ArticleMolecular systems biology2021
The genotype-phenotype landscape of an allosteric protein.
Article in Molecular systems biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 39 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
39 citing papers in PubMed, 68 citations in OpenAlex.
- Distinct energetic blueprints diversify function of conserved protein folds.Nature chemistry · 2026Article
- Using enantioselective biosensors to evolve asymmetric biocatalysts.Nature chemical biology · 2026Article
- The genetic architecture of an allosteric hormone receptor.Nature communications · 2026Article
- Generative design of synthetic gene circuits for functional and evolutionary properties.NPJ systems biology and applications · 2026Article
- Mapping the phenotypic landscape of a transcriptional repressor using deep mutational scanning and growth-based quantitative sequencing.Nucleic acids research · 2026Article
- Multiplexed assays of variant effect for clinical variant interpretation.Nature reviews. Genetics · 2026Review
- Computational design of allulose-responsive biosensor toolbox for auto-inducible protein expression and CRISPRi mediated dynamic metabolic regulation.Nature communications · 2025Article
- Identification and understanding of allostery hotspots in proteins: Integration of deep mutational scanning and multi-faceted computational analyses.Journal of molecular biology · 2025Review
- Dynamic Allostery: Evolution's Double-Edged Sword in Protein Function and Disease.Journal of molecular biology · 2025Review
- Learning sequence-function relationships with scalable, interpretable Gaussian processes.bioRxiv : the preprint server for biology · 2025Article
- Importance of higher-order epistasis in protein sequence-function relationships.bioRxiv : the preprint server for biology · 2025Article
- Machine learning in molecular biophysics: Protein allostery, multi-level free energy simulations, and lipid phase transitions.Biophysics reviews · 2025Review
- Transfer learning for cross-context prediction of protein expression from 5'UTR sequence.Nucleic acids research · 2024Article
- A parameterized two-domain thermodynamic model explains diverse mutational effects on protein allostery.eLife · 2024Article
- Engineering is evolution: a perspective on design processes to engineer biology.Nature communications · 2024Article
- A parametrized two-domain thermodynamic model explains diverse mutational effects on protein allostery.bioRxiv : the preprint server for biology · 2024Article
- Accelerating Genetic Sensor Development, Scale-up, and Deployment Using Synthetic Biology.Biodesign research · 2024Article
- Advances in ligand-specific biosensing for structurally similar molecules.Cell systems · 2023Review
- Applications of artificial intelligence and machine learning in dynamic pathway engineering.Biochemical Society transactions · 2023Review
- Divergent directed evolution of a TetR-type repressor towards aromatic molecules.Nucleic acids research · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Allostery is a fundamental biophysical mechanism that underlies cellular sensing, signaling, and metabolism. Yet a quantitative understanding of allosteric genotype-phenotype relationships remains elusive. Here, we report the large-scale measurement of the genotype-phenotype landscape for an allosteric protein: the lac repressor from Escherichia coli, LacI. Using a method that combines long-read and short-read DNA sequencing, we quantitatively measure the dose-response curves for nearly 10
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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.