The number of fatalities and economic losses caused by the Ebola virus infection across the planet culminated in the havoc that occurred between August and November 2014. However, little is known about the molecular protein profile of this devastating virus. This work represents a thorough bioinformatics analysis of the regularities of charge distribution (polar profiles) in two groups of proteins and their functional domains associated with Ebola virus disease: Ebola virus proteins and Human proteins interacting with Ebola virus. Our analysis reveals that a fragment exists in each of these proteins-one named the "functional domain"-with the polar profile similar to the polar profile of the protein that contains it. Each protein is formed by a group of short sub-sequences, where each fragment has a different and distinctive polar profile and where the polar profile between adjacent short sub-sequences changes orderly and gradually to coincide with the polar profile of the whole protein. When using the charge distribution as a metric, it was observed that it effectively discriminates the proteins from their functional domains. As a counterexample, the same test was applied to a set of synthetic proteins built for that purpose, revealing that any of the regularities reported here for the Ebola virus proteins and human proteins interacting with Ebola virus were not present in the synthetic proteins. Our results indicate that the polar profile of each protein studied and its corresponding functional domain are similar. Thus, when building each protein from its functional domai-adding one amino acid at a time and plotting each time its polar profile-it was observed that the resulting graphs can be divided into groups with similar polar profiles.
Preeclampsia, hemorrhage, and infection are the leading causes of maternal death in underdeveloped countries. Since several proteins associated with preeclampsia are known, we conducted a computational study which evaluated the commonness and potential functionality of intrinsic disorder of these proteins and also made an attempt to characterize their origin. The origin of the preeclampsia-related proteins was assessed with a supervised technique, a Polarity Index Method (PIM), which evaluates the electronegativity of proteins based solely on their sequence. The commonness of intrinsic disorder was evaluated using several disorder predictors from the PONDR family, the charge-hydropathy plot (CH-plot) and cumulative distribution function (CDF) analyses, and using the MobiDB web-based tool, whereas potential functionality of intrinsic disorder was studied with the D2P2 resource and ANCHOR predictor of disorder-based binding sites, and the STRING tool was used to build the interactivity networks of the preeclampsia-related proteins. Peculiarities of the PIM-derived polar profile of the group of preeclampsia-related proteins were then compared with profiles of a group of lipoproteins, antimicrobial peptides, angiogenesis-related proteins, and the intrinsically disordered proteins. Our results showed a high graphical correlation between preeclampsia proteins, lipoproteins, and the angiogenesis proteins. We also showed that many preeclampsia-related proteins contain numerous functional disordered regions. Therefore, these bioinformatics results led us to assume that the preeclampsia proteins are highly associated with the lipoproteins group, and that some preeclampsia-related proteins contain significant amounts of functional disorders.
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