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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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Protein Networks02:26

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Hepatic Drug Clearance: Effect of Protein Binding01:09

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Hepatic clearance is influenced by protein binding based on the drug's extraction ratio. Drugs with high extraction ratios are considered flow-limited and remain unaffected by protein binding during hepatic clearance. On the other hand, drugs with low extraction ratios may be impacted by plasma protein binding, although the extent of this influence depends on the fraction of the drug bound.
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Renal clearance plays a pivotal role in drug elimination from the body and can be influenced by drug distribution and interactions. Understanding these factors is crucial in pharmacology as they impact the effectiveness and duration of drug therapy.
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Hepatic clearance refers to the volume of blood cleared of a drug by the liver per unit of time. It plays a crucial role in drug metabolism and elimination. While hepatic clearance is commonly estimated by subtracting renal clearance from total body clearance, other pathways, such as pulmonary or biliary clearance, may also contribute. However, these pathways are generally less significant than hepatic and renal clearance.
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Renal Clearance01:23

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The glomerular filtration rate (GFR) is a critical marker of kidney function, reflecting the efficiency of filtration by the glomeruli. Renal clearance of specific substances, such as inulin or creatinine, is commonly used to measure GFR.
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A Biomolecular Network Driven Proteinic Interaction in HCV Clearance.

Pratichi Singh1, Febin Prabhu Dass J2

  • 1Department of Integrative Biology, School of Biosciences and Technology, VIT University, Vellore, Tamil Nadu, 632014, India.

Cell Biochemistry and Biophysics
|January 10, 2018
PubMed
Summary

Hepatitis C virus (HCV) clearance involves specific immune genes. This study identifies key genes, transcription factors, and pathways, like interferon gamma signaling, crucial for spontaneous HCV clearance in affected populations.

Keywords:
Dinucleotide frequencyHCV clearance candidate genesPathway enrichmentProtein–protein interaction networkTranscription factors

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Area of Science:

  • Immunology
  • Virology
  • Bioinformatics

Background:

  • Hepatitis C virus (HCV) infection can lead to chronic liver disease and cancer.
  • Spontaneous clearance of HCV occurs in approximately 30% of infected individuals, mediated by immune responses.
  • Understanding the genetic and molecular mechanisms of spontaneous clearance is vital for therapeutic strategies.

Purpose of the Study:

  • To identify key immune-response genes and transcription factors (TFs) involved in spontaneous Hepatitis C virus clearance.
  • To analyze the regulatory network of these genes and TFs using a network approach.
  • To elucidate the role of specific signaling pathways in HCV clearance.

Main Methods:

  • Network analysis was employed to identify hub genes and their associated transcription factors.
  • Analysis of TF binding elements and dinucleotide frequencies.
  • Gene enrichment analysis to identify relevant biological pathways.

Main Results:

  • IFNG, TNF, IFNB1, STAT1, NFKB1, STAT3, SOCS1, and MYD88 were identified as prioritized hub genes.
  • IRF9, NFKB1, and STAT1 were identified as common transcription factors regulating these hub genes.
  • GG-rich motifs were prevalent in TF binding elements, and the interferon gamma signaling pathway was significantly enriched, playing a central role in HCV clearance.

Conclusions:

  • The study prioritizes key genes, TFs, and the interferon gamma pathway critical for spontaneous HCV clearance.
  • The identified hub genes, TFs, and regulatory elements may be important biomarkers for predicting clearance in specific populations.
  • Network-based insights provide a deeper understanding of the molecular underpinnings of HCV clearance.