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.

中文翻译：

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通过计算机研究鉴定新的二氢菲衍生物作为有前景的抗 SARS-CoV-2 药物

摘要

为了研究、评估和发明抑制 SARS-CoV-2 活性的新型化合物，对一系列已报道的 39 种取代的 9, 10-二氢菲衍生物进行了定量构效关系 (QSAR) 研究。Gaussian 09 和 ChemOffice 程序用于计算分子描述符，以确定它们对研究活性的影响。然后，我们通过使用主成分分析（PCA）消除冗余信息来减少描述符的数量。根据经济合作与发展组织 (OECD) 制定的原则，使用多元线性回归 (MLR) 创建分子模型，并使用外部和内部验证、Y 随机化测试和域进行验证的适用性。而且，我们使用 ADMET 和分子对接评估了所开发化合物的毒性，以确定它们形成稳定复合物的最佳位置。因此，四种分子可用于开发一种可以抑制 SARS-CoV-2 而不会引起副作用的新药物。