4.7 Article

Antivirals virtual screening to SARS-CoV-2 non-structural proteins

期刊

JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
卷 40, 期 19, 页码 8989-9003

出版社

TAYLOR & FRANCIS INC
DOI: 10.1080/07391102.2021.1921033

关键词

COVID-19; SARS-CoV-2; Non-structural proteins; Molecular docking; Molecular dynamics

资金

  1. Fundacao de Amparo a Pesquisa do Estado de Minas Gerais

向作者/读者索取更多资源

The study conducted virtual screening of 22 antiviral drugs using molecular docking and molecular dynamics simulations, identifying paritaprevir and simeprevir as promising multi-target drugs that effectively bound to key proteins of SARS-CoV-2.
In March 2020, the World Health Organization (WHO) declared coronavirus disease-19 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a pandemic. Since then, the search for a vaccine or drug for COVID-19 treatment has started worldwide. In this regard, a fast approach is the repurposing of drugs, primarily antiviral drugs. Herein, we performed a virtual screening using 22 antiviral drugs retrieved from the DrugBank repository, azithromycin (antibiotic), ivermectin (antinematode), and seven non-structural proteins (Nsps) of SARS-CoV-2, which are considered important targets for drugs, via molecular docking and molecular dynamics simulations. Drug-receptor binding energy was employed as the main descriptor. Based on the results, paritaprevir was predicted as a promising multi-target drug that favorably bound to all tested Nsps, mainly adipose differentiation-related protein (ADRP) (-36.2 kcal mol(-1)) and coronavirus main proteinase (Mpro) (-32.2 kcal mol(-1)). Moreover, the results suggest that simeprevir is a strong inhibitor of Mpro (-37.2 kcal mol(-1)), which is an interesting finding because Mpro plays an important role in viral replication. In addition to drug-receptor affinity, hot spot residues were characterized to facilitate the design of new drug derivatives with improved biological responses.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据