Computational approach towards promoter sequence comparison via TF mapping using a new distance measure

We propose a method for identifying transcription factor binding sites (TFBS) in the given promoter sequence and mapping the transcription factors (TFs). The proposed algorithm searches the +1 transcription start site (TSS) for eukaryotic and prokaryotic sequences individually. The algorithm was tested with sequences from both eukaryotes and prokaryotes for at least 9 experimentally verified and validated functional TFs in promoter sequences. The order and type of TF binding to the promoter of genes encoding central metabolic pathway (CMP) enzyme was tabulated. A new similarity measure was devised for scoring the similarity between a pair of promoter sequences based on the number and order of motifs. Further, these were grouped in clusters considering the scores between them. The distance between each of the clusters in individual pathway was calculated and a phylogenetic tree was developed. This method is further applied to other pathways such as lipid and amino acid biosynthesis to retrieve and compare experimentally verified and conserved TFBS.