ArticleThe journal of physical chemistry. B2023
Machine Learning Guided Design of High-Affinity ACE2 Decoys for SARS-CoV-2 Neutralization.
Article in The journal of physical chemistry. B, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 9 citations in OpenAlex.
- Disulfide Bond Engineering of Soluble ACE2 for Thermal Stability Enhancement.International journal of molecular sciences · 2024Article
- Genetic diversity and evolutionary dynamics of the Omicron variant of SARS-CoV-2 in Morocco.Pathogens and global health · 2024Article
- The Experimentalist's Guide to Machine Learning for Small Molecule Design.ACS applied bio materials · 2024Review
- SARS-CoV-2 Binding and Neutralization Properties of Peptides Derived from N-Terminus of Human ACE2.International journal of molecular sciences · 2023Article
- Multivalent ACE2 engineering-A promising pathway for advanced coronavirus nanomedicine development.Nano today · 2022Review
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
A potential therapeutic strategy for neutralizing SARS-CoV-2 infection is engineering high-affinity soluble ACE2 decoy proteins to compete for binding to the viral spike (S) protein. Previously, a deep mutational scan of ACE2 was performed and has led to the identification of a triple mutant variant, named sACE2
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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.