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Related Concept Videos

Drug Nomenclature01:17

Drug Nomenclature

During the development of a new pharmaceutical, the manufacturer initially assigns a code name to the drug. Once approved, the drug receives a United States Adopted Name (USAN)—a generic, nonproprietary designation. Upon being listed in the United States Pharmacopeia, this nonproprietary name becomes the drug's official name. Additionally, the manufacturer assigns a proprietary name or trademark, which serves as the brand name under which the drug is marketed. It is worth noting that the same...
Therapeutic Drug Monitoring: Overview and Classification01:16

Therapeutic Drug Monitoring: Overview and Classification

Therapeutic Drug Monitoring (TDM) is a clinical practice that measures specific drug levels in a patient's blood at designated intervals to ensure the drug concentration stays within a therapeutic range. This monitoring is crucial for optimizing individual dosage regimens, enhancing therapeutic efficacy, and minimizing drug-related toxicity. TDM is vital for drugs with narrow therapeutic windows, significant variability in pharmacokinetics, and a clear correlation between plasma levels and...
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...
Principles of Drug Action01:24

Principles of Drug Action

Drugs are chemical substances that modify biological responses by interacting with macromolecular targets such as receptors, ion channels, transporters, and enzymes. Pharmacodynamics describes the course of action of drugs leading to the physiological effect at a specific site in the body.
Drugs can be agonists or antagonists. Like the endogenous ligands, agonists always bind and activate the target to produce a cellular response. Agonist binding induces a conformational change which in turn...
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Therapeutic Drug Monitoring: Drug Analysis Methods

Therapeutic Drug Monitoring (TDM) is a clinical practice that measures specific drug levels in a patient's blood or body tissues to tailor drug therapy effectively. This monitoring is critical for managing drugs with narrow therapeutic indices like digoxin and phenytoin, ensuring they are both safe and effective. For instance, monitoring theophylline levels in asthma patients involves precision and sensitivity to adjust doses according to individual responses to therapy, ensuring efficacy and...

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Related Experiment Video

Updated: May 12, 2026

Network Pharmacology Prediction and Experimental Validation of Trichosanthes-Fritillaria thunbergii Action Mechanism Against Lung Adenocarcinoma
13:18

Network Pharmacology Prediction and Experimental Validation of Trichosanthes-Fritillaria thunbergii Action Mechanism Against Lung Adenocarcinoma

Published on: March 3, 2023

Network predicting drug's anatomical therapeutic chemical code.

Yong-Cui Wang1, Shi-Long Chen, Nai-Yang Deng

  • 1Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China.

Bioinformatics (Oxford, England)
|April 9, 2013
PubMed
Summary

A new computational method, NetPredATC, accurately predicts drug Anatomical Therapeutic Chemical (ATC) codes by integrating chemical structures and drug-target interactions. This approach enhances drug mechanism understanding and aids in drug discovery and repositioning.

Related Experiment Videos

Last Updated: May 12, 2026

Network Pharmacology Prediction and Experimental Validation of Trichosanthes-Fritillaria thunbergii Action Mechanism Against Lung Adenocarcinoma
13:18

Network Pharmacology Prediction and Experimental Validation of Trichosanthes-Fritillaria thunbergii Action Mechanism Against Lung Adenocarcinoma

Published on: March 3, 2023

Area of Science:

  • Pharmacology and Cheminformatics
  • Computational Drug Discovery
  • Bioinformatics

Background:

  • Understanding drug classification at the molecular level is crucial for drug action.
  • Computational methods for predicting drug Anatomical Therapeutic Chemical (ATC) codes are limited.
  • Drug-target interactions and chemical structures are key to drug classification.

Purpose of the Study:

  • To develop a novel computational method, NetPredATC, for predicting drug ATC codes.
  • To integrate drug chemical structures and target protein information for improved ATC code prediction.
  • To validate the efficacy of NetPredATC against existing methods.

Main Methods:

  • Constructed a gold-standard dataset from ATC code annotation databases.
  • Characterized drugs and ATC codes by similarity profiles using kernel functions.
  • Employed a support vector machine (SVM) with a kernel method for ATC code prediction.
  • Integrated drug chemical structure and target protein data.

Main Results:

  • NetPredATC accurately predicts drug ATC codes by integrating chemical structures and target proteins.
  • Target protein information demonstrated higher predictive accuracy than chemical structure alone.
  • The integrated approach yielded more experimentally validated ATC codes.
  • NetPredATC outperformed the chemical similarity-based method SuperPred in both coverage and accuracy.

Conclusions:

  • NetPredATC offers a more accurate prediction of drug ATC codes by leveraging drug-target networks and integrated data.
  • This method advances the understanding of drug mechanisms.
  • NetPredATC facilitates drug repositioning and discovery efforts.