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Protein Networks

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

Protein Networks

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

Protein-protein Interfaces

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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a polypeptide...

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Drug–drug interactions can precipitate toxicity through multiple mechanisms. Absorption interactions alter how drugs enter the body, exemplified when ranitidine increases the absorption of basic drugs, while cholestyramine decreases the levels of propranolol. Protein binding interactions occur when drugs share the same binding sites on plasma proteins. Drugs like aspirin and warfarin, when bound in excess, can lead to increased free drug concentrations, enhancing the potential for...

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Drug-receptor interaction describes the binding of receptors by drugs, but not all drug-receptor interactions result in activation and tissue response. For instance, the binding of agonists activates the receptor to generate a cellular reaction, while antagonists bind to receptors without causing their activation.
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Related Experiment Video

Updated: May 9, 2026

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Published on: December 1, 2020

Predict drug-protein interaction in cellular networking.

Xuan Xiao¹, Jian-Liang Min, Pu Wang

¹Computer Department, Jing- De-Zhen Ceramic Institute, Jing-De-Zhen 333046 China. xxiao@gordonlifescience.org

Current Topics in Medicinal Chemistry

|July 30, 2013

Summary

This study introduces two web servers, iGPCR-Drug and iCDI-PseFpt, to predict interactions between drug compounds and G-protein-coupled receptors (GPCRs) and ion channels, aiding drug development for various diseases.

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Last Updated: May 9, 2026

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Published on: December 1, 2020

Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay (PCA) in Living Cells

Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay (PCA) in Living Cells

Published on: March 3, 2015

Area of Science:

Biochemistry and Pharmacology
Computational Biology and Cheminformatics

Background:

G-protein-coupled receptors (GPCRs) and ion channels are critical drug targets for numerous diseases, including cancer, diabetes, and neurological disorders.
Over 50% of current drugs target GPCRs, highlighting their importance in medicine.
Ion channels are recognized as the next frontier in drug discovery due to their vital physiological roles and disease relevance.

Purpose of the Study:

To introduce two novel web servers, iGPCR-Drug and iCDI-PseFpt, for predicting drug compound interactions.
To facilitate drug discovery efforts targeting GPCRs and ion channels.

Main Methods:

Drug compounds are formulated using 2D molecular fingerprints.
Protein receptors (GPCRs and ion channels) are represented by pseudo amino acid composition derived from grey model theory.
The fuzzy K-nearest neighbor algorithm powers the prediction engine in both web servers.

Main Results:

The iGPCR-Drug web server predicts interactions between drug compounds and GPCRs.
The iCDI-PseFpt web server predicts interactions between drug compounds and ion channels.
Both predictors offer a user-friendly interface with step-by-step guides for researchers.

Conclusions:

The developed web servers provide valuable tools for identifying potential drug-receptor interactions.
These predictors can accelerate the development of novel therapeutics targeting GPCRs and ion channels.
The tools are designed for accessibility to pharmaceutical and medical scientists, simplifying complex computational methods.