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Related Concept Videos

Factors Affecting Protein-Drug Binding: Drug-Related Factors01:18

Factors Affecting Protein-Drug Binding: Drug-Related Factors

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Drug binding to proteins is a complex phenomenon influenced by various drug-related factors, each playing a significant role in the interaction between drugs and proteins within the body.
One crucial factor in drug-protein binding is the drug's lipophilicity or its affinity for fat. More lipophilic drugs tend to have higher binding extents. For example, highly lipophilic drugs like cloxacillin exhibit substantial protein binding, with as much as 95% of the drug binding to proteins. In...
488
Factors Affecting Protein-Drug Binding: Drug Interactions01:23

Factors Affecting Protein-Drug Binding: Drug Interactions

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Drug interactions are a critical aspect of pharmacology and can occur when two or more drugs compete for the same binding site. This competition can result in one drug displacing another, altering the effect of the displaced drug. Drug interactions are complex processes that rely heavily on how much of the displacer drug is present and how strongly it can bind to the same sites as the displaced drug.
Displacement interactions can have varying outcomes, ranging from toxicity to virtually...
611
Factors Affecting Protein-Drug Binding: Protein-Related Factors01:20

Factors Affecting Protein-Drug Binding: Protein-Related Factors

575
Drug binding to proteins is a key aspect of pharmacokinetics and can influence a drug's distribution, absorption, and elimination in the body. Several factors, including the drug's physiochemical properties, protein concentration, disease states, and the number of binding sites on the protein, influence this process.
The physicochemical properties of a drug play a significant role in its ability to bind to proteins. Lipophilic drugs, which dissolve in fats, oils, and lipids, can be...
575
Drug Distribution: Plasma Protein Binding01:29

Drug Distribution: Plasma Protein Binding

9.0K
Drugs predominantly attach to plasma proteins, with only a small percentage remaining unbound. The unbound portion can be calculated as one minus the bound fraction. Acidic drugs form large, inactive complexes by reversibly binding to plasma albumin, which prevents them from diffusing across biological barriers. These drug-protein complexes act as reservoirs for the drugs. As the concentration of unbound drugs decreases, these complexes quickly dissociate to release the free drug, maintaining...
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Protein-Drug Binding: Determination Methods01:22

Protein-Drug Binding: Determination Methods

667
Determining protein-drug binding can be achieved through indirect and direct methods, each providing valuable insights into the interaction between proteins and drugs.
Indirect methods involve isolating the bound drug from its free form in biological samples such as blood, serum, or plasma. These techniques aim to measure the percentage of drugs bound to proteins. Equilibrium dialysis is a commonly used method where the free drug concentration at equilibrium is measured by separating the bound...
667
Protein-Drug Binding: Mechanism and Kinetics01:16

Protein-Drug Binding: Mechanism and Kinetics

1.8K
Protein-drug binding refers to the interaction between drugs and proteins within the body. This binding process can occur intracellularly, involving drug interactions with enzymes or receptors within cells, or extracellularly, involving plasma proteins in the blood.
Various forces drive these interactions, including hydrogen bonds, hydrophobic interactions, ionic bonds, electrostatic interactions, and van der Waals forces. These bonds enable drugs to bind to specific sites on proteins,...
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Related Experiment Video

Updated: Feb 9, 2026

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
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Incorporating Protein Dynamics Through Ensemble Docking in Machine Learning Models to Predict Drug Binding.

Fatemah Alghamedy1, Jeevith Bopaiah1, Derek Jones1

  • 1University of Kentucky, Lexington, KY, USA.

AMIA Joint Summits on Translational Science Proceedings. AMIA Joint Summits on Translational Science
|June 12, 2018
PubMed
Summary

This study enhances drug binding prediction accuracy by combining ensemble docking with machine learning and biomedical data. This approach significantly improves identifying active compounds, paving the way for safer and more efficient drug discovery.

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Area of Science:

  • Computational chemistry
  • Pharmacology
  • Machine learning

Background:

  • Drug discovery is costly, time-consuming, and carries inherent risks.
  • Accurate computational prediction of drug binding is crucial for improving cost-effectiveness and safety in drug development.

Purpose of the Study:

  • To enhance the accuracy of predicting drug binding.
  • To improve the classification of active compounds versus decoys in drug discovery pipelines.

Main Methods:

  • Ensemble docking utilizing multiple protein conformations from molecular dynamics trajectories.
  • Integration of additional biomedical data sources.
  • Application of machine learning algorithms for improved prediction.

Main Results:

  • Significantly increased classification accuracy for active compounds over decoys compared to docking scores alone.
  • Achieved over 99% accuracy when specific protein conformations showed strong correlation with active vs. decoy classification.
  • Demonstrated the potential of the integrated approach to outperform traditional methods.

Conclusions:

  • Accurate drug binding predictions can streamline drug discovery and development.
  • This methodology supports the creation of computational polypharmacology networks for predicting side effects, repurposing drugs, and assessing drug efficacy.