Frequency Rank Vector based Phylogeny: A new Alignment-Free Protein Sequence Comparison

The expansion of protein sequence research has emerged as a prominent area of focus in the field of bioinformatics. The growing need for accurate evolutionary relationships has spurred researchers to develop sophisticated methodologies. Alignment-free methods have demonstrated greater efficiency and effectiveness in time and space utilization compared to alignment-based methods for sequence analysis. This paper proposes an alignment-free approach utilizing DNA codon encoding of amino acids, incorporates Frequency-Rank vector and Shannon Entropy as sequence features, to compute a distance matrix. Next, phylogenetic trees are generated for a range of protein sequences. These trees are then compared with trees derived by others. Moreover, the validation process involved comparing this approach to the Clustal Omega method, considering symmetric distance and computational time. The findings depict that the alignment-free method offers accurate species classifications and increased computational efficiency compared to existing methods. Therefore, the proposed method offers a new perspective on protein sequence analysis, potentially providing advantages over traditional methods and enabling researchers to cross-validate and compare results more effectively. This efficiency leads to a more comprehensive understanding of the evolutionary relationships among the protein sequences.