TI2BioP: Topological Indices to BioPolymers. Its practical use to unravel cryptic bacteriocin-like domains

• Type: Article in International Scientific Journal
• Date: 2011

Authors

Guillermin Agueero Chapin (Author) Other; Gisselle Perez Machado (Author) Other; Reinaldo Molina Ruiz (Author) Other; Yunierkis Perez Castillo (Author) Other; Aliuska Morales Helguera (Author) Other; Vitor Vasconcelos (Author) FCUP; Agostinho Antunes (Author) FCUP

Journal

Title: Amino Acids

Vol. 40

Pages: 431-442

ISSN: 0939-4451

Publisher: Springer Nature

Indexing

ISI Web of Knowledge - 12 Citations

Scopus - 12 Citations

Scientific classification

FOS: Natural sciences > Biological sciences

Other information

Authenticus ID: P-002-VG9

DOI: 10.1007/s00726-010-0653-9

Abstract (EN): Bacteriocins are proteinaceous toxins produced and exported by both gram-negative and gram-positive bacteria as a defense mechanism. The bacteriocin protein family is highly diverse, which complicates the identification of bacteriocin-like sequences using alignment approaches. The use of topological indices (TIs) irrespective of sequence similarity can be a promising alternative to predict proteinaceous bacteriocins. Thus, we present Topological Indices to BioPolymers (TI2BioP) as an alignment-free approach inspired in both the Topological Substructural Molecular Design (TOPS-MODE) and Markov Chain Invariants for Network Selection and Design (MARCH-INSIDE) methodology. TI2BioP allows the calculation of the spectral moments as simple TIs to seek quantitative sequence-function relationships (QSFR) models. Since hydrophobicity and basicity are major criteria for the bactericide activity of bacteriocins, the spectral moments ((HP)mu (k) ) were derived for the first time from protein artificial secondary structures based on amino acid clustering into a Cartesian system of hydrophobicity and polarity. Several orders of (HP)mu (k) characterized numerically 196 bacteriocin-like sequences and a control group made up of 200 representative CATH domains. Subsequently, they were used to develop an alignment-free QSFR model allowing a 76.92% discrimination of bacteriocin proteins from other domains, a relevant result considering the high sequence diversity among the members of both groups. The model showed a prediction overall performance of 72.16%, detecting specifically 66.7% of proteinaceous bacteriocins whereas the InterProScan retrieved just 60.2%. As a practical validation, the model also predicted successfully the cryptic bactericide function of the Cry 1Ab C-terminal domain from Bacillus thuringiensis's endotoxin, which has not been detected by classical alignment methods.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12