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作为严重急性呼吸综合征冠状病毒2(SARS-CoV-2)抑制剂的与选择性雌激素受体降解剂艾拉司群相似分子的分子模拟研究

Molecular Modeling Studies of Similar Molecules to Selective Estrogen Receptor Degrader Elacestrant as Inhibitors of SARS-COV-2.

作者信息

Omotoso Oluwadamilare D, Joshua Funsho Oyetunde, Oyebamiji Abel Kolawole, Ebenezer Oluwakemi

机构信息

Department of Bioinformatics, Faculty of Chemistry, Wybrzeze Stanislawa Wyspianskiego,, Waclow University of Science and Technology, Wroclaw, Poland.

Center of excellence for pharmaceutical sciences Northwest University, Potchefstroom, South Africa.

出版信息

Cell Biochem Biophys. 2025 Mar;83(1):741-753. doi: 10.1007/s12013-024-01506-3. Epub 2024 Sep 11.

Abstract

Coronavirus 2019 (COVID-19) is a disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) strain. Many anticancer compounds have been repurposed as effective anti-coronavirus agents and are currently in a clinical trial to be evaluated for treatment. Elacestrant is a novel selective estrogen receptor degrader (SERD). A fingerprint Tanimoto-based 2-dimensional similarity search was performed in the PubChem database using elacestrant as a prototype. The chemical compounds were downloaded, and virtual screening, molecular docking, and molecular dynamics were further used to identify the most active molecules in the binding pocket SARS-COV-2 main protease. Eight compounds with superior docking score, gscore, and glide binding energy were identified. Molecular dynamic simulations (MD) were performed at 100 ns to remove the false interactions between the receptor and the active ligands. The results showed that all the compounds displayed good stability. Further, the ADMET results showed that compounds CID58023104 was observed to be deemed a hit compound; hence, CID58023104 and could be optimize, derivatize, and explore for further development as an anti-coronavirus agent targeting SARS-COV-2 main protease.

摘要

2019冠状病毒病(COVID-19)是由严重急性呼吸综合征冠状病毒2(SARS-COV-2)毒株引起的一种疾病。许多抗癌化合物已被重新用作有效的抗冠状病毒药物,目前正处于临床试验阶段以评估其治疗效果。艾拉司群是一种新型的选择性雌激素受体降解剂(SERD)。以艾拉司群为原型,在PubChem数据库中进行了基于指纹Tanimoto的二维相似性搜索。下载了化学化合物,并进一步使用虚拟筛选、分子对接和分子动力学来确定在严重急性呼吸综合征冠状病毒2主要蛋白酶结合口袋中最具活性的分子。鉴定出了8种具有优异对接分数、gscore和Glide结合能的化合物。进行了100纳秒的分子动力学模拟,以消除受体与活性配体之间的错误相互作用。结果表明,所有化合物均表现出良好的稳定性。此外,ADMET结果显示,化合物CID58023104被认为是一种命中化合物;因此,CID58023104可以进行优化、衍生化,并作为一种靶向严重急性呼吸综合征冠状病毒2主要蛋白酶的抗冠状病毒药物进行进一步开发探索。

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