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Related Concept Videos

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...
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...
The Equilibrium Binding Constant and Binding Strength02:18

The Equilibrium Binding Constant and Binding Strength

The equilibrium binding constant (Kb) quantifies the strength of a protein-ligand interaction. Kb can be calculated as follows when the reaction is at equilibrium:
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence the...
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence the...
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...

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Related Experiment Video

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Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
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Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

CSAR data set release 2012: ligands, affinities, complexes, and docking decoys.

James B Dunbar1, Richard D Smith, Kelly L Damm-Ganamet

  • 1Department of Medicinal Chemistry, University of Michigan, 428 Church St., Ann Arbor, Michigan 48109-1065, USA. jbdunbar@umich.edu

Journal of Chemical Information and Modeling
|April 27, 2013
PubMed
Summary

The Community Structure Activity Resource (CSAR) offers curated datasets for drug design, including protein targets, compound affinities, and crystal structures. This data aids in validating computational docking and scoring methods, focusing on relative compound rankings.

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

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Last Updated: May 12, 2026

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
05:08

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

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:

  • Computational chemistry and drug discovery.
  • Structural biology and cheminformatics.

Background:

  • Drug design heavily relies on computational docking and scoring methods.
  • The Community Structure Activity Resource (CSAR) curates industry and in-house data for method development.
  • Existing datasets often lack inactive compounds and diverse structural information.

Purpose of the Study:

  • To provide a comprehensive, curated dataset for the development and validation of computational docking and scoring methods.
  • To include diverse chemical series with varying biological affinities and associated physical properties.
  • To generate decoy sets for robust method evaluation.

Main Methods:

  • Collected and curated data from industry partners (Abbott, GlaxoSmithKline, Vertex) and in-house projects.
  • Assembled a dataset comprising 6 protein targets, 647 compounds with biological affinities, and 82 crystal structures.
  • Measured biological affinities using Thermofluor, Octet RED, and isothermal titration calorimetry.
  • Characterized physical properties including logD, logP, thermodynamic solubility, and pK(a).
  • Generated decoy sets with diverse conformations for 58 CSAR-quality crystal structures.

Main Results:

  • The dataset includes multiple congeneric series with affinity ranges of 3-4 orders of magnitude.
  • Experimental data revealed considerable variance in absolute affinity values but better relative rankings.
  • Predicting relative compound rankings is a more tractable computational problem.
  • Physical properties and decoy sets enhance the dataset's utility for method validation.

Conclusions:

  • The CSAR datasets provide valuable, publicly available resources for improving computational drug design tools.
  • The data supports the development of methods that focus on relative compound activity prediction.
  • The inclusion of inactive compounds and diverse structures aids in more rigorous validation of docking and scoring algorithms.