{"title":"Insights from computational studies on the potential of natural compounds as inhibitors against SARS-CoV-2 spike omicron variant.","authors":"A A Alzain","doi":"10.1080/1062936X.2022.2152486","DOIUrl":null,"url":null,"abstract":"<p><p>Coronavirus disease 2019 (COVID-19) is a major global health emergency, with more than six million deaths worldwide. It is becoming increasingly challenging to treat COVID-19 due to the emergence of novel variants. The omicron variant is capable to evade defences and spread quickly. Among many validated COVID-19 targets, the spike (S) protein plays an important role in receptor recognition (via the S1 subunit) and membrane fusion (via the S2 subunit). The S protein is one of the vital targets for the development of drugs to combat this illness. In this research, we applied various computational methods such as molecular docking, molecular dynamics, MM-GBSA calculations, and ADMET prediction to identify potential natural products from Saudi medicinal plants against the spike omicron variant. As a result, three compounds (LTS0002490, LTS0117007, and LTS0217912) were identified with better binding affinity to the spike omicron variant compared to the reference compound (VE607). In addition, these compounds showed stable interactions with the target during molecular dynamics simulations for 140 ns. Last, these compounds have optimal ADMET properties. We suggest that these compounds may be considered promising hits to treat COVID-19 if experimentally validated.</p>","PeriodicalId":21446,"journal":{"name":"SAR and QSAR in Environmental Research","volume":"33 12","pages":"953-968"},"PeriodicalIF":2.3000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SAR and QSAR in Environmental Research","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1080/1062936X.2022.2152486","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 5
Abstract
Coronavirus disease 2019 (COVID-19) is a major global health emergency, with more than six million deaths worldwide. It is becoming increasingly challenging to treat COVID-19 due to the emergence of novel variants. The omicron variant is capable to evade defences and spread quickly. Among many validated COVID-19 targets, the spike (S) protein plays an important role in receptor recognition (via the S1 subunit) and membrane fusion (via the S2 subunit). The S protein is one of the vital targets for the development of drugs to combat this illness. In this research, we applied various computational methods such as molecular docking, molecular dynamics, MM-GBSA calculations, and ADMET prediction to identify potential natural products from Saudi medicinal plants against the spike omicron variant. As a result, three compounds (LTS0002490, LTS0117007, and LTS0217912) were identified with better binding affinity to the spike omicron variant compared to the reference compound (VE607). In addition, these compounds showed stable interactions with the target during molecular dynamics simulations for 140 ns. Last, these compounds have optimal ADMET properties. We suggest that these compounds may be considered promising hits to treat COVID-19 if experimentally validated.
期刊介绍:
SAR and QSAR in Environmental Research is an international journal welcoming papers on the fundamental and practical aspects of the structure-activity and structure-property relationships in the fields of environmental science, agrochemistry, toxicology, pharmacology and applied chemistry. A unique aspect of the journal is the focus on emerging techniques for the building of SAR and QSAR models in these widely varying fields. The scope of the journal includes, but is not limited to, the topics of topological and physicochemical descriptors, mathematical, statistical and graphical methods for data analysis, computer methods and programs, original applications and comparative studies. In addition to primary scientific papers, the journal contains reviews of books and software and news of conferences. Special issues on topics of current and widespread interest to the SAR and QSAR community will be published from time to time.