A general assay platform to study protein pharmacology using ligand-dependent structural dynamics

Drug design strategies represent a fundamental challenge in chemical biology that could benefit from the development of next-generation high-throughput assays. Here we demonstrate that structural dynamic changes induced by ligand binding can be transmitted to a sensor protein fused to a target protein terminus. Here, NanoLuc luciferase, used as the intact protein or its α-complementation peptide, was fused to seven proteins from distinct enzyme superfamilies resulting in sensitive ligand-dependent bioluminescent outputs. This finding allows a general non-competitive, function-independent, quantitative, isothermal gain-of-signal ligand binding readout. As applied to chemical library high throughput screening, we can observe multivariate pharmacologic outputs including cofactor-induced synergy in ligand binding, as well as an example of allosteric site binding. The structural dynamics response assay format described here can enable the investigation of proteins precluded from study due to cost-prohibitive, insensitive, or technically challenging assays, including from cell lysates containing endogenously expressed gene edited proteins.

Authors

Institutions

Publication Details

Journal
Nature Communications
Published
2025-05-09
DOI
https://doi.org/10.1038/s41467-025-59658-6
Citations
2
Primary Topic
Advanced Biosensing Techniques and Applications
Type
article
Field-Weighted Citation Impact
1.61

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A general assay platform to study protein pharmacology using ligand-dependent structural dynamics

Ravi Tharakan, Kelli M. Wilson, Renier H. P. van Neer, Mahesh Aitha et al.
2 citations
Nature Communications
Advanced Biosensing Techniques and Applications
1.61
article

A general assay platform to study protein pharmacology using ligand-dependent structural dynamics

Ravi Tharakan, Kelli M. Wilson, Renier H. P. van Neer, Mahesh Aitha, Patricia Dranchak, John Braisted, Daniel A. Ciulla, James Inglese, Divia Shah, Yuhong Wang
article en
2 citations

Abstract

Drug design strategies represent a fundamental challenge in chemical biology that could benefit from the development of next-generation high-throughput assays. Here we demonstrate that structural dynamic changes induced by ligand binding can be transmitted to a sensor protein fused to a target protein terminus. Here, NanoLuc luciferase, used as the intact protein or its α-complementation peptide, was fused to seven proteins from distinct enzyme superfamilies resulting in sensitive ligand-dependent bioluminescent outputs. This finding allows a general non-competitive, function-independent, quantitative, isothermal gain-of-signal ligand binding readout. As applied to chemical library high throughput screening, we can observe multivariate pharmacologic outputs including cofactor-induced synergy in ligand binding, as well as an example of allosteric site binding. The structural dynamics response assay format described here can enable the investigation of proteins precluded from study due to cost-prohibitive, insensitive, or technically challenging assays, including from cell lysates containing endogenously expressed gene edited proteins.

Nature CommunicationsVol. 16(1)
National Human Genome Research Institute (US), National Center for Advancing Translational Sciences (US)
U.S. Department of Health and Human Services, National Institutes of Health, National Center for Advancing Translational Sciences
Openalex Percentile: Top 17%
Advanced Biosensing Techniques and Applications
1.61
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.