified using fully connected layers.

Main Results:

  • The ProB-site model demonstrated superior performance compared to state-of-the-art techniques.
  • The model's effectiveness stems from optimal feature selection and consideration of local amino acid information.

Conclusions:

  • ProB-site offers a highly effective computational approach for predicting protein-protein interaction sites.
  • This method holds significant potential for accelerating drug discovery and development by identifying key binding sites.