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On Drug-Membrane Permeability of Antivirals for SARS-CoV-2.
Liu, Changjiang; Elvati, Paolo; Violi, Angela.
  • Liu C; Biophysics Program, University of Michigan, Ann Arbor, Michigan 48109-2125, United States.
  • Elvati P; Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan 48109-2125, United States.
  • Violi A; Biophysics Program, University of Michigan, Ann Arbor, Michigan 48109-2125, United States.
J Phys Chem Lett ; 12(5): 1384-1389, 2021 Feb 11.
Article in English | MEDLINE | ID: covidwho-1052086
ABSTRACT
One of the key parameters required to identify effective drugs is membrane permeability, as a compound intended for an intracellular target with poor permeability will have low efficacy. In this paper, we leverage a computational approach recently developed by our group to study the interactions between nanoparticles and mammalian membranes to study the time of entry of a variety of drugs into the viral envelope of coronavirus as well as cellular organelles. Using a combination of all-atoms molecular dynamics simulations and statistical analysis, we consider both drug characteristics and membrane properties to determine the behavior of 79 drugs and their interactions with the viral envelope, composed of the membrane and spike protein, as well as five other membranes that correspond to various mammalian compartments (lysosome, plasma, Golgi, mitochondrial, and endoplasmic reticulum membranes). The results highlight important trends that can be exploited for drug design, from the relatively high permeability of the viral envelope and the effect of transmembrane proteins, to the differences in permeability between organelles. When compared with bioavailability data present in the literature, the model results suggest a negative correlation between time of permeation and bioavailability of promising drugs. The method is general and flexible and can be employed for a variety of molecules, from small drugs to small nanoparticles, as well to a variety of biological membranes. Overall, the results indicate that this model can contribute to the identification of successful drugs as it predicts the ability of compounds to reach both intended and unintended intracellular targets.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Antiviral Agents / SARS-CoV-2 / COVID-19 Drug Treatment Type of study: Prognostic study Limits: Humans Language: English Journal: J Phys Chem Lett Year: 2021 Document Type: Article Affiliation country: Acs.jpclett.0c02397

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Antiviral Agents / SARS-CoV-2 / COVID-19 Drug Treatment Type of study: Prognostic study Limits: Humans Language: English Journal: J Phys Chem Lett Year: 2021 Document Type: Article Affiliation country: Acs.jpclett.0c02397