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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...
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...
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...
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...

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Related Experiment Video

Updated: Jun 4, 2026

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source
08:35

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source

Published on: May 29, 2021

A unified, probabilistic framework for structure- and ligand-based virtual screening.

Steven L Swann1, Scott P Brown, Steven W Muchmore

  • 1Global Pharmaceutical Research and Development, Abbott Laboratories, 100 Abbott Park Road, Abbott Park, Illinois 60064, United States.

Journal of Medicinal Chemistry
|February 12, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a probabilistic framework to interpret structure-based virtual screening results, providing a quantitative likelihood of bioactivity. This method enhances drug discovery by combining multiple screening approaches for more accurate predictions.

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Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery
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Last Updated: Jun 4, 2026

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source
08:35

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source

Published on: May 29, 2021

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery
06:26

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

Published on: May 16, 2021

Area of Science:

  • Computational Chemistry
  • Drug Discovery
  • Bioinformatics

Background:

  • Structure-based virtual screening (SBVS) is crucial for identifying potential drug candidates.
  • Interpreting SBVS results quantitatively remains a challenge, limiting integration with other screening methods.
  • Existing metrics often provide limited predictive power individually.

Purpose of the Study:

  • To develop a probabilistic framework for interpreting SBVS results.
  • To enable quantitative combination of SBVS with ligand-based screening methods.
  • To improve the accuracy and reliability of drug candidate prioritization.

Main Methods:

  • Developed a probabilistic framework to transform SBVS outputs into quantitative probabilities of bioactivity.
  • Validated the approach on over 30 diverse protein targets.
  • Demonstrated the fusion of structure- and ligand-based screening data within the probabilistic framework.

Main Results:

  • The framework provides a quantitative likelihood of observing bioactivity from SBVS.
  • Cumulative predictions integrating multiple screening metrics consistently outperformed single metrics.
  • Successfully validated across more than 30 protein targets, showing broad applicability.

Conclusions:

  • The probabilistic framework offers a paradigm shift in interpreting docking and scoring results.
  • Enables robust fusion of structure- and ligand-based computational tools.
  • Enhances early lead-finding by maximizing the value of in silico screening for drug discovery.