Computational Analysis of Marburg Virus Envelope Glycoproteins: Insights from Bioinformatics and Genomics

Abstract

Background: Marburg virus (MARV), which is spread by one species of fruit bats, can cause deadly Marburg virus disease (MVD, also known as Marburg hemorrhagic fever, MHF), which is a severe form of viral hemorrhagic fever with symptoms similar to Ebola. MARV is considered to be very dangerous, and there are no approved vaccines or antiviral treatments for Marburg disease. Objective: Computational studies were conducted to comprehend the envelope glycoproteins GP1 and GP2 expressed by the Marburg virus. Methods: Determination of the predicted intrinsic disorder predisposition of each glycoprotein sequence (PIDP) and the Polarity Index Method Profile 3.0v (PIM 3.0v) using genomics software and multiple computer algorithms, several of which have been specifically designed for this purpose. Results: The PIM 3.0v and PIDP profiles showed different MARV envelope glycoprotein patterns. These patterns revealed structural and morphological commonalities. Conclusions: Our computer systems were able to identify MARV envelope glycoprotein isolates using the PIM 3.0v profile, and they suggest that they can be used as a first-step filter for identifying them from databases or building synthetic proteins.