ArticleMolecular informatics2021
Targeting SARS-CoV-2 Spike Protein/ACE2 Protein-Protein Interactions: a Computational Study.
Article in Molecular informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The trial behind it
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Who cites it
7 citing papers in PubMed, 27 citations in OpenAlex.
- Identification of Covalent Cyclic Peptide Inhibitors Targeting Protein-Protein Interactions Using Phage Display.Journal of the American Chemical Society · 2025Article
- Identification of Covalent Cyclic Peptide Inhibitors Targeting Protein-Protein Interactions Using Phage Display.bioRxiv : the preprint server for biology · 2024Article
- Review
- Virtual screening and molecular dynamics simulations provide insight into repurposing drugs against SARS-CoV-2 variants Spike protein/ACE2 interface.Scientific reports · 2023Article
- Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2.Chemical reviews · 2022Review
- Artificial Intelligence Technologies for COVID-19 De Novo Drug Design.International journal of molecular sciences · 2022Review
- Targeting SARS-CoV-2 Spike Protein/ACE2 Protein-Protein Interactions: a Computational Study.Molecular informatics · 2021Article
Corrections and comments
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Authors and funding
3 authors at 1 institution.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The spike glycoprotein (S) of the SARS-CoV-2 virus surface plays a key role in receptor binding and virus entry. The S protein uses the angiotensin converting enzyme (ACE2) for entry into the host cell and binding to ACE2 occurs at the receptor binding domain (RBD) of the S protein. Therefore, the protein-protein interactions (PPIs) between the SARS-CoV-2 RBD and human ACE2, could be attractive therapeutic targets for drug discovery approaches designed to inhibit the entry of SARS-CoV-2 into the host cells. Herein, with the support of machine learning approaches, we report structure-based virtual screening as an effective strategy to discover PPIs inhibitors from ZINC database. The proposed computational protocol led to the identification of a promising scaffold which was selected for subsequent binding mode analysis and that can represent a useful starting point for the development of new treatments of the SARS-CoV-2 infection.
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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.