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Related Concept Videos

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.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
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.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
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...
Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to form...
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...

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Related Experiment Video

Updated: Jun 22, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

Model criticism based on likelihood-free inference, with an application to protein network evolution.

Oliver Ratmann1, Christophe Andrieu, Carsten Wiuf

  • 1Department of Public Health and Epidemiology, Imperial College London, London, United Kingdom. oliver.ratmann@imperial.ac.uk

Proceedings of the National Academy of Sciences of the United States of America
|June 16, 2009
PubMed
Summary

This study introduces Approximate Bayesian Computation under model uncertainty (ABCmicro) for evaluating complex mathematical models when likelihoods are intractable. The method diagnoses model deficiencies and guides refinement, revealing inconsistencies in protein network evolution models.

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Area of Science:

  • Computational Biology
  • Statistical Modeling
  • Evolutionary Biology

Background:

  • Mathematical models are crucial for understanding complex phenomena, but their evaluation is challenging when likelihoods are intractable.
  • Current Bayesian inference methods often lack formal procedures for assessing model adequacy against data when likelihoods cannot be computed.

Purpose of the Study:

  • To develop a statistical framework for assessing model adequacy in the presence of likelihood intractability.
  • To introduce Approximate Bayesian Computation under model uncertainty (ABCmicro) for explicit accounting of model-data discrepancies.

Main Methods:

  • Augmenting model likelihoods with unknown error terms based on checking functions.
  • Employing Monte Carlo strategies for sampling from joint posterior distributions without likelihood evaluation.
  • Integrating model diagnostics within the Approximate Bayesian Computation (ABC) framework.

Main Results:

  • The ABCmicro method effectively diagnoses model mismatch and guides model refinement.
  • Analysis of protein interaction datasets for *Helicobacter pylori* and *Treponema pallidum* revealed model deficiencies.
  • Protein network evolution in *T. pallidum* appears inconsistent with models solely based on link turnover or lateral gene transfer.

Conclusions:

  • ABCmicro provides a robust approach for model adequacy assessment under likelihood intractability.
  • The study highlights the importance of incorporating model diagnostics in Bayesian inference.
  • Findings suggest specific evolutionary mechanisms may not fully explain the *T. pallidum* protein interaction network topology.