Cargando…
A Novel Computational Approach for the Discovery of Drug Delivery System Candidates for COVID-19
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 m...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7998631/ https://www.ncbi.nlm.nih.gov/pubmed/33802169 http://dx.doi.org/10.3390/ijms22062815 |
_version_ | 1783670596541874176 |
---|---|
author | Cho, Taeheum Han, Hyo-Sang Jeong, Junhyuk Park, Eun-Mi Shim, Kyu-Sik |
author_facet | Cho, Taeheum Han, Hyo-Sang Jeong, Junhyuk Park, Eun-Mi Shim, Kyu-Sik |
author_sort | Cho, Taeheum |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7998631 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-79986312021-03-28 A Novel Computational Approach for the Discovery of Drug Delivery System Candidates for COVID-19 Cho, Taeheum Han, Hyo-Sang Jeong, Junhyuk Park, Eun-Mi Shim, Kyu-Sik Int J Mol Sci Article 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. MDPI 2021-03-10 /pmc/articles/PMC7998631/ /pubmed/33802169 http://dx.doi.org/10.3390/ijms22062815 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Cho, Taeheum Han, Hyo-Sang Jeong, Junhyuk Park, Eun-Mi Shim, Kyu-Sik A Novel Computational Approach for the Discovery of Drug Delivery System Candidates for COVID-19 |
title | A Novel Computational Approach for the Discovery of Drug Delivery System Candidates for COVID-19 |
title_full | A Novel Computational Approach for the Discovery of Drug Delivery System Candidates for COVID-19 |
title_fullStr | A Novel Computational Approach for the Discovery of Drug Delivery System Candidates for COVID-19 |
title_full_unstemmed | A Novel Computational Approach for the Discovery of Drug Delivery System Candidates for COVID-19 |
title_short | A Novel Computational Approach for the Discovery of Drug Delivery System Candidates for COVID-19 |
title_sort | novel computational approach for the discovery of drug delivery system candidates for covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7998631/ https://www.ncbi.nlm.nih.gov/pubmed/33802169 http://dx.doi.org/10.3390/ijms22062815 |
work_keys_str_mv | AT chotaeheum anovelcomputationalapproachforthediscoveryofdrugdeliverysystemcandidatesforcovid19 AT hanhyosang anovelcomputationalapproachforthediscoveryofdrugdeliverysystemcandidatesforcovid19 AT jeongjunhyuk anovelcomputationalapproachforthediscoveryofdrugdeliverysystemcandidatesforcovid19 AT parkeunmi anovelcomputationalapproachforthediscoveryofdrugdeliverysystemcandidatesforcovid19 AT shimkyusik anovelcomputationalapproachforthediscoveryofdrugdeliverysystemcandidatesforcovid19 AT chotaeheum novelcomputationalapproachforthediscoveryofdrugdeliverysystemcandidatesforcovid19 AT hanhyosang novelcomputationalapproachforthediscoveryofdrugdeliverysystemcandidatesforcovid19 AT jeongjunhyuk novelcomputationalapproachforthediscoveryofdrugdeliverysystemcandidatesforcovid19 AT parkeunmi novelcomputationalapproachforthediscoveryofdrugdeliverysystemcandidatesforcovid19 AT shimkyusik novelcomputationalapproachforthediscoveryofdrugdeliverysystemcandidatesforcovid19 |