Background:The global outbreak of the 2019 novel Coronavirus Disease (COVID-19) caused by the infection with the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), which appeared in China at the end of2019, signifies a major public health issue at the current time.Objective: The objective of the present study is to characterize the physicochemical properties of the SARS-CoV-2 proteins at a residues level, and to generate a “bioinformatics fingerprint” in the form of a “PIM® profile” created for eachsequence utilizing the Polarity Index Method® (PIM®), suitable for the identification of these proteins.Methods:Two different bioinformatics approaches were used to analyze sequence characteristics of these proteins atthe residues level, an in-house bioinformatics system PIM®, and a set of the commonly used algorithms for the predic-tion of protein intrinsic disorder predisposition, such as PONDR® VLXT, PONDR® VL3, PONDR® VSL2, PONDR®FIT, IUPred_short and IUPred_long. The PIM® profile was generated for four SARS-CoV-2 structural proteins andcompared with the corresponding profiles of the SARS-CoV-2 non-structural proteins, SARS-CoV-2 putative proteins,SARS-CoV proteins, MERS-CoV proteins, sets of bacterial, fungal, and viral proteins, cell-penetrating peptides, and aset of intrinsically disordered proteins. We also searched for the UniProt proteins with PIM® profiles similar to those ofSARS-CoV-2 structural, non-structural, and putative proteins.Results:We show that SARS-CoV-2 structural, non-structural, and putative proteins are characterized by a uniquePIM® profile. A total of 1736 proteins were identified from the 562,253 “reviewed” proteins from the UniProt database,whose PIM® profile was similar to that of the SARS-CoV-2 structural, non-structural, and putative proteins.Conclusion:The PIM® profile represents an important characteristic that might be useful for the identification of proteins similar to SARS-CoV-2 proteins.

中文翻译：

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使用极性指数方法® (PIM®) 和内在疾病易感性对 SARS-CoV-2 相关蛋白质进行基于生物信息学的表征

以及一组用于预测蛋白质内在疾病易感性的常用算法，例如 PONDR® VLXT、PONDR® VL3、PONDR® VSL2、PONDR®FIT、IUPred_short 和 IUPred_long。为四种 SARS-CoV-2 结构蛋白生成 PIM® 图谱，并与 SARS-CoV-2 非结构蛋白、SARS-CoV-2 推定蛋白、SARS-CoV 蛋白、MERS-CoV 蛋白、一组细菌、真菌和病毒蛋白质、细胞穿透肽和一组本质上无序的蛋白质。我们还搜索了具有与 SARS-CoV-2 结构、非结构和推定蛋白相似的 PIM® 谱的 UniProt 蛋白。结果：我们显示了 SARS-CoV-2 结构、非结构和推定蛋白的特征通过独特的 PIM® 配置文件。