Search results

1

Non-racemic mixture model: a computational approach

100%

Polanco C., Buhse T.

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2017

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vol. 64

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issue 1

17-19

EN

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.

2

Detection of selective antibacterial peptides by the Polarity Profile method

81%

Polanco C., Buhse T., Samaniego J. L., Castañón-González J. A.

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2013

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vol. 60

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issue 2

183-189

EN

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.

3

The polar profile of ancient proteins: a computational extrapolation from prebiotics to paleobiochemistry

81%

Polanco C., Buhse T., Vizcaíno G., Picciotto J.

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2017

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vol. 64

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issue 1

117-122

EN

This paper addresses the polar profile of ancient proteins using a comparative study of amino acids found in 25 000 000-year-old shells described in Abelson's work. We simulated the polar profile with a computer platform that represented an evolutionary computational toy model that mimicked the generation of small proteins starting from a pool of monomeric amino acids and that included several dynamic properties, such as self-replication and fragmentation-recombination of the proteins. The simulations were taken up to 15 generations and produced a considerable number of proteins of 25 amino acids in length. The computational model included the amino acids found in the ancient shells, the thermal degradation factor, and the relative abundance of the amino acids observed in the Miller-Urey experimental simulation of the prebiotic amino acid formation. We found that the amino acid polar profiles of the ancient shells and those simulated and extrapolated from the Miller-Urey abundances are coincident.

4

Structure and function relationships of proteins based on polar profile: a review

81%

Polanco C., Buhse T., Uversky V.

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2016

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vol. 63

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issue 2

229-233

EN

Proteins in the post-genome era impose diverse research challenges, the main are the understanding of their structure-function mechanism, and the growing need for new pharmaceutical drugs, particularly antibiotics that help clinicians treat the ever- increasing number of Multidrug-Resistant Organisms (MDROs). Although, there is a wide range of mathematical-computational algorithms to satisfy the demand, among them the Quantitative Structure-Activity Relationship algorithms that have shown better performance using a characteristic training data of the property searched; their performance has stagnated regardless of the number of metrics they evaluate and their complexity. This article reviews the characteristics of these metrics, and the need to reconsider the mathematical structure that expresses them, directing their design to a more comprehensive algebraic structure. It also shows how the main function of a protein can be determined by measuring the polarity of its linear sequence, with a high level of accuracy, and how such exhaustive metric stands as a "fingerprint" that can be applied to scan the protein regions to obtain new pharmaceutical drugs, and thus to establish how the singularities led to the specialization of the protein groups known today.

5

Possible computational filter to detect proteins associated to influenza A subtype H1N1

81%

Polanco C., Buhse T., Castañón-González J., Samaniego J.

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2014

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vol. 61

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issue 4

693-698

EN

The design of drugs with bioinformatics methods to identify proteins and peptides with a specific toxic action is increasingly recurrent. Here, we identify toxic proteins towards the influenza A virus subtype H1N1 located at the UniProt database. Our quantitative structure-activity relationship (QSAR) approach is based on the analysis of the linear peptide sequence with the so-called Polarity Index Method that shows an efficiency of 90% for proteins from the Uniprot Database. This method was exhaustively verified with the APD2, CPPsite, Uniprot, and AmyPDB databases as well as with the set of antibacterial peptides studied by del Rio et al. and Oldfield et al.

6

Discrete dynamic system oriented on the formation of prebiotic dipeptides from Rode's experiment

81%

Polanco C., Samaniego J., Buhse T., Castañón González J.

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2014

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vol. 61

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issue 4

717-726

EN

This work attempts to rationalize the possible prebiotic profile of the first dipeptides of about 4 billion years ago based on a computational discrete dynamic system that uses the final yields of the dipeptides obtained in Rode's experiments of salt-induced peptide formation (Rode et al., 1999, Peptides 20: 773-786). The system built a prebiotic scenario that allowed us to observe that (i) the primordial peptide generation was strongly affected by the abundances of the amino acid monomers, (ii) small variations in the concentration of the monomers have almost no effect on the final distribution pattern of the dipeptides and (iii) the most plausible chemical reaction of prebiotic peptide bond formation can be linked to Rode's hypothesis of a salt-induced scenario. The results of our computational simulations were related to former simulations of the Miller, and Fox & Harada experiments on amino acid monomer and oligomer generation, respectively, offering additional information to our approach.

7

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

81%

Polanco C., Buhse T., Samaniego J. L., González J. A. C.

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2013

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vol. 60

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issue 2

175-182

EN

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.

8

Computational model of abiogenic amino acid condensation to obtain a polar amino acid profile

71%

Polanco C., Buhse T., Samaniego J., Castañón González J., Estrada M.

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2014

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vol. 61

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issue 2

253-258

EN

In accordance with the second law of thermodynamics, the Universe as a whole tends to higher entropy. However, the sequence of far-from-equilibrium events that led to the emergence of life on Earth could have imposed order and complexity during the course of chemical reactions in the so-called primordial soup of life. Hence, we may expect to find characteristic profiles or biases in the prebiotic product mixtures, as for instance among the first amino acids. Seeking to shed light on this hypothesis, we have designed a high performance computer program that simulates the spontaneous formation of the amino acid monomers in closed environments. The program was designed in reference to a prebiotic scenario proposed by Sydney W. Fox. The amino acid abundances and their polarities as the two principal biases were also taken into consideration. We regarded the computational model as exhaustive since 200 000 amino acid dimers were formed by simulation, subsequently expressed in a vector and compared with the corresponding amino acid dimers that were experimentally obtained by Fox. We found a very high similarity between the experimental results and our simulations.

9

Characterization of a possible uptake mechanism of selective antibacterial peptides

71%

Polanco C., Samaniego J., Castañón-González J., Buhse T., Sordo M.

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2013

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vol. 60

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issue 4

629-633

EN

Selective antibacterial peptides containing less than 30 amino acid residues, cationic, with amphipathic properties, have been the subject of several studies due to their active participation and beneficial effects in strengthening the immune system of all living organisms. This manuscript reports the results of a comparison between the group of selective antibacterial peptides and another group called "cell penetrating peptides". An important number of the selective antibacterial peptides are cell penetrating peptides, suggesting that their toxicity is related to their uptake mechanism. The verification of this observation also includes the adaptation of a method previously published, called Polarity index, which reproduces and confirms the action of this new set of peptides. The efficiency of this method was verified based on four different databases, yielding a high score. The verification was based exclusively on the peptides already reported in the databases which have been experimentally verified.

10

Classifying lipoproteins based on their polar profiles

71%

Polanco C., Castañón-González J., Buhse T., Uversky V., Amkie R.

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2016

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vol. 63

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issue 2

235-241

EN

The lipoproteins are an important group of cargo proteins known for their unique capability to transport lipids. By applying the Polarity index algorithm, which has a metric that only considers the polar profile of the linear sequences of the lipoprotein group, we obtained an analytical and structural differentiation of all the lipoproteins found in UniProt Database. Also, the functional groups of lipoproteins, and particularly of the set of lipoproteins relevant to atherosclerosis, were analyzed with the same method to reveal their structural preference, and the results of Polarity index analysis were verified by an alternate test, the Cumulative Distribution Function algorithm, applied to the same groups of lipoproteins.

11

Identification of proteins associated with Mycobacterium tuberculosis virulence pathway by their polar profile

62%

Polanco C., Castañón-González J., Mancilla R., Buhse T., Samaniego J., Gimbel A.

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2015

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vol. 62

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issue 2

191-196

EN

With almost one third of the world population infected, tuberculosis is one of the most devastating diseases worldwide and it is a major threat to any healthcare system. With the mathematical-computational method named "Polarity Index Method", already published by this group, we identified, with high accuracy (70%), proteins related to Mycobacterium tuberculosis bacteria virulence pathway from the Tuberculist Database. The test considered the totality of proteins cataloged in the main domains: fungi, bacteria, and viruses from three databases: Antimicrobial Peptide Database (APD2), Tuberculist Database, Uniprot Database, and four antigens of Mycobacterium tuberculosis: PstS-1, 38-kDa, 19-kDa, and H37Rv ORF. The method described was calibrated with each database to achieve the same performance, showing a high percentage of coincidence in the identification of proteins associated with Mycobacterium tuberculosis bacteria virulence pathway located in the Tuberculist Database, and identifying a polar pattern regardless of the group studied. This method has already been used in the identification of diverse groups of proteins and peptides, showing that it is an effective discriminant. Its metric considers only one physico-chemical property, i.e. polarity.

12

Electronegativity and intrinsic disorder of preeclampsia-related proteins

62%

Polanco C., Castañón-González J., Uversky V., Buhse T., Samaniego Mendoza J., Calva J.

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2017

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vol. 64

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issue 1

99-111

EN

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.

13

Identification of proteins associated with amyloidosis by polarity index method

42%

Polanco C., Samaniego J., Uversky V., Castañón-González J., Buhse T., Leopold-Sordo M., Madero-Arteaga A., Morales-Reyes A., Tavera-Sierra L., González-Bernal J., Arias-Estrada M.

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2015

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vol. 62

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issue 1

41-55

EN

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 β-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).

Refine search results

Non-racemic mixture model: a computational approach

Detection of selective antibacterial peptides by the Polarity Profile method

The polar profile of ancient proteins: a computational extrapolation from prebiotics to paleobiochemistry

Structure and function relationships of proteins based on polar profile: a review

Possible computational filter to detect proteins associated to influenza A subtype H1N1

Discrete dynamic system oriented on the formation of prebiotic dipeptides from Rode's experiment

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

Computational model of abiogenic amino acid condensation to obtain a polar amino acid profile

Characterization of a possible uptake mechanism of selective antibacterial peptides

Classifying lipoproteins based on their polar profiles

Identification of proteins associated with Mycobacterium tuberculosis virulence pathway by their polar profile

Electronegativity and intrinsic disorder of preeclampsia-related proteins

Identification of proteins associated with amyloidosis by polarity index method