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Alignment-free prediction of mycobacterial DNA promoters based on pseudo-folding lattice network or star-graph topological indices
Authors:Perez-Bello Alcides  Munteanu Cristian Robert  Ubeira Florencio M  De Magalhães Alexandre Lopes  Uriarte Eugenio  González-Díaz Humberto
Affiliation:a Department of Microbiology and Parasitology, University of Santiago de Compostela, Santiago de Compostela 15782, Spain
b Department of Veterinary Medicine, UCLV, Santa Clara 54830, Cuba
c Department of Organic Chemistry, Faculty of Pharmacy, University of Santiago de Compostela, Santiago de Compostela 15782, Spain
d REQUIMTE/University of Porto, Faculty of Science, Chemistry Department, Porto 4169-007, Portugal
Abstract:The importance of the promoter sequences in the function regulation of several important mycobacterial pathogens creates the necessity to design simple and fast theoretical models that can predict them. This work proposes two DNA promoter QSAR models based on pseudo-folding lattice network (LN) and star-graphs (SG) topological indices. In addition, a comparative study with the previous RNA electrostatic parameters of thermodynamically-driven secondary structure folding representations has been carried out. The best model of this work was obtained with only two LN stochastic electrostatic potentials and it is characterized by accuracy, selectivity and specificity of 90.87%, 82.96% and 92.95%, respectively. In addition, we pointed out the SG result dependence on the DNA sequence codification and we proposed a QSAR model based on codons and only three SG spectral moments.
Keywords:QSAR   Markov model   Mycobacterial promoters   Star-graph   Lattice network   Topological indices
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