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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 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.
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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...
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:
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.
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Related Experiment Video

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Determination of High-affinity Antibody-antigen Binding Kinetics Using Four Biosensor Platforms
15:27

Determination of High-affinity Antibody-antigen Binding Kinetics Using Four Biosensor Platforms

Published on: April 17, 2017

Antibody-protein interactions: benchmark datasets and prediction tools evaluation.

Julia V Ponomarenko1, Philip E Bourne

  • 1San Diego Supercomputer Center, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA. jpon@sdsc.edu

BMC Structural Biology
|October 4, 2007
PubMed
Summary

Predicting antibody binding sites is crucial for vaccine design. This study benchmarks 3D structure-based epitope prediction methods, finding current tools have limited accuracy, highlighting challenges in identifying B-cell epitopes.

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

Published on: January 26, 2024

Area of Science:

  • Structural biology
  • Immunoinformatics
  • Computational vaccinology

Background:

  • Accurate prediction of antibody binding sites (B-cell epitopes) is essential for developing new vaccines and diagnostics.
  • X-ray crystallography provides reliable experimental data for B-cell epitope identification.
  • Growing availability of 3D structures of antibody-protein complexes fuels interest in structure-based prediction methods.

Purpose of the Study:

  • To establish a benchmark for evaluating 3D structure-based B-cell epitope prediction methods.
  • To assess the performance of existing computational tools for predicting antibody binding sites.

Main Methods:

  • Creation of two benchmark datasets from 3D structures of antibody-protein complexes (62 antigen structures, 82 complex structures).
  • Evaluation of eight web-servers for antibody and protein binding site prediction using these datasets.
  • Performance metrics included precision, recall, and area under the receiver operating characteristic curve (AUC).

Main Results:

  • No evaluated method exceeded 40% precision and 46% recall.
  • AUC values were around 0.6 for some methods and up to 0.7 for protein-protein docking methods.
  • Most methods performed close to random, indicating limitations in current prediction capabilities.

Conclusions:

  • Improving epitope prediction may involve training on immune epitope datasets and incorporating features like evolutionary conservation.
  • The generally poor performance suggests antigenicity may be too general, hindering the identification of B-cell epitopes as intrinsic protein features.
  • It remains an open question whether definitive discriminatory features for B-cell epitope prediction can be identified.