Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Protein Networks02:26

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 Interfaces02:04

Protein-protein Interfaces

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...
Drug-Receptor Interactions01:29

Drug-Receptor Interactions

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.
Several parameters, such as the drug's affinity for its receptor and its efficacy, which is its ability to activate the receptor, determine the drug's effect on the tissue.
Targets for Drug Action: Overview01:26

Targets for Drug Action: Overview

Drugs target macromolecules to modify ongoing cellular processes. Primary drug targets include receptors, ion channels, transporters, and enzymes.
Receptors are either membrane-spanning or intracellular proteins, which upon binding a ligand, get activated and transmit the signal downstream to elicit a response. Drugs bind receptors, either mimicking the action of endogenous ligands or blocking the receptor activity to bring about a modified response. Nearly 35% of approved drugs target the G...
Drug-Receptor Interaction: Agonist01:25

Drug-Receptor Interaction: Agonist

Agonists are drugs that interact with specific receptors in the body to produce a biological response. When an agonist binds to a receptor, it activates or enhances the receptor's function, leading to physiological effects. The interaction between agonist drugs and receptors is crucial for their therapeutic action in various medical treatments.
Agonists can bind to receptors in different ways. Some agonists bind directly to the receptor's active site, mimicking the endogenous ligand's action.
The Two-State Receptor Model01:29

The Two-State Receptor Model

The two-state receptor model explains a drug's interaction with receptors, such as G protein-coupled receptors and ligand-gated ion channels, to induce or inhibit a biological response. When no natural ligands are present, a receptor exists in an equilibrium of inactive (Ri) and active (Ra) conformations. The inactive form does not produce a response, while the active form generates a basal effect known as constitutive activity.
The binding affinity of a drug determines its interaction with one...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Protein-nucleic acid binding site prediction using interpretable Kolmogorov-Arnold networks with hypergraph representation learning.

Bioinformatics (Oxford, England)·2026
Same author

The miniaturized vacuum system for cold atom sensors based on the technology of passive vacuum.

Scientific reports·2026
Same author

DeepHFFT-m7G: A dual-channel self-attention and hybrid feature fusion framework for RNA m7G modification identification.

Computational biology and chemistry·2025
Same author

EGCPPIS: learning hierarchical equivariant graph representations with contrastive integration for protein-protein interaction site identification.

BMC bioinformatics·2025
Same author

iDRKAN: Interpretable miRNA-Disease Association Prediction Based on Dual-Graph Representation Learning and Kolmogorov-Arnold Network.

IEEE transactions on computational biology and bioinformatics·2025
Same author

Spatial mapping of cold atom clouds using velocity-selective Raman pulses in differential atom interferometers.

Optics express·2025

Related Experiment Video

Updated: May 23, 2026

Simultaneous Detection of c-Fos Activation from Mesolimbic and Mesocortical Dopamine Reward Sites Following Naive Sugar and Fat Ingestion in Rats
08:07

Simultaneous Detection of c-Fos Activation from Mesolimbic and Mesocortical Dopamine Reward Sites Following Naive Sugar and Fat Ingestion in Rats

Published on: August 24, 2016

FGAIM: Identifying Drug-Target Activation and Inhibition Mechanisms via Inductive Graph Neural Networks Based on

Yi Tang, Yongxian Fan, Guicong Sun

    IEEE Transactions on Computational Biology and Bioinformatics
    |May 21, 2026
    PubMed
    Summary

    This study introduces FGAIM, a novel computational method using graph neural networks (GNNs) to identify drug-target activation and inhibition mechanisms by analyzing fine-grained interactions. FGAIM significantly outperforms existing methods, offering insights into drug discovery and regulatory pathways.

    Related Experiment Videos

    Last Updated: May 23, 2026

    Simultaneous Detection of c-Fos Activation from Mesolimbic and Mesocortical Dopamine Reward Sites Following Naive Sugar and Fat Ingestion in Rats
    08:07

    Simultaneous Detection of c-Fos Activation from Mesolimbic and Mesocortical Dopamine Reward Sites Following Naive Sugar and Fat Ingestion in Rats

    Published on: August 24, 2016

    Area of Science:

    • Computational biology
    • Drug discovery
    • Bioinformatics

    Background:

    • Distinguishing drug-target activation/inhibition mechanisms is vital for drug discovery.
    • Existing computational methods often neglect drug-protein interactions and rely heavily on sequence information.
    • Graph neural networks (GNNs) offer advantages in handling complex, graph-structured data.

    Purpose of the Study:

    • To propose FGAIM, a novel computational method for identifying drug-target activation and inhibition mechanisms.
    • To overcome limitations of existing methods by incorporating fine-grained drug-protein interactions and multi-modal features.
    • To enhance the understanding of drug regulatory pathways and potential therapeutic applications.

    Main Methods:

    • Utilized a multi-scale GNN module for expressive drug molecular embeddings.
    • Constructed protein representations by integrating pre-trained language model (PLM) embeddings and 3D structural information.
    • Employed a GraphSAGE module to extract features from drug and drug-protein interaction graphs, followed by MLP classification.

    Main Results:

    • FGAIM significantly outperformed existing computational approaches on two public datasets.
    • Demonstrated strong generalization capabilities and identified previously unrecognized activation/inhibition relationships.
    • Case studies and attention weight analysis revealed the model's interpretability at the molecular structural level.

    Conclusions:

    • FGAIM effectively identifies drug-target activation and inhibition mechanisms by leveraging fine-grained interactions.
    • The method provides valuable insights for drug discovery and development by capturing complex molecular patterns.
    • FGAIM offers enhanced interpretability, aiding in the understanding of drug action at a structural level.