دورية أكاديمية

First report on the QSAR modelling and multistep virtual screening of the inhibitors of nonstructural protein Nsp14 of SARS-CoV-2: Reducing unnecessary chemical synthesis and experimental tests

التفاصيل البيبلوغرافية
العنوان: First report on the QSAR modelling and multistep virtual screening of the inhibitors of nonstructural protein Nsp14 of SARS-CoV-2: Reducing unnecessary chemical synthesis and experimental tests
المؤلفون: Qianqian Wang, Tengjiao Fan, Runqing Jia, Na Zhang, Lijiao Zhao, Rugang Zhong, Guohui Sun
المصدر: Arabian Journal of Chemistry, Vol 17, Iss 3, Pp 105614- (2024)
بيانات النشر: Elsevier, 2024.
سنة النشر: 2024
المجموعة: LCC:Chemistry
مصطلحات موضوعية: COVID-19, SARS-CoV-2, Nsp14 inhibitor, QSAR, Docking, ADMET, Chemistry, QD1-999
الوصف: Corona Virus Disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), poses a serious threat to human health and life safety. How to effectively prevent and treat COVID-19 is crucial. In this study, we used the inhibitors of nonstructural protein Nsp14 of SARS-CoV-2 to perform the quantitative structure activity relationship (QSAR) modelling for the first time. Based on different dataset division strategies, we selected partial least square (PLS) and multiple linear regression (MLR) methods to develop easily interpretable and reproducible QSAR models with 2D molecular descriptors. All models complied with the strict QSAR validation principles of OECD and internationally recognized validation metrics. The best model contained two molecular descriptors with the following statistical parameters: R2 = 0.7796, QLOO2= 0.7373, Rtest2 = 0.8539 and CCCtest = 0.9073. Obviously, the model exhibited good prediction performance and can be used for quickly predicting the inhibitory activity of unknown compounds against Nsp14. Mechanistic interpretation identified the detailed relationship between molecular structure information and inhibitory activity. The best QSAR model was used to predict the inhibitory activity of 263 true external compounds without experimental values against Nsp14, and the prediction reliability was analyzed and discussed. Molecular docking and ADMET analyses were conducted for compounds with higher similarity to the modelling compounds. Finally, two compounds were identified as potential candidate drugs of targeting Nsp14. The current work lays a solid theoretical foundation for the discovery of inhibitors targeting Nsp14, and has an important reference significance for the development of anti-COVID-19 drugs.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1878-5352
Relation: http://www.sciencedirect.com/science/article/pii/S1878535224000169; https://doaj.org/toc/1878-5352
DOI: 10.1016/j.arabjc.2024.105614
URL الوصول: https://doaj.org/article/251e5f1ad2e14ab3b23be90e3846796e
رقم الأكسشن: edsdoj.251e5f1ad2e14ab3b23be90e3846796e
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:18785352
DOI:10.1016/j.arabjc.2024.105614