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Related Concept Videos

Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
Ligand Binding Sites02:40

Ligand Binding Sites

Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...

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Related Experiment Video

Updated: Jun 13, 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

Improved docking, screening and selectivity prediction for small molecule nuclear receptor modulators using

So-Jung Park1, Irina Kufareva, Ruben Abagyan

  • 1Department of Molecular Biology, The Scripps Research Institute, 10550 N Torrey Pines Rd, La Jolla, CA 92037, USA.

Journal of Computer-Aided Molecular Design
|May 11, 2010
PubMed
Summary

This study introduces a nuclear receptor (NR) pocket ensemble library for improved virtual screening. The library accurately predicts ligand binding poses and selectivity, aiding drug discovery for diseases like cancer and diabetes.

Related Experiment Videos

Last Updated: Jun 13, 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

Area of Science:

  • Biochemistry and Molecular Biology
  • Pharmacology and Drug Discovery
  • Computational Chemistry

Background:

  • Nuclear receptors (NRs) are crucial transcriptional factors regulating key physiological processes.
  • Dysregulation of NRs is implicated in diseases including cancer, inflammation, and diabetes.
  • Targeting NRs offers therapeutic potential for various human diseases.

Purpose of the Study:

  • To develop and validate a comprehensive library of conformational ensembles for thirteen human nuclear receptors.
  • To assess the utility of these ensembles in virtual screening for ligand recognition, binding pose prediction, and affinity estimation.
  • To evaluate the potential of ensemble models for predicting NR ligand selectivity profiles.

Main Methods:

  • Generation of a pocket conformational ensemble library for thirteen human nuclear receptors.
  • Virtual screening of known NR modulators using the ensemble library.
  • Benchmarking against 157 known NR modulators and 66 experimental structures.
  • Calculation of receptor-specific binding energy offsets for selectivity profiling.

Main Results:

  • The pocket ensemble library achieved 94% accuracy in predicting ligand binding poses.
  • Virtual screening models demonstrated high selectivity for active ligands, with AUCs ranging from 82% to 99%.
  • Computationally derived binding energy offsets successfully predicted NR ligand selectivity profiles.

Conclusions:

  • Receptor ensembles offer significant advantages for compound docking and virtual screening of nuclear receptors.
  • The developed library provides a valuable tool for drug discovery targeting nuclear receptors.
  • This approach enhances the prediction of binding affinity, pose, and selectivity, facilitating the development of novel NR modulators.