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Related Concept Videos

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.
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,...
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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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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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Evolutionary Relationships through Genome Comparisons02:54

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Molecular Models02:00

Molecular Models

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Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
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Topoisomerases are enzymes that relax overwound DNA molecules during various cell processes, including DNA replication and transcription. These enzymes regulate positive and negative DNA supercoiling without changing the nucleotide sequence. DNA overwinding in a clockwise direction results in positively supercoiled DNA, whereas underwinding in a counterclockwise direction produces negatively supercoiled DNA.
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Updated: Jun 17, 2025

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
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Network Topology Evaluation and Transitive Alignments for Molecular Networking.

Xianghu Wang1, Michael Strobel1, Allegra T Aron2

  • 1Department of Computer Science and Engineering, University of California Riverside, 900 University Ave., Riverside, California 92521, United States.

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Untargeted tandem mass spectrometry (MS/MS) generates complex data. This study introduces Transitive Alignments to improve molecular network construction for better analysis of chemical structures and pathways.

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Area of Science:

  • Analytical Chemistry
  • Computational Chemistry
  • Bioinformatics

Background:

  • Untargeted tandem mass spectrometry (MS/MS) is vital for analyzing complex chemical samples.
  • High-throughput MS/MS generates large datasets, posing interpretation challenges.
  • Molecular Networks (MNs) organize and visualize MS/MS data but their construction needs optimization.

Purpose of the Study:

  • To evaluate network topology's influence on Molecular Network construction.
  • To introduce novel metrics for assessing MN quality.
  • To propose and validate the Transitive Alignments approach for enhanced MN construction.

Main Methods:

  • Developed metrics to evaluate Molecular Network construction.
  • Benchmarked existing state-of-the-art MN approaches.
  • Introduced the Transitive Alignments technique, leveraging network topology.
  • Combined Transitive Alignments with pseudoclique finding for improved molecular families.
  • Developed induced transitive alignments for targeted network construction.

Main Results:

  • Transitive Alignments effectively realigns MS/MS spectra of related compounds with multiple structural differences.
  • The combination of Transitive Alignments and pseudoclique finding yielded more complete and higher-quality molecular families.
  • Induced transitive alignments demonstrated effectiveness in a natural product discovery application.

Conclusions:

  • The Transitive Alignments approach significantly enhances Molecular Network construction for untargeted MS/MS data.
  • This method improves the identification of related compounds, metabolic pathways, and potential biomarkers.
  • The developed workflow is released as a high-throughput tool for the research community.