Alignment-free prediction of mycobacterial DNA promoters based on pseudo-folding lattice network or star-graph topological indices

• Published in: Journal of theoretical biology Vol. 256; no. 3; pp. 458 - 466
• Main Authors: Perez-Bello, Alcides, Munteanu, Cristian Robert, Ubeira, Florencio M., Lopes De Magalhães, Alexandre, Uriarte, Eugenio, González-Díaz, Humberto
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 07.02.2009; Elsevier
• Subjects: Codon; DNA, Bacterial - genetics; Lattice network; Markov Chains; Markov model; Models, Biological; Mycobacterial promoters; Mycobacterium; Mycobacterium - genetics; Promoter Regions, Genetic - genetics; Protein Structure, Secondary; QSAR; Quantitative Structure-Activity Relationship; Star-graph; Topological indices; Lattice network; Markov model; QSAR; Mycobacterial promoters; Star-graph; Topological indices; Life Sciences
• ISSN: 0022-5193; 1095-8541
• DOI: 10.1016/j.jtbi.2008.09.035

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.