I. Yamari, Ossama Abchir, H. Nour, M. El kouali, Samir CHTITA
{"title":"Identification of new dihydrophenanthrene derivatives as promising anti-SARS-CoV-2 drugs through in silico investigations","authors":"I. Yamari, Ossama Abchir, H. Nour, M. El kouali, Samir CHTITA","doi":"10.3233/mgc-220127","DOIUrl":null,"url":null,"abstract":"To research, evaluate, and invent novel compounds that inhibit SARS-CoV-2 activity, a series of reported 39 substituted 9, 10-dihydrophenanthrene derivatives were subjected to a quantitative structure-activity relationship (QSAR) study. Gaussian 09 and ChemOffice programs were used to calculate the molecular descriptors employed to determine their impact on the studied activity. Then we reduced the number of descriptors by eliminating the redundant information using principal component analysis (PCA). The creation of molecular models was done by using multiple linear regression (MLR) according to the principles established by the Organization for Economic Co-operation and Development (OECD) and the validation by using external and internal validation, Y-randomization tests, and domain of applicability. Moreover, we evaluated the toxicity of developed compounds using ADMET and Molecular docking to determine their optimal position to form a stable complex. As a result, four molecules may be used to develop a novel drug that can inhibit SARS-CoV-2 without causing the side effect.","PeriodicalId":18027,"journal":{"name":"Main Group Chemistry","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2023-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Main Group Chemistry","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.3233/mgc-220127","RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 7
Abstract
To research, evaluate, and invent novel compounds that inhibit SARS-CoV-2 activity, a series of reported 39 substituted 9, 10-dihydrophenanthrene derivatives were subjected to a quantitative structure-activity relationship (QSAR) study. Gaussian 09 and ChemOffice programs were used to calculate the molecular descriptors employed to determine their impact on the studied activity. Then we reduced the number of descriptors by eliminating the redundant information using principal component analysis (PCA). The creation of molecular models was done by using multiple linear regression (MLR) according to the principles established by the Organization for Economic Co-operation and Development (OECD) and the validation by using external and internal validation, Y-randomization tests, and domain of applicability. Moreover, we evaluated the toxicity of developed compounds using ADMET and Molecular docking to determine their optimal position to form a stable complex. As a result, four molecules may be used to develop a novel drug that can inhibit SARS-CoV-2 without causing the side effect.
期刊介绍:
Main Group Chemistry is intended to be a primary resource for all chemistry, engineering, biological, and materials researchers in both academia and in industry with an interest in the elements from the groups 1, 2, 12–18, lanthanides and actinides. The journal is committed to maintaining a high standard for its publications. This will be ensured by a rigorous peer-review process with most articles being reviewed by at least one editorial board member. Additionally, all manuscripts will be proofread and corrected by a dedicated copy editor located at the University of Kentucky.