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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.
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Updated: May 26, 2026

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
08:49

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

Normal mode-based approaches in receptor ensemble docking.

Claudio N Cavasotto1

  • 1School of Biomedical Informatics, The University of Texas Health Center, Houston, TX, USA. claudio.n.cavasotto@uth.tmc.edu

Methods in Molecular Biology (Clifton, N.J.)
|December 21, 2011
PubMed
Summary
This summary is machine-generated.

Normal mode analysis efficiently generates multiple receptor conformations (MRCs) for ensemble docking. This approach accounts for target flexibility, crucial for high-throughput screening and drug discovery.

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Last Updated: May 26, 2026

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Area of Science:

  • Computational chemistry
  • Structural biology
  • Drug discovery

Background:

  • Accounting for target flexibility in molecular docking is computationally challenging, especially for high-throughput screening.
  • Ensemble docking using multiple receptor conformations (MRCs) is a strategy to address binding site flexibility.
  • Generating diverse MRCs can be difficult when experimental structures are limited.

Purpose of the Study:

  • To present normal mode analysis as an efficient method for generating MRCs for ensemble docking.
  • To explain the theoretical and practical aspects of implementing normal mode-based ensemble docking.

Main Methods:

  • Utilizing normal mode analysis to generate MRCs by distorting along low-frequency modes.
  • Reducing the dimensionality of the conformational space for sampling.
  • Focusing on incorporating backbone flexibility of the target.

Main Results:

  • Normal mode analysis provides an efficient in silico approach to generate diverse MRCs.
  • This method significantly reduces the conformational space that needs to be sampled.
  • The methodology is particularly effective for modeling backbone flexibility.

Conclusions:

  • Normal mode analysis is a powerful tool for generating MRCs in ensemble docking.
  • This approach facilitates the incorporation of target flexibility, improving docking accuracy.
  • The presented methodology offers practical considerations for implementation in drug discovery pipelines.