Bioinformatics Insights on the Physicochemical Properties of SCN5A Mutant Proteins Associated with the Brugada Syndrome.

BACKGROUND: The Brugada syndrome (BrS) is a heart rhythm condition that is commonly associated with a strong predisposition for sudden cardiac death. Malignant ventricular arrhythmias could occur secondary to the dysfunction of the cardiac sodium voltage-gated Na(v)1.5 channel (SCN5A). OBJECTIVE: This study aimed to perform a multiparametric computational analysis of the physicochemical properties of SCN5A mutants associated with BrS using a set of bioinformatics tools. METHODS: In-house algorithms were calibrated to calculate, in a double-blind test, the Polarity Index Method (PIM) profile and protein intrinsic disorder predisposition (PIDP) profile of each sequence, and computer programs specialized in the genomic analysis were used. RESULTS: Specific regularities in the charge/polarity and PIDP profile of the SCN5A mutant proteins enabled the re-creation of the taxonomy, allowing us to propose a bioinformatics method that takes advantage of the PIM profile to identify this group of proteins from their sequence. CONCLUSION: Bioinformatics programs could reproduce characteristic PIM and PIDP profiles of the BrS-related SCN5A mutant proteins. This information can contribute to a better understanding of these altered proteins.

Bioinformatics-based Characterization of the Sequence Variability of Zika Virus Polyprotein and Envelope Protein (E).

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.

Non-racemic mixture model: a computational approach.

The behavior of a slight chiral bias in favor of l-amino acids over d-amino acids was studied in an evolutionary mathematical model generating mixed chiral peptide hexamers. The simulations aimed to reproduce a very generalized prebiotic scenario involving a specified couple of amino acid enantiomers and a possible asymmetric amplification through autocatalytic peptide self-replication while forming small multimers of a defined length. Our simplified model allowed the observation of a small ascending but not conclusive tendency in the l-amino acid over the d-amino acid profile for the resulting mixed chiral hexamers in computer simulations of 100 peptide generations. This simulation was carried out by changing the chiral bias from 1% to 3%, in three stages of 15, 50 and 100 generations to observe any alteration that could mean a drastic change in behavior. So far, our simulations lead to the assumption that under the exposure of very slight non-racemic conditions, a significant bias between l- and d-amino acids, as present in our biosphere, was unlikely generated under prebiotic conditions if autocatalytic peptide self-replication was the main or the only driving force of chiral auto-amplification.

Irregular Liesegang-type patterns in gas phase revisited. I. Experimental setup, data processing, and test of the spacing law.

Since the early work on Liesegang rings in gels, they have been a reference point for the study of pattern formation in chemical physics. Here we present a variant of the Liesegang experiment in gas phase, where ammonia and hydrochloric acid react within a glass tube producing a precipitate, which deposits along the tube wall producing a spatial pattern. With this apparently simple experiment a wide range of rich phenomenon can be observed due to the presence of convective flows and irregular dynamics reminiscent of turbulent behavior, for which precise measurements are scarce. In this first part of our work, we describe in detail the experimental setup, the method of data acquisition, the image processing, and the procedure used to obtain an intensity profile, which is representative of the amount of precipitate deposited at the tube walls. Special attention is devoted to the techniques rendering a data series reliable for statistical studies and model building, which may contribute to a characterization and understanding of the pattern formation phenomenon under consideration. As a first step in this direction, based on our data, we are able to show that the observed band pattern follows, with slight deviations, the spacing law encountered in common Liesegang rings, despite that the experimental conditions are very different. A further statistical correlation analysis of the data constitutes Paper II of this research.

Identification of proteins associated with amyloidosis by polarity index method.

There is a natural protein form, insoluble and resistant to proteolysis, adopted by many proteins independently of their amino acid sequences via specific misfolding-aggregation process. This dynamic process occurs in parallel with or as an alternative to physiologic folding, generating toxic protein aggregates that are deposited and accumulated in various organs and tissues. These proteinaceous deposits typically represent bundles of ß-sheet-enriched fibrillar species known as the amyloid fibrils that are responsible for serious pathological conditions, including but not limited to neurodegenerative diseases, grouped under the term amyloidoses. The proteins that might adopt this fibrillar conformation are some globular proteins and natively unfolded (or intrinsically disordered) proteins. Our work shows that intrinsically disordered and intrinsically ordered proteins can be reliably identified, discriminated, and differentiated by analyzing their polarity profiles generated using a computational tool known as the polarity index method (Polanco & Samaniego, 2009; Polanco et al., 2012; 2013; 2013a; 2014; 2014a; 2014b; 2014c; 2014d). We also show that proteins expressed in neurons can be differentiated from proteins in these two groups based on their polarity profiles, and also that this computational tool can be used to identify proteins associated with amyloidoses. The efficiency of the proposed method is high (i.e. 70%) as evidenced by the analysis of peptides and proteins in the APD2 database (2012), AVPpred database (2013), and CPPsite database (2013), the set of selective antibacterial peptides from del Rio et al. (2001), the sets of natively unfolded and natively folded proteins from Oldfield et al. (2005), the set of human revised proteins expressed in neurons, and non-human revised proteins expressed in neurons, from the Uniprot database (2014), and also the set of amyloidogenic proteins from the AmyPDB database (2014).

Polar profile of antiviral peptides from AVPpred Database.

Diseases of viral origin in humans are among the most serious threats to health and the global economy. As recent history has shown the virus has a high pandemic potential, among other reasons, due to its ability to spread by air, hence the identification, investigation, containment, and treatment of viral diseases should be considered of paramount importance. In this sense, the bioinformatics research has focused on finding fast and efficient algorithms that can identify highly toxic antiviral peptides and to serve as a first filter, so that trials in the laboratory are substantially reduced. The work presented here contributes to this effort through the use of an algorithm already published by this team, called polarity index method, which identifies with high efficiency antiviral peptides from the exhaustive analysis of the polar profile, using the linear sequence of the peptide. The test carried out included all peptides in APD2 Database and 60 antiviral peptides identified by Kumar and co-workers (Nucleic Acids Res 40:W199-204, 2012), to build its AVPpred algorithm. The validity of the method was focused on its discriminating capacity so we included the 15 sub-classifications of both Databases.

Polar characterization of antifungal peptides from APD2 Database.

The increase in the number of pathogens due to fungi that are tolerant to therapies does not grow at the same speed than the advance on new antifungal drugs. In this sense, it is imperative to find anti-fungi peptides that are not detrimental to mammalian cells and have an effective toxicity to fungi. In this work, we use a method called polarity index, to identify anti-fungi peptides with an efficiency of 70 %. This method already published, initially identified selective antibacterial peptides from APD2 Database, and was characterized by developing a comprehensive analysis of the polar dynamics of a peptide from its linear sequence. Discriminating tests showed that in addition to being efficient in this identification, it was also good at rejecting other classifications of peptides found in that same database.

A toy model of prebiotic peptide evolution: the possible role of relative amino acid abundances.

This paper presents a mathematical-computational toy model based on the assumed dynamic principles of prebiotic peptide evolution. Starting from a pool of amino acid monomers, the model describes in a generalized manner the generation of peptides and their sequential information. The model integrates the intrinsic and dynamic key elements of the initiation of biopolymerization, such as the relative amino acid abundances and polarities, as well as the oligomer reversibility, i.e. fragmentation and recombination, and peptide self-replication. Our modeling results suggest that the relative amino acid abundances, as indicated by Miller-Urey type electric discharge experiments, played a principal role in the early sequential information of peptide profiles. Moreover, the computed profiles display an astonishing similarity to peptide profiles observed in so-called biological common ancestors found in the following three microorganisms; E. coli, M. jannaschii, and S. cereviasiae. The prebiotic peptide fingerprint was obtained by the so-called polarity index method that was earlier reported as a tool for the identification of cationic amphipathic antibacterial short peptides.

Detection of selective antibacterial peptides by the Polarity Profile method.

Antimicrobial peptides occupy a prominent place in the production of pharmaceuticals, because of their effective contribution to the protection of the immune system against almost all types of pathogens. These peptides are thoroughly studied by computational methods designed to shed light on their main functions. In this paper, we propose a computational approach, named the Polarity Profile method that represents an improvement to the former Polarity Index method. The Polarity Profile method is very effective in detecting the subgroup of antibacterial peptides called selective cationic amphipathic antibacterial peptides (SCAAP) that show high toxicity towards bacterial membranes and exhibit almost zero toxicity towards mammalian cells. Our study was restricted to the peptides listed in the antimicrobial peptides database (APD2) of December 19, 2012. Performance of the Polarity Profile method is demonstrated through a comparison to the former Polarity Index method by using the same sets of peptides. The efficiency of the Polarity Profile method exceeds 85% taking into account the false positive and/or false negative peptides.

Kinetic analysis of self-replicating peptides: possibility of chiral amplification in open systems.

A simplified kinetic model scheme is presented that addresses the main reactions of two recently reported peptide self-replicators. Experimentally observed differences in the autocatalytic efficiency between these two systems-- caused by variations in the peptide sequences--and the possible effect of chiral amplification under heterochiral reaction conditions were evaluated. Our numerical simulations indicated that differences in the catalytic performance are exclusively due to pronounced variations in the rate parameters that control the reversible and hydrophobic interactions in the reaction system but neither to alterations in the underlying reaction network nor to changes in the stoichiometry of the involved aggregation processes. Model predictions further demonstrated the possible existence of chiral amplification if peptide self-replication is performed under heterochiral reaction conditions. Pointing into the direction of a possible cause for biomolecular homochirality, it was found that in open flow reactors, keeping the system under non-equilibrium conditions, a remarkable amplification of enantiomeric excess could be achieved. According to our modeling, this is due to a chiroselective autocatalytic effect and a meso-type separation process both of which are assumed to be intrinsic for the underlying dynamics of heterochiral peptide self-replication.

Kinetic analysis of artificial peptide self-replication. Part I: the homochiral case.

Computational kinetic analysis of a lately discovered homochiral peptide self-replicator is presented. A 6-step kinetic model was designed that addresses the main reactions and hydrophobic interactions involved in this template-directed, autocatalytic system and that gave rise to excellent fitting of 4 previously published independent experimental series. The model sheds light on the mechanistic principle of the reaction system and illustrates directly a number of dynamic properties such as the observed autocatalytic efficiency. It was found that the dynamics are basically governed by two reversible hydrophobic interactions: between the template and a peptide fragment and between two template species. The later association was determined to be considerably more favored, which leads to the predominant presence of the catalytically inactive template dimer in the reaction system. Our results show that the involvement of a template trimer is not necessary to obtain the observed fittings.

Kinetic analysis of artificial peptide self-replication. Part II: the heterochiral case.

A kinetic model has been designed to describe and to analyze the stereoselective behavior of a recently discovered heterochiral template-directed peptide self-replicator by Ghadiri and co-workers [Nature 409 (2001) 797-801]. It turned out that previous assumptions stating that exclusively homochiral species participate in a stereoselective and autocatalytic pathway and that heterochiral species originate only from uncatalyzed background reactions could not be validated by our model. On the contrary, excellent fitting of experimental data indicated that the whole combinatorial variety of possible cross-catalytic processes involving L- and D- peptide species play an important role and need to be taken into account. The system shows no net creation of chiral matter but only a redistribution of the initially present chiral material. Both, the separation of an optically inactive meso-type template dimer and a slight chiroselective autocatalytic effect, contribute to a predicted amplification of enantiomeric excess that, in some cases, can simultaneously result in a substantial amount of optically active matter.