scholarly journals Possible computational filter to detect proteins associated to influenza A subtype H1N1.

2014 ◽  
Vol 61 (4) ◽  
Author(s):  
Carlos Polanco ◽  
Thomas Buhse ◽  
Jorge Alberto Castañón-González ◽  
José Lino Samaniego
Keyword(s):  
Influenza A ◽  
Quantitative Structure Activity Relationship ◽  
Peptide Sequence ◽  
Index Method ◽  
Linear Peptide ◽  
Polarity Index ◽  
Uniprot Database ◽  
Del Rio ◽  
Virus Subtype ◽  
Proteins And Peptides

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.

Bioinformatics-based identification of proteins expressed by arthropod-borne viruses transmitted by Aedes aegypti mosquito

2020 ◽  
Vol 17 ◽  
Author(s):  
Carlos Polanco ◽  
Vladimir N. Uversky ◽  
Alberto Huberman ◽  
Leire Andrés ◽  
Thomas Buhse ◽  
...  
Keyword(s):  
Aedes Aegypti ◽  
Intrinsically Disordered Proteins ◽  
Intrinsic Disorder ◽  
Cell Penetrating Peptides ◽  
Disordered Proteins ◽  
Index Method ◽  
Intrinsically Disordered ◽  
Polarity Index ◽  
Uniprot Database ◽  
Prophylactic Measures

Background: The female Aedes aegypti mosquito is a vector of several arthropodborne viruses, such as Mayaro, Dengue, Chikungunya, Yellow Fever, and Zika. These viruses cause the death of at least 600000 people a year and temporarily disable several millions more around the world. Up to date, there are no effective prophylactic measures that would prevent the contact and bite of this arthropod and, therefore, its consequential contagion. Objective: The objective of the present study was to search for the regularities of the proteins expressed by these five viruses, at residues level, and obtain a "bioinformatic fingerprint" to select them. Methods: We used two bioinformatic systems, our in-house bioinformatic system named Polarity Index Method® (PIM®) supported at residues level, and the commonly used algorithm for the prediction of intrinsic disorder predisposition, PONDR® FIT. We applied both programs to the 29 proteins that express the five groups of arboviruses studied, and we calculated for each of them their Polarity Index Method® profile and their intrinsic disorder predisposition. This information was then compared with analogous information for other protein groups, such as proteins from bacteria, fungi, viruses, and cell penetrating peptides from the UniProt database, and a set of intrinsically disordered proteins. Once the "fingerprint" of each group of arboviruses was obtained, these "fingerprints" were searched among the 559228 "reviewed" proteins from the UniProt database. Results: In total, 1736 proteins were identified from the 559228 “reviewed” proteins from UniProt database, with similar "PIM® profile" to the 29 mutated proteins that express the five groups of arboviruses. Conclusion: We propose that the “PIM® profile” of characterization of proteins might be useful for the identification of proteins expressed by arthropod-borne viruses transmitted by Aedes aegypti mosquito.

Bioinformatics-based identification of Selective Cationic Amphipatic Antibacterial Peptides: Aurein 1.2 variants case

2020 ◽  
Vol 17 ◽  
Author(s):  
Carlos Polanco ◽  
Alberto Huberman ◽  
Vladimir N. Uversky ◽  
Leire Andrés ◽  
Thomas Buhse ◽  
...  
Keyword(s):  
Mammalian Cells ◽  
Intrinsically Disordered Proteins ◽  
Intrinsic Disorder ◽  
Cell Penetrating Peptides ◽  
Disordered Proteins ◽  
Antibacterial Peptides ◽  
Index Method ◽  
Intrinsically Disordered ◽  
Polarity Index ◽  
Uniprot Database

Background: Selective Cationic Amphipathic Antibacterial Peptides (SCAAPs) occupy a prominent place in the production of new drugs on account of their high toxicity towards bacteria and low toxicity towards mammalian cells, low hemolytic activity, and contribution to the protection of the human immune system. Introduction: Their number in nature is very low and experimental tests are very protracted and costly. Therefore, it would be useful to have bioinformatics tools that would identify them in the existing databases and also propose new synthetic SCAAPs. Method: In order to reduce the costs of identification and/or chemical synthesis. To know the physicochemical characteristics of SCAAPs at a residues level and to obtain a “bioiformatics fingerprint” suitable for their selection, we have modified the Polarity Index Method® (PIM®) to include the α-helical configuration of each sequence to determine their individual “PIM® profile”. We have also used a set of computer program to determine their “Intrinsic Disorder Predisposition”. This information was then compared with other protein groups such as bacteria, fungi, virus and cell penetrating peptides (CPP) from the UniProt database and a set of intrinsically disordered proteins. Once the “fingerprint” of SCAAPs was obtained, it was used for searching among the 559228 “reviewed” proteins from the UniProt database and a set of synthetic SCAAPs characterized by the predefined “PIM® profile” selected. Results: Our results showed that the metric named “PIM® profile” can identify, with a high level of accuracy, a group of bacterial SCAAPs. This bioinformatics study was supported at residues level, using the in-house bioinformatics system Polarity Index Method the commonly used algorithm for the prediction of intrinsic disorder predisposition, PONDR® FIT. Conclusions: The Polarity Index Method seems highly efficient identifying SCAAP candidates.

The comparative biochemistry of viruses and humans: an evolutionary path towards autoimmunity

2019 ◽  
Vol 400 (5) ◽  
pp. 629-638 ◽  
Author(s):  
Darja Kanduc
Keyword(s):  
Measles Virus ◽  
Influenza A ◽  
Viral Infections ◽  
Sequence Similarity ◽  
Eukaryotic Cell ◽  
Point Of View ◽  
Peptide Sequence ◽  
Human Viruses ◽  
Archaeal Ancestor ◽  
Borna Disease

Abstract Analyses of the peptide sharing between five common human viruses (Borna disease virus, influenza A virus, measles virus, mumps virus and rubella virus) and the human proteome highlight a massive viral vs. human peptide overlap that is mathematically unexpected. Evolutionarily, the data underscore a strict relationship between viruses and the origin of eukaryotic cells. Indeed, according to the viral eukaryogenesis hypothesis and in light of the endosymbiotic theory, the first eukaryotic cell (our lineage) originated as a consortium consisting of an archaeal ancestor of the eukaryotic cytoplasm, a bacterial ancestor of the mitochondria and a viral ancestor of the nucleus. From a pathologic point of view, the peptide sequence similarity between viruses and humans may provide a molecular platform for autoimmune crossreactions during immune responses following viral infections/immunizations.

New avian influenza A virus subtype combination H5N7 identified in Danish mallard ducks

2005 ◽  
Vol 109 (2) ◽  
pp. 181-190 ◽  
Author(s):  
K. Bragstad ◽  
P.H. Jørgensen ◽  
K.J. Handberg ◽  
S. Mellergaard ◽  
S. Corbet ◽  
...  
Keyword(s):  
Avian Influenza ◽  
Influenza A Virus ◽  
Influenza A ◽  
Avian Influenza A Virus ◽  
Virus Subtype

Identification of proteins associated with amyloidosis by polarity index method

2015 ◽  
Vol 62 (1) ◽  
pp. 41-55 ◽  
Author(s):  
Carlos Polanco ◽  
José Lino Samaniego ◽  
Vladimir N. Uversky ◽  
Jorge Alberto Castañón-González ◽  
Thomas Buhse ◽  
...  
Keyword(s):  
Index Method ◽  
Polarity Index

scholarly journals Virus subtype-specific suppression of MAVS aggregation and activation by PB1-F2 protein of influenza A (H7N9) virus

2020 ◽  
Vol 16 (6) ◽  
pp. e1008611 ◽  
Author(s):  
Pak-Hin Hinson Cheung ◽  
Tak-Wang Terence Lee ◽  
Chun Kew ◽  
Honglin Chen ◽  
Kwok-Yung Yuen ◽  
...  
Keyword(s):  
Influenza A ◽  
H7n9 Virus ◽  
Specific Suppression ◽  
Virus Subtype

Drug design for Influenza A virus subtype H1N1

2010 ◽  
Vol 41 (1) ◽  
pp. 8-15 ◽  
Author(s):  
Chien-Yu Chen ◽  
Hung-Jin Huang ◽  
Fuu-Jen Tsai ◽  
Calvin Yu-Chian Chen
Keyword(s):  
Drug Design ◽  
Influenza A Virus ◽  
Influenza A ◽  
Virus Subtype
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