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Drug-Receptor Interactions01:29

Drug-Receptor 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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An antagonist is a drug that binds strongly to a receptor without activating it. An antagonist prevents other molecules, such as neurotransmitters or hormones, from binding to the receptor and triggering a cellular response. Such interaction effectively hinders the normal physiological processes mediated by the receptor, resulting in various pharmacological effects depending on the specific receptor targeted.
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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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The two-state receptor model explains a drug's interaction with receptors, such as G protein-coupled receptors and ligand-gated ion channels, to induce or inhibit a biological response. When no natural ligands are present, a receptor exists in an equilibrium of inactive (Ri) and active (Ra) conformations. The inactive form does not produce a response, while the active form generates a basal effect known as constitutive activity.
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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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Modeling the complete chemokine-receptor interaction.

Michael J Wedemeyer1, Benjamin K Mueller2, Brian J Bender3

  • 1Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI, United States.

Methods in Cell Biology
|January 9, 2019
PubMed
Summary
This summary is machine-generated.

Chemokines and their receptors are crucial for cell migration in health and disease. This study presents a computational method using Rosetta to model chemokine-GPCR complexes, aiding therapeutic development.

Keywords:
ChemokineChemokine receptorG protein-coupled receptorGPCR interfaceHomology modelingMulti-receptor/multi-ligand systemRosetta

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Area of Science:

  • Molecular biology
  • Structural biology
  • Biochemistry

Background:

  • Chemokines are secreted proteins mediating leukocyte migration via G protein-coupled receptors (GPCRs).
  • Chemokine receptor signaling is vital in inflammation, cancer, and other diseases, making them therapeutic targets.
  • Understanding chemokine-GPCR interactions is key for developing novel therapeutics.

Purpose of the Study:

  • To present a specialized methodology for constructing and validating models of chemokine-GPCR complexes.
  • To leverage existing structural data for homology modeling of under-characterized chemokine-GPCR interactions.
  • To facilitate the understanding of molecular mechanisms underlying chemokine function in disease.

Main Methods:

  • Utilizes the Rosetta software suite for computational modeling.
  • Employs homology modeling based on existing high-resolution protein structures of chemokine-GPCR complexes.
  • Includes model validation steps to ensure accuracy and reliability.

Main Results:

  • Demonstrates a specialized methodology for generating models of chemokine-GPCR complexes.
  • Provides a framework for studying interactions not yet structurally characterized.
  • Expands the utility of limited available structural data for a large protein family.

Conclusions:

  • The Rosetta-based methodology enables the construction and validation of chemokine-GPCR complex models.
  • This approach aids in understanding disease-related chemokine functions and designing targeted therapeutics.
  • Computational modeling serves as a critical tool for exploring these essential protein-protein interactions.