Computational Phylogenetic Study and Data Mining Approach to Laccase Enzyme Sequences

Abstract

Currently data mining is an essential tool to discover the hidden data and important patterns from a large data set. The present work is a pilot study that compares the result of sequence based phylogenetic study and some of the physicochemical and structural feature based clustering of Laccase enzyme sequences. Total of 50 homologous sequences were obtained specific to each of the organism like plant, fungi and bacteria. Multiple sequences alignment of sequences was performed followed by phylogenetic tree construction and consistency study also to observe the major clusters. Again the major domain and motif analysis was done to support the study in the divergence pattern of Laccase enzyme sequences. There after 13 numbers of physicochemical and structural features were computed for each enzyme sequences. Then data normalisation and k-means clustering technique revealed that the fungi, bacteria and plant were obtained in three distinct clusters. The analysis indicates that the result of sequence based classification is in a good agreement with physicochemical basis of classification of proteins. The methods can be further optimised for different clustering algorithm to obtain specific physicochemical features that would help to classification of proteins.

Biochemical and Molecular Analysis of Laccase Enzyme in Saprobic Fungus; Sordaria fimicola

“…3). The fifty specific laccase gene sequences from different organisms including fungi were compared by multiple sequence alignment and results of the phylogenetic analysis reported diversity of the derived proteins (Satpathy et al, 2013). The protein coding genes have been used to study the phylogenetic analysis among Ascomycetes and Zygomycetes fungi as reported earlier by several coworkers (Diezmann et al, 2004;Tanabe et al, 2004).…”

Short Communication: Preliminary phylogenetic analysis of bacteria producing laccase isolated from Gunung Pancar, Bogor, Indonesia

“…The complete alignment of these sequences with a Clustal-X instrument was combined using the MEGA X software. The phylogenetic tree showed a taxonomic clustering through the major taxa (Satpathy 2014). The neighboring relationship of sequences was demonstrated by constructing a phylogenetic tree (Figure 4).…”

“…The distance matrix of the suitable clustering system is used to create the phylogenetic tree. Mostly, phylogenetic analysis of enzyme sequences is a powerful instrument for group and interpretation of the taxa (Satpathy 2014). Surely, phylogenetic tree interpretation is constructed for most of the comparative evolutionary biology.…”