A Novel Computational Approach for the Discovery of Drug Delivery System Candidates for COVID-19

Autor: Taeheum Cho, Hyo-Sang Han, Eun-Mi Park, Junhyuk Jeong, Kyu-Sik Shim
Rok vydání: 2021
Předmět:
0301 basic medicine
Databases
Pharmaceutical
Anti-Inflammatory Agents
Nanoparticle
Guanidines
030226 pharmacology & pharmacy
Micelle
lcsh:Chemistry
Drug Delivery Systems
nafamostat
0302 clinical medicine
Drug Stability
micelle nanoparticles
Zeta potential
Cluster Analysis
drug delivery system
lcsh:QH301-705.5
Micelles
Spectroscopy
Drug Carriers
Molecular Structure
General Medicine
Computer Science Applications
Drug repositioning
machine learning
in silico
docking
Drug delivery
Hydrophobic and Hydrophilic Interactions
clustering
molecule mocking
Materials science
Cell Survival
Nanotechnology
unsupervised learning
Article
Catalysis
Inorganic Chemistry
computer-aided drug discovery
03 medical and health sciences
Microscopy
Electron
Transmission
CADD
Humans
Computer Simulation
Particle Size
Physical and Theoretical Chemistry
Molecular Biology
Organic Chemistry
Drug Repositioning
Computational Biology
COVID-19
Glycyrrhizic Acid
Benzamidines
COVID-19 Drug Treatment
030104 developmental biology
lcsh:Biology (General)
lcsh:QD1-999
A549 Cells
Docking (molecular)
Nanoparticles
Particle
Particle size
Zdroj: International Journal of Molecular Sciences, Vol 22, Iss 2815, p 2815 (2021)
International Journal of Molecular Sciences
Volume 22
Issue 6
ISSN: 1422-0067
DOI: 10.3390/ijms22062815
Popis: In order to treat Coronavirus Disease 2019 (COVID-19), we predicted and implemented a drug delivery system (DDS) that can provide stable drug delivery through a computational approach including a clustering algorithm and the Schrödinger software. Six carrier candidates were derived by the proposed method that could find molecules meeting the predefined conditions using the molecular structure and its functional group positional information. Then, just one compound named glycyrrhizin was selected as a candidate for drug delivery through the Schrödinger software. Using glycyrrhizin, nafamostat mesilate (NM), which is known for its efficacy, was converted into micelle nanoparticles (NPs) to improve drug stability and to effectively treat COVID-19. The spherical particle morphology was confirmed by transmission electron microscopy (TEM), and the particle size and stability of 300–400 nm were evaluated by measuring DLSand the zeta potential. The loading of NM was confirmed to be more than 90% efficient using the UV spectrum.
Databáze: OpenAIRE
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