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Related Concept Videos

Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence its...
Quantitative Aspects of Drug-Receptor Interaction01:30

Quantitative Aspects of Drug-Receptor Interaction

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 Kd...
Transducer Mechanism: Nuclear Receptors01:31

Transducer Mechanism: Nuclear Receptors

Nuclear receptors, or NRs, are unique transcription factors that regulate gene transcription and affect the cellular pathways involved in reproduction, development, or metabolism. Their ability to be stimulated by small lipophilic ligands and control vital cellular processes makes them ideal drug targets. Nearly 10-15% of currently prescribed drugs target these receptors.
About 48 different soluble family members of nuclear receptors are identified that can be divided into two main classes:
Drug-Receptor Interactions01:29

Drug-Receptor Interactions

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.
Several parameters, such as the drug's affinity for its receptor and its efficacy, which is its ability to activate the receptor, determine the drug's effect on the tissue.
The Two-State Receptor Model01:29

The Two-State Receptor Model

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.
The binding affinity of a drug determines its interaction with one...
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...

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Related Experiment Video

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Reverse Yeast Two-hybrid System to Identify Mammalian Nuclear Receptor Residues that Interact with Ligands and/or Antagonists
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Structure-activity relationship modeling for predicting interactions with pregnane X receptor by recursive

Shuya Yoshida1, Fumiyoshi Yamashita, Takayuki Itoh

  • 1Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan.

Drug Metabolism and Pharmacokinetics
|March 29, 2012
PubMed
Summary

This study developed a computational model to predict Pregnane X receptor (PXR) agonists, crucial for understanding drug interactions. The model achieved high accuracy, aiding in the design of safer pharmaceuticals.

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Last Updated: May 23, 2026

Reverse Yeast Two-hybrid System to Identify Mammalian Nuclear Receptor Residues that Interact with Ligands and/or Antagonists
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05:47

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Published on: August 28, 2019

Area of Science:

  • Pharmacology
  • Computational Chemistry
  • Molecular Biology

Background:

  • Pregnane X receptor (PXR) is a nuclear receptor regulating xenobiotic detoxification, primarily via CYP3A4.
  • Understanding PXR agonist activity is vital for predicting and mitigating drug-drug interactions and pharmacokinetic variability.

Purpose of the Study:

  • To develop a large-scale, ligand-based structure-activity relationship (SAR) model for human PXR agonists.
  • To identify key molecular descriptors influencing PXR agonism for improved drug design.

Main Methods:

  • Systematic data collection of chemical-PXR interactions from PubMed and PubChem databases.
  • Utilized text mining and curated screening data to compile a dataset of 270 agonists and 248 non-agonists.
  • Employed recursive partitioning for classification tree modeling, with cross-validation for optimization.

Main Results:

  • The classification tree model achieved 79.0% accuracy on the training set and 70.9% on the external testing set.
  • Identified molecular electronic properties as significant descriptors for PXR agonist classification.
  • Successfully classified known PXR agonists and non-agonists based on chemical structure.

Conclusions:

  • A robust computational model for predicting PXR agonists was established.
  • The model's reliance on electronic properties highlights their importance in PXR ligand binding and activation.
  • This approach facilitates SAR analysis and aids in the rational design of PXR-modulating drugs.