ArticleeLife2022
Ligand-induced shifts in conformational ensembles that describe transcriptional activation.
Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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Who cites it
8 citing papers in PubMed, 14 citations in OpenAlex.
- Lactylation Converts ABHD6 into a Mitochondrial Regulator That Drives Lenvatinib Resistance in Hepatocellular Carcinoma.Cancer research · 2026Article
- DNA induces non-canonical dimerization of the farnesoid X receptor.Nucleic acids research · 2026Article
- Undirected Exploration of Binding Pockets with Flexible Topology.Journal of chemical theory and computation · 2025Article
- Drug resistance and tumor heterogeneity: cells and ensembles.Biophysical reviews · 2025Review
- Simulations Reveal Unique Roles for the FXR Hinge in the FXR-RXR Nuclear Receptor Heterodimer.ACS bio & med chem Au · 2025Article
- Illuminating ligand-induced dynamics in nuclear receptors through MD simulations.Biochimica et biophysica acta. Gene regulatory mechanisms · 2024Review
- Cell phenotypes can be predicted from propensities of protein conformations.Current opinion in structural biology · 2023Review
- Ligand-induced shifts in conformational ensembles that describe transcriptional activation.eLife · 2022Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Nuclear receptors function as ligand-regulated transcription factors whose ability to regulate diverse physiological processes is closely linked with conformational changes induced upon ligand binding. Understanding how conformational populations of nuclear receptors are shifted by various ligands could illuminate strategies for the design of synthetic modulators to regulate specific transcriptional programs. Here, we investigate ligand-induced conformational changes using a reconstructed, ancestral nuclear receptor. By making substitutions at a key position, we engineer receptor variants with altered ligand specificities. We combine cellular and biophysical experiments to characterize transcriptional activity, as well as elucidate mechanisms underlying altered transcription in receptor variants. We then use atomistic molecular dynamics (MD) simulations with enhanced sampling to generate ensembles of wildtype and engineered receptors in combination with multiple ligands, followed by conformational analysis and correlation of MD-based predictions with functional ligand profiles. We determine that conformational ensembles accurately describe ligand responses based on observed population shifts. These studies provide a platform which will allow structural characterization of physiologically-relevant conformational ensembles, as well as provide the ability to design and predict transcriptional responses in novel ligands.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.