Bioinformatics-Based Characterization of Proteins Related to SARS-CoV-2 Using the Polarity Index Method (R) (PIM (R)) and Intrinsic Disorder Predis-position

Background: : The global outbreak of the 2019 novel Coronavirus disease (COVID-19) caused by infection with the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), which appeared in China at the end of 2019, 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 each sequence utilizing the Polarity Index Method (PIM), suit-able for the identification of these proteins. Methods: Two different bioinformatics approaches were used to analyze sequence characteristics of these proteins at the residues level, an in-house bioinformatics system PIM, and a set of the com-monly used algorithms for the prediction of protein intrinsic disorder predisposition, such as PON-DR VLXT, PONDR VL3, PONDR VSL2, PONDR FIT, IUPred _short and IUPred_long. The PIM profile was generated for four SARS-CoV-2 structural proteins and compared with the correspond-ing 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 a set of intrinsically disordered proteins. We also searched for the UniProt proteins with PIM profiles similar to those of SARS-CoV-2 structural, non-structural, and putative proteins. Results: We show that SARS-CoV-2 structural, non-structural, and putative proteins are character-ized by a unique PIM 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 similar to SARS-CoV-2 protiens