ABSTRACT

Perhaps there is some similarity between the coronavirus of 2017 and the COVID-19. Consequently, a predictive model for the antiviral activity for the Middle East respiratory syndrome coronavirus (MERS‐CoV, 2017) could be useful for designing the strategy and tactics in the struggle with coronaviruses in general and with COVID 19 in particular. Quantitative structure-activity relationships (QSARs) of inhibitory activity to MERS-CoV were developed. The index of ideality of correlation was applied to build up these models for the antiviral activity. The statistical quality of the best model is quite good (r² = 0.84). A mechanistic interpretation of these models based on the molecular features with strong positive (i.e. promoters for endpoint increase) and strong negative (i.e. promoters for endpoint decrease) influence on the inhibitory activity is suggested. A collection of possible biologically active compounds, constructed using data on the above molecular features which are statistically reliable promoters of increase or decrease of the activity, is presented.

摘要

也许 2017 年的冠状病毒与 COVID-19 之间存在一些相似之处。因此，中东呼吸综合征冠状病毒（MERS-CoV，2017）抗病毒活性的预测模型可用于设计与一般冠状病毒特别是 COVID 19 斗争的战略和战术。开发了对 MERS-CoV 抑制活性的定量构效关系 (QSAR)。应用相关性理想指数来建立这些抗病毒活性模型。最佳模型的统计质量相当好（r ² = 0.84）。建议基于对抑制活性具有强正影响（即终点增加的启动子）和强负（即终点减少的启动子）影响的分子特征对这些模型进行机械解释。提供了可能的生物活性化合物的集合，这些化合物是使用上述分子特征的数据构建的，这些分子特征是活性增加或减少的统计上可靠的促进剂。