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TI2BioP: Topological Indices to BioPolymers. Its practical use to unravel cryptic bacteriocin-like domains
Authors:Guillermín Agüero-Chapin  Gisselle Pérez-Machado  Reinaldo Molina-Ruiz  Yunierkis Pérez-Castillo  Aliuska Morales-Helguera  Vítor Vasconcelos  Agostinho Antunes
Institution:1.CIMAR/CIIMAR, Centro Interdisciplinar de Investiga??o Marinha e Ambiental,Universidade do Porto,Porto,Portugal;2.Molecular Simulation and Drug Design (CBQ),Central University of Las Villas,Santa Clara,Cuba;3.Department of Organic Chemistry,Vigo University,Vigo,Spain;4.Department of Chemistry,Central University of Las Villas,Santa Clara,Cuba;5.REQUIMTE, Department of Chemistry,University of Porto,Porto,Portugal;6.Departamento de Biologia, Faculdade de Ciências,Universidade do Porto,Porto,Portugal
Abstract: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 (HPμ 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 HPμ 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.
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