Bioinformatics Analysis of Dysfunctional (Mutated) Proteins of Cardiac Ion Channels Underlying the Brugada Syndrome

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The Brugada syndrome (BrS) is a disease with a great predisposition to sudden cardiac death due to ventricular arrhythmias. Dysfunctional ion channels are considered responsible for this entity. To date, there are 4,388 overrepresented BrS mutated proteins underlying this disease, which is reported in the UniProt database. In an effort to characterize proteins, a nonsupervised computational system called the Polarity Index Method® (PIM) has been developed by our group to extensively measure the “polar profile” or “electromagnetic balance” of proteins. PIM® takes the linear representation of the protein amino acid sequence as input and not its three-dimensional structure. This computational approximation provides means for the extensive analysis of large datasets, without detriment to its performance. In this work, this method was calibrated with the BrS mutated proteins, searching for an association of these entities with (i) the group of 36 BrS proteins, of which are known where 4,388 BrS mutated proteins come from, (ii) two groups of intrinsically disordered proteins, (iii) six lipoprotein groups, (iv) three main groups of antimicrobial proteins from UniProt and APD2 databases, (v) a set of selective cationic amphipathic antibacterial peptides (SCAAP), and (vi) the group of 557,713 “reviewed” proteins from the UniProt database. To appreciate the peculiarities of their linear sequences, the BrS mutated proteins identified by the PIM system were further examined by the algorithms for the prediction of intrinsic disorder predisposition, such as PONDR® FIT, PONDR® VLXT, PONDR® VSL2, PONDR® VL3, FoldIndex, IUPred, and TopIDP. Our results led to the assumption that it is possible to computationally identify and differentiate the BrS mutated proteins with 85% accuracy without ambiguity. In contrast, there were no features in the intrinsic disorder profiles of query proteins that can discriminate BrS-related mutations from any other mutations in these proteins.

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Bioinformatics Analysis of Dysfunctional (Mutated) Proteins of Cardiac Ion Channels Underlying the Brugada Syndrome, in Q. A. Memon & S. A. Khoja (Eds.), Data Science, CRC Press