RESUMO
Background: Zika virus, which is widely spread and infects humans through the bites of Aedes albopictus and Aedes aegypti female mosquitoes, represents a serious global health issue. Objective: The objective of the present study is to computationally characterize Zika virus polyproteins (UniProt Name: PRO_0000443018 [residues 1-3423], PRO_0000445659 [residues 1-3423] and PRO_0000435828 [residues 1-3419]) and their envelope proteins using their physico-chemical properties. Methods: To achieve this, the Polarity Index Method (PIM) profile and the Protein Intrinsic Disorder Predisposition (PIDP) profile of 3 main groups of proteins were evaluated: structural proteins extracted from specific Databases, Zika virus polyproteins, and their envelope proteins (E) extracted from UniProt Database. Once the PIM profile of the Zika virus envelope proteins (E) was obtained and since the Zika virus polyproteins were also identified with this profile, the proteins defined as "reviewed proteins" extracted from the UniProt Database were searched for the similar PIM profile. Finally, the difference between the PIM profiles of the Zika virus polyproteins and their envelope proteins (E) was tested using 2 non-parametric statistical tests. Results: It was found and tested that the PIM profile is an efficient discriminant that allows obtaining a "computational fingerprint" of each Zika virus polyprotein from its envelope protein (E). Conclusion: PIM profile represents a computational tool, which can be used to effectively discover Zika virus polyproteins from Databases, from their envelope proteins (E) sequences.
RESUMO
In the last two decades, a group of proteins whose mutations are associated with a disease manifested by episodes of muscle weakness (periodic paralysis), changes in heart rhythm (arrhythmia), and developmental abnormalities has been under constant study. This malady is known as Andersen-Tawil syndrome, with ~60% of cases of this syndrome being caused by 16 mutations in the KCNJ2 gene [UniProt ID: P63252-01-P63252-17]. In this work, we present a computational study designed to obtain a fingerprint of Andersen-Tawil mutated proteins and differentiate them from mutated proteins associated with Brugada syndrome and from functional groups of proteins belonging to APD3, UniProt, and CPPsite databases. We show here that Andersen-Tawil mutated proteins are characterized by specific features that can be used to differentiate, with a high level of certainty (90%), proteins carrying these mutations from similar functional groups, such as mutated proteins associated with Brugada syndrome, and from different functional protein and peptide groups, such as antimicrobial peptides, Cell-Penetrating Peptides, and intrinsically disorder proteins. Therefore, our main results allow us to conjecture that it is possible to identify the group of the Andersen-Tawil mutated proteins by their "PIM profile". Furthermore, when we applied this "fingerprint PIM profile" on the UniProt database, we observed that one protein found in humans [UniProt ID: Q9NZV8], and six of all "reviewed" proteins found in living organisms, possess a very similar PIM profile as the Andersen-Tawil mutated protein group. The bioinformatics "fingerprint" of the Andersen-Tawil mutated proteins was retrieved using the in-house bioinformatics system named Polarity Index Method® and supported-at residues level- by the algorithms for the prediction of intrinsic disorder predisposition, such as PONDR® FIT, PONDR® VLXT, PONDR® VSL2, PONDR® VL3, FoldIndex, IUPred, and TopIDP.