ArticleCell death discovery2022
Microfluidic deep mutational scanning of the human executioner caspases reveals differences in structure and regulation.
Article in Cell death discovery, 2022. 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 13 papers.
What it found
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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.
The trial behind it
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
13 citing papers in PubMed, 14 citations in OpenAlex.
- Megascale recombination generates millions of catalytically competent PETases.bioRxiv : the preprint server for biology · 2026Article
- Why variant effect predictors and multiplexed assays agree and disagree.Nature communications · 2026Article
- Molecular dynamics simulations of intrinsically disordered protein regions enable biophysical interpretation of variant-effect predictors.HGG advances · 2026Article
- A probabilistic graphical model for estimating selection coefficients of nonsynonymous variants from human population sequence data.Nature communications · 2025Article
- Droplet microfluidic screening to engineer angiotensin-converting enzyme 2 (ACE2) catalytic activity.Journal of biological engineering · 2025Article
- A deep mutational scanning platform to characterize the fitness landscape of anti-CRISPR proteins.Nucleic acids research · 2024Article
- Understanding activity-stability tradeoffs in biocatalysts by enzyme proximity sequencing.Nature communications · 2024Article
- ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction.bioRxiv : the preprint server for biology · 2023Article
- Deep mutational scanning of proteins in mammalian cells.Cell reports methods · 2023Review
- Updated benchmarking of variant effect predictors using deep mutational scanning.Molecular systems biology · 2023Article
- Decoupling of catalysis and transition state analog binding from mutations throughout a phosphatase revealed by high-throughput enzymology.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Ultrahigh-Throughput Enzyme Engineering and Discovery inChemical reviews · 2023Review
- From Deep Mutational Mapping of Allosteric Protein Landscapes to Deep Learning of Allostery and Hidden Allosteric Sites: Zooming in on "Allosteric Intersection" of Biochemical and Big Data Approaches.International journal of molecular sciences · 2023Review
Corrections and comments
- Erratum issued
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
The human caspase family comprises 12 cysteine proteases that are centrally involved in cell death and inflammation responses. The members of this family have conserved sequences and structures, highly similar enzymatic activities and substrate preferences, and overlapping physiological roles. In this paper, we present a deep mutational scan of the executioner caspases CASP3 and CASP7 to dissect differences in their structure, function, and regulation. Our approach leverages high-throughput microfluidic screening to analyze hundreds of thousands of caspase variants in tightly controlled in vitro reactions. The resulting data provides a large-scale and unbiased view of the impact of amino acid substitutions on the proteolytic activity of CASP3 and CASP7. We use this data to pinpoint key functional differences between CASP3 and CASP7, including a secondary internal cleavage site, CASP7 Q196 that is not present in CASP3. Our results will open avenues for inquiry in caspase function and regulation that could potentially inform the development of future caspase-specific therapeutics.
Identifiers
What OpenQuestion holds
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.