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Related Concept Videos

Ligand Binding Sites02:40

Ligand Binding Sites

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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.
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...
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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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Protein-protein Interfaces02:04

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

Ligand Binding and Linkage

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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.
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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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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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Machine learning approaches for predicting protein-ligand binding sites from sequence data.

Orhun Vural1, Leon Jololian1

  • 1Department of Electrical and Computer Engineering, The University of Alabama at Birmingham, Birmingham, AL, United States.

Frontiers in Bioinformatics
|February 18, 2025
PubMed
Summary
This summary is machine-generated.

This review explores machine learning methods for predicting protein-ligand binding sites using only protein sequence data. It highlights recent advancements, challenges, and future research directions in this crucial area of drug discovery.

Keywords:
binding predictioncomputational drug discoverydeep learningprotein-ligand binding sitessequence-based methods

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Area of Science:

  • Biochemistry and Computational Biology
  • Focuses on molecular interactions and computational approaches in biological systems.

Background:

  • Proteins perform vital biological functions through interaction sites, notably protein-ligand binding sites.
  • Accurate prediction of these sites is critical for computational drug discovery and therapeutic development.

Purpose of the Study:

  • To review machine learning studies predicting protein-ligand binding sites from sequence data.
  • To examine recent advancements, embedding methods, and machine learning architectures in this field.

Main Methods:

  • Review of existing literature on sequence-based machine learning for protein-ligand binding site prediction.
  • Analysis of various embedding techniques and neural network architectures used in recent studies.

Main Results:

  • Machine learning significantly enhances the prediction accuracy of protein-ligand binding sites from sequence data.
  • Identified various successful embedding methods and deep learning architectures.

Conclusions:

  • Sequence-based machine learning offers a powerful approach for predicting protein-ligand binding sites.
  • Further research is needed to address current challenges and explore future directions for improved accuracy and application in drug discovery.