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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...
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:
G Protein-coupled Receptors01:15

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G Protein-Coupled Receptors or GPCRs are membrane-bound receptors that transiently associate with heterotrimeric G proteins and induce an appropriate response to sensory stimuli such as light, odors, hormones, cytokines, or neurotransmitters.
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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...
Drug Discovery: Overview01:26

Drug Discovery: Overview

Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...

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Related Experiment Video

Updated: May 27, 2026

Reverse Yeast Two-hybrid System to Identify Mammalian Nuclear Receptor Residues that Interact with Ligands and/or Antagonists
10:51

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Published on: November 15, 2013

Structure-based machine learning model for discovering pregnane X receptor (PXR) agonists and biological activity

Fang-Fang Huang1, Ying Luo1, Hao Chen1

  • 1Key Laboratory for Chemistry and Molecular Engineering of Medicinal Resources (Ministry of Education of China), Guangxi Key Laboratory of Chemistry and Molecular Engineering of Medicinal Resources, University Engineering Research Center for Chemistry of Characteristic Medicinal Resources (Guangxi), School of Chemistry and Pharmaceutical Sciences, Guangxi Normal University, 15 Yucai Road, Guilin, 541004, People's Republic of China.

Archives of Toxicology
|May 25, 2026
PubMed
Summary

A novel machine learning strategy identified potent Pregnane X receptor (PXR) agonists from natural products. These compounds, including schisantherin A, show promise for treating PXR-related liver and inflammatory diseases.

Keywords:
AgonistsIn vitro assayPregnane X receptorStructure-based machine learning

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Screening Peptides that Activate MRGPRX2 using Engineered HEK Cells
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Last Updated: May 27, 2026

Reverse Yeast Two-hybrid System to Identify Mammalian Nuclear Receptor Residues that Interact with Ligands and/or Antagonists
10:51

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

Published on: November 15, 2013

Screening Peptides that Activate MRGPRX2 using Engineered HEK Cells
12:38

Screening Peptides that Activate MRGPRX2 using Engineered HEK Cells

Published on: November 6, 2021

Area of Science:

  • Pharmacology and Computational Chemistry
  • Nuclear Receptor Signaling
  • Drug Discovery

Background:

  • Pregnane X receptor (PXR) is crucial for bile acid homeostasis and inflammation, making it a therapeutic target for cholestatic liver diseases and inflammatory bowel disease.
  • PXR regulates key metabolic enzymes (CYP3A4, UGT1A1) and transporters, and modulates inflammatory pathways (NF-κB).

Purpose of the Study:

  • To develop a structure-based machine learning strategy for identifying novel PXR agonists from natural product databases.
  • To validate the predictive power of the machine learning model and identify potent natural product-derived PXR agonists.

Main Methods:

  • A novel structure-based machine learning approach integrating ligand-based and structure-based features using Light Gradient Boosting Machine.
  • Pharmacophore modeling for initial screening, followed by machine learning prediction of PXR agonistic activity.
  • In vitro validation using HepG2 cell culture and dual-luciferase reporter assays to determine EC50 values.

Main Results:

  • The developed machine learning model achieved high accuracy (R²=0.874 internal, R²=0.845 external validation), outperforming other regression models.
  • Schisantherin A, rhynchophylline, and irigenin were identified as potent PXR agonists with EC50 values of 1.58 μM, 2.57 μM, and 20.67 μM, respectively.
  • The identified compounds demonstrate significant PXR agonistic activity.

Conclusions:

  • The novel machine learning strategy effectively identifies potent PXR agonists from natural products.
  • Schisantherin A, rhynchophylline, and irigenin are promising candidates for developing targeted therapies for PXR-related diseases.
  • This work supports the design and discovery of new PXR modulators for therapeutic applications.