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https://dx.doi.org/10.48550/ar...
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Recognition of Potential COVID-19 Drug Treatments through the Study of Existing Protein–Drug and Protein–Protein Structures: An Analysis of Kinetically Active Residues

Authors: Perišić, Ognjen;

Recognition of Potential COVID-19 Drug Treatments through the Study of Existing Protein–Drug and Protein–Protein Structures: An Analysis of Kinetically Active Residues

Abstract

We report the results of our in silico study of approved drugs as potential treatments for COVID-19. The study is based on the analysis of normal modes of proteins. The drugs studied include chloroquine, ivermectin, remdesivir, sofosbuvir, boceprevir, and α-difluoromethylornithine (DMFO). We applied the tools we developed and standard tools used in the structural biology community. Our results indicate that small molecules selectively bind to stable, kinetically active residues and residues adjoining them on the surface of proteins and inside protein pockets, and that some prefer hydrophobic sites over other active sites. Our approach is not restricted to viruses and can facilitate rational drug design, as well as improve our understanding of molecular interactions, in general.

Keywords

Models, Molecular, Eflornithine, remdesivir, normal-modes, Antibodies, Viral, sofosbuvir, Microbiology, Antiviral Agents, Article, pharmacology_toxicology, chloroquine, ivermectin, Antigen-Antibody Reactions, protein–drug interactions, Betacoronavirus, boceprevir, Humans, Pandemics, spike glycoprotein, Alanine, Binding Sites, Ivermectin, L-Lactate Dehydrogenase, Drug Repositioning, COVID-19, Chloroquine, Biomolecules (q-bio.BM), proteins, QR1-502, Adenosine Monophosphate, Molecular Docking Simulation, Quantitative Biology - Biomolecules, FOS: Biological sciences, α-difluoromethylornithine (DMFO), Angiotensin-Converting Enzyme 2, Coronavirus Infections, Hydrophobic and Hydrophilic Interactions

  • BIP!
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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    13
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Top 10%
Average
Top 10%
Green
gold