ArticleScientific reports2023
Optimizing variant-specific therapeutic SARS-CoV-2 decoys using deep-learning-guided molecular dynamics simulations.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 15 citations in OpenAlex.
- Drug repurposing against viral infections (2020-2025): clinical trials, computational strategies, and therapeutic interventions.Inflammopharmacology · 2026Review
- Optimized ACE2-Fc fusion proteins with picomolar neutralization activity against highly evolved SARS-CoV-2 variants.Protein science : a publication of the Protein Society · 2026Article
- A combinatorial and computational Tandem approach towards a universal therapeutics against ACE2-mediated coronavirus infections.iScience · 2025Article
- Deep Learning Reaction Framework (DLRN) for kinetic modeling of time-resolved data.Communications chemistry · 2025Article
- Variant-proof high affinity ACE2 antagonist limits SARS-CoV-2 replication in upper and lower airways.Nature communications · 2024Article
- Folding the human proteome using BioNeMo: A fused dataset of structural models for machine learning purposes.Scientific data · 2024Article
- Accelerating Biocatalysis Discovery with Machine Learning: A Paradigm Shift in Enzyme Engineering, Discovery, and Design.ACS catalysis · 2023Review
- Identification and validation of fusidic acid and flufenamic acid as inhibitors of SARS-CoV-2 replication using DrugSolver CavitomiX.Scientific reports · 2023Article
- Exploring and Learning the Universe of Protein Allostery Using Artificial Intelligence Augmented Biophysical and Computational Approaches.Journal of chemical information and modeling · 2023Review
- In-silico approaches for identification of compounds inhibiting SARS-CoV-2 3CL protease.PloS one · 2023Article
Corrections and comments
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Authors and funding
24 authors at 4 institutions in 2 countries.
Funding
Abstract
Treatment of COVID-19 with a soluble version of ACE2 that binds to SARS-CoV-2 virions before they enter host cells is a promising approach, however it needs to be optimized and adapted to emerging viral variants. The computational workflow presented here consists of molecular dynamics simulations for spike RBD-hACE2 binding affinity assessments of multiple spike RBD/hACE2 variants and a novel convolutional neural network architecture working on pairs of voxelized force-fields for efficient search-space reduction. We identified hACE2-Fc K31W and multi-mutation variants as high-affinity candidates, which we validated in vitro with virus neutralization assays. We evaluated binding affinities of these ACE2 variants with the RBDs of Omicron BA.3, Omicron BA.4/BA.5, and Omicron BA.2.75 in silico. In addition, candidates produced in Nicotiana benthamiana, an expression organism for potential large-scale production, showed a 4.6-fold reduction in half-maximal inhibitory concentration (IC
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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.