Carlos Polanco*, Vladimir N. Uversky, Guy W. Dayhoff II, Alberto Huberman, Thomas Buhse, Manlio F. Márquez, Gilberto Vargas-Alarcón, Jorge Alberto Castañón-González, Leire Andrés, Juan Luciano Dı́az-González and Karina González-Bañales
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 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®), suitable 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 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 and compared 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 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 characterized 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 proteins similar to SARS-CoV-2 proteins.
Severe Acute Respiratory Syndrome 2 proteins, antimicrobial peptides, structural proteomics, bioinformatics, intrinsic disorder predisposition, PIM® profile.
Department of Electromechanical Instrumentation, Instituto Nacional de Cardiología “Ignacio Chávez”, México City 14800, Department of Molecular Medicine and USF Health Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida, Tampa, FL 33647, Department of Molecular Medicine and USF Health Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida, Tampa, FL 33647, Department of Biochemistry, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, C.P. 14080 México City, Centro de Investigaciones Químicas, Universidad Autónoma del Estado de Morelos, Cuernavaca Morelos 62209, Subdirección de Investigación Clínica, Instituto Nacional de Cardiología “Ignacio Chávez”, México City 14800, Dirección de Investigación, Instituto Nacional de Cardiología “Ignacio Chávez”, México City 14800, Department of Critical Care Medicine, Hospital Juárez de México, México City 07760, Department of Pathology, Hospital de Cruces, 48903, Barakaldo, Department of Computer Sciences, Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, México City 04510, Department of Mathematics, Faculty of Sciences, Universidad Nacional Autónoma de México, México City 04510