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Related Concept Videos

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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Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
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Related Experiment Video

Updated: Mar 22, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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How to Predict Molecular Interactions between Species?

Sylvie Schulze1, Jana Schleicher1, Reinhard Guthke1

  • 1Research Group Systems Biology and Bioinformatics, Leibniz-Institute for Natural Product Research and Infection Biology - Hans-Knöll-Institute Jena, Germany.

Frontiers in Microbiology
|April 12, 2016
PubMed
Summary

Network inference using dual transcriptomics accurately predicts gene regulatory networks between interacting species. This approach enhances understanding of host-pathogen and other inter-species molecular interactions.

Keywords:
dual RNA-seqdual transcriptomicsgene regulatory networkhost-pathogen interactionmolecular inter-species interactionnetwork inference

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Area of Science:

  • Molecular Biology
  • Systems Biology
  • Bioinformatics

Background:

  • Organisms interact, causing molecular changes like transcriptome alterations.
  • Gene expression adaptation is mediated by complex gene regulatory networks, often incompletely understood.
  • High-throughput methods like RNA-seq monitor these changes.

Purpose of the Study:

  • To predict inter-species gene regulatory networks using dual transcriptomics data.
  • To review and contextualize the application of network inference on dual transcriptomics data.
  • To explore dual transcriptomics in host-pathogen, mutualistic, and commensalistic interactions.

Main Methods:

  • Application of the NetGenerator software tool to dual RNA-sequencing data.
  • Utilizing an updated NetGenerator version that incorporates measurement variances and handles missing data in time-series expression data.
  • Testing various modeling scenarios for gene regulatory network stimuli functions.

Main Results:

  • Successfully predicted an inter-species gene regulatory network from murine dendritic cells and Candida albicans.
  • The updated NetGenerator demonstrated improved algorithmic procedures.
  • Dual transcriptomics is applicable beyond host-pathogen studies to other interaction types.

Conclusions:

  • Network inference applied to dual transcriptomics is a powerful method for predicting molecular inter-species interactions.
  • Further investigation into molecular interactions using dual transcriptomics is encouraged.
  • This approach offers insights into the complex molecular basis of species interactions.