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Ligand Binding Sites

Ligand Binding Sites

Ligand Binding Sites

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...

Quantitative Aspects of Drug-Receptor Interaction

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The receptor occupancy theory connects a drug's response to the number of occupied receptors. With higher drug concentrations, more receptors are occupied, leading to increased responses. The formation of drug-receptor complexes involves association and dissociation rates, which reach equilibrium when the forward and backward reactions are equal. The equilibrium association constant (Ka) and its inverse, the equilibrium dissociation constant (Kd), indicate drug affinity. Higher Ka and lower...

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Related Experiment Video

Updated: May 7, 2026

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Published on: May 9, 2025

Charting spatial ligand-target activity using Renoir.

Narein Rao¹, Tanush Kumar², Dina Kazemi³

¹Department of Computer Science and Engineering, Indian Institute of Technology Kanpur, Kanpur, India.

Nature Communications

|May 5, 2026

Summary

This summary is machine-generated.

Renoir maps ligand-target activities in spatial niches, revealing cell-cell communication critical for understanding tissue microenvironments in development and disease.

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Area of Science:

Single-cell RNA sequencing
Spatial transcriptomics
Cellular interactions
Tissue microenvironment

Background:

Advances in single-cell RNA sequencing and spatial transcriptomics enable inference of cellular interactions.
Existing methods lack the ability to map ligand influence on downstream target genes across spatial niches.
Resolving niche-specific ligand-target relationships is crucial for understanding tissue microenvironments.

Purpose of the Study:

To present Renoir, a novel method for charting ligand-target activities across spatial topology.
To delineate spatial communication niches defined by specific ligand-target activities.
To spatially map pathway-level activity of gene sets.

Main Methods:

Renoir analyzes spatial transcriptomics data at varying resolutions (spot to single-cell).
It infers cellular niches with distinct ligand-target interactions.
It maps pathway activities and identifies context-specific cell-cell interactions.

Main Results:

Renoir successfully inferred distinct ligand-target interactions in various spatial niches across development and disease datasets.
The method spatially mapped pathway activities and identified context-specific cell-cell interactions.
Identified key interactions, including hepatocyte-macrophage interactions in fetal liver and cell interactions in hepatocellular carcinoma.

Conclusions:

Renoir uncovers biological insights and therapeutically relevant cellular crosstalk from spatial transcriptomics data.
The method provides a powerful tool for dissecting complex cellular communication within tissue microenvironments.
Renoir advances the understanding of niche-specific ligand-target relationships and their implications in biological processes and diseases.