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Synergism is a useful mechanism where combining two or more drugs is more effective than each constituent used alone. Such combinations are also called supra-additive interactions. The drugs collectively enhance the final therapeutic effect by acting on different targets. Another advantage is that the low dose of each constituent drug is sufficient to achieve the desired effect. This helps reduce the duration of therapy and lower the adverse effects of these drugs.
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Functions can be combined to form new mathematical models that describe interactions between variables. These combinations are fundamental in understanding relationships between changing quantities and are commonly encountered in scientific and engineering contexts. The combination methods—addition, subtraction, multiplication, division, and composition—each have unique implications for the resulting function’s domain and behavior.When combining functions through arithmetic...
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Sequence Networks of Rotating Machines01:24

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A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
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High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method
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Synergy Maps: exploring compound combinations using network-based visualization.

Richard Lewis1, Rajarshi Guha2, Tamás Korcsmaros3

  • 1Department of Chemistry, Centre for Molecular Informatics, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW UK.

Journal of Cheminformatics
|August 4, 2015
PubMed
Summary
This summary is machine-generated.

Synergy Maps offer a novel visualization for compound combinations, integrating compound properties with synergistic interactions. This tool aids in understanding drug synergy and facilitates the discovery of new therapeutic strategies.

Keywords:
Compound combinationsDimensionality reductionMixturesNetworkSynergyVisualization

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Area of Science:

  • Pharmacology
  • Computational Chemistry
  • Bioinformatics

Background:

  • Synergy, the super-additive biological response to joint compound application, offers therapeutic potential.
  • High-throughput screening of compound combinations generates large datasets, but existing visualizations (heat-maps, networks) incompletely represent the data.
  • Understanding compound interactions is crucial for drug discovery and development.

Purpose of the Study:

  • To introduce a new visualization technique, Synergy Maps, for pairwise combination screening data.
  • To integrate compound properties (structure, physicochemical, bioactivity) with synergy information into a single visualization.
  • To provide an interactive web application for exploring and filtering large-scale combination datasets.

Main Methods:

  • Development of the Synergy Maps visualization technique.
  • Integration of compound property data with synergy data.
  • Creation of an interactive web application for public use.
  • Application of Synergy Maps to an anti-malarial dataset against Plasmodium falciparum.

Main Results:

  • Synergy Maps enable simultaneous investigation of compound properties and their synergistic interactions.
  • The web app facilitates navigation and filtering of large combination screening datasets.
  • Analysis of an anti-malarial dataset revealed disproportionate synergism of histone deacetylase inhibitors.
  • The tool suggested new hypotheses for further research into anti-malarial drug combinations.

Conclusions:

  • Synergy Maps advance compound combination visualization by integrating individual compound properties and interactions.
  • The web-based tool simplifies exploration of combination data and correlation identification.
  • This approach enhances understanding of drug synergy and aids in identifying promising therapeutic combinations.