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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.
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Drug-receptor interaction describes the binding of receptors by drugs, but not all drug-receptor interactions result in activation and tissue response. For instance, the binding of agonists activates the receptor to generate a cellular reaction, while antagonists bind to receptors without causing their activation.
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The receptor occupancy theory connects a drug's response to the number of occupied receptors. With higher drug concentrations, more receptors are occupied, leading to increased responses. The formation of drug-receptor complexes involves association and dissociation rates, which reach equilibrium when the forward and backward reactions are equal. The equilibrium association constant (Ka) and its inverse, the equilibrium dissociation constant (Kd), indicate drug affinity. Higher Ka and lower...
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The combined effects of drugs can result in various interactions, of which an important type is antagonism. Antagonism is a mechanism where one drug inhibits or counteracts the effects of another drug. Antagonism can occur through various means, including receptor binding, allosteric modulation, functional interaction, chemical reactions, and pharmacokinetic processes.
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Combined Effects of Drugs: Synergism01:27

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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.
Such synergistic combinations...
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Drug-Receptor Interaction: Agonist01:25

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Agonists are drugs that interact with specific receptors in the body to produce a biological response. When an agonist binds to a receptor, it activates or enhances the receptor's function, leading to physiological effects. The interaction between agonist drugs and receptors is crucial for their therapeutic action in various medical treatments.
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Text Mining Protocol to Retrieve Significant Drug-Gene Interactions from PubMed Abstracts.

Sadhanha Anand1, Oviya Ramalakshmi Iyyappan2, Sharanya Manoharan3

  • 1Department of Biomedical Engineering, PSG College of Technology, Coimbatore, Tamilnadu, India.

Methods in Molecular Biology (Clifton, N.J.)
|June 17, 2022
PubMed
Summary

This study explores computational methods, including text mining, to accelerate the identification of drug-gene targets for disease treatment. It aims to improve drug discovery by analyzing biomedical literature for drug-gene interactions.

Keywords:
ADRDrug–disease–targetDrug–gene interactionFunctional annotationPolymorphismText mining

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Area of Science:

  • Genomics and Molecular Biology
  • Pharmacology and Drug Discovery
  • Bioinformatics

Background:

  • Cellular processes rely on genes and proteins; disruptions cause genetic diseases.
  • External factors and infections also lead to diseases, despite individual immunogenicity.
  • Identifying drug targets within biological pathways is crucial for drug discovery.

Purpose of the Study:

  • To investigate computational approaches for identifying drug-gene interactions.
  • To explore the use of text mining in accelerating drug target discovery.
  • To analyze how identified drug-gene information can be utilized for drug interaction studies.

Main Methods:

  • Utilizing computational approaches for drug target identification.
  • Employing text mining techniques on vast biomedical literature.
  • Analyzing relationships between drugs, diseases, genes, and proteins.

Main Results:

  • Computational methods offer speed and efficiency compared to traditional drug discovery.
  • Text mining effectively aids in identifying potential drug-gene targets.
  • Extracted information facilitates the review of disease components and drug-disease-gene relationships.

Conclusions:

  • Computational and text mining approaches are essential for efficient drug discovery.
  • Identifying drug-gene interactions is key to understanding and exploring drug interactions.
  • This research aids in the early stages of drug development and target identification.