Abstract

Background: The infection caused by the dengue fever virus is a severe threat to public health on a global scale; nevertheless, there is currently no effective medical treatment or vaccine available to prevent or treat the condition.

Objective: To better understand the physicochemical regularities of these proteins, it is necessary to carry out a computational multiparametric study of the amino acid sequences of envelope proteins expressed by the dengue fever virus and obtain a bioinformatics method that can use the subsequences of the training protein group to figure out the preponderant function of a protein, up to its sequence.

Methods: Essentially, at the amino acid level, various computational programs were applied to the sequences expressing the dengue virus envelope glycoproteins to determine the PIM 2.0 v profile and the Protein Intrinsic Disorder Predisposition (PIDP) profile of each protein, and then, at the nucleotide level, a set of programs for genomic analysis was applied. Finally, these results were contrasted with statistical tests.

Results: The re-creation of structural morphological similarities provided by specific regularities in the PIM 2.0 v profile and PIDP of the proteins from diverse dengue fever virus envelopes made it possible to propose a computer method that employs the PIM 2.0 v profile to identify this group of proteins based on their sequences; based on our findings, this method is a "fingerprint" of this protein group.

Conclusion: The typical PIM 2.0 v profiles of the dengue fever virus proteins might be reproduced by computational tools. This knowledge will be helpful in gaining a better understanding of the newly discovered virus. Moreover, the method introduced here can identify, from the sequence, the predominant function of the protein.

Keywords: Dengue, DENV gene, DENV mutant protein, dengue envelop glycoprotein, structural proteomics, bioinformatics, intrinsic disorder predisposition, polarity index method, polarity index method 2.0 v profile.