论文标题
通过研究现有蛋白质 - 药物和蛋白质 - 蛋白质结构来识别潜在的COVID-19药物治疗：动力活性残基的分析
Recognition of potential Covid-19 drug treatments through the study of existing protein-drug and protein-protein structures: an analysis of kinetically active residues
论文作者
论文摘要
我们根据应用各种生物信息学预测方法的应用，报告了我们研究的批准药物研究的结果作为Covid 19的潜在治疗方法。所研究的药物包括氯喹，伊维菌素，雷姆德西维尔，索福斯布韦，boceprevir和α-二氟甲基氨基氨酸（DMFO）。我们的结果表明，这些小分子选择性地结合了稳定的，动力活性的残基和残基在蛋白质和蛋白质袋的表面上毗邻，并且有些人比其他活性位点更喜欢疏水。我们的方法不仅限于病毒，而且可以促进合理的药物设计，也可以提高我们对分子相互作用的理解。
We report the results of our study of approved drugs as potential treatments for COVID 19, based on the application of various bioinformatics predictive methods. The drugs studied include chloroquine, ivermectin, remdesivir, sofosbuvir, boceprevir, and α-difluoromethylornithine (DMFO). Our results indicate that these small molecules selectively bind to stable, kinetically active residues and residues adjoining them on the surface of proteins and inside protein pockets and that some prefer hydrophobic over other active sites. Our approach is not restricted to viruses and can facilitate rational drug design, as well as improve our understanding of molecular interactions, in general.
