In silico approach to evaluate evolutionary relatedness of significant Lung cancer proteins.

Lung cancer is feared to be deadly and is caused due to the involvement of a cascade of proteins significant among which are EPAS1, Thrombomodulin, Metallothionein and Matrix Metallo Proteinase. The evolutionary aspects of these proteins are important to study the extent of conservation and mutation across different generations in diverse species. The rooted and unrooted tree would depict the relatedness among organisms and the ancestor of the organisms involved in the study. The evolutionary histories of groups of species are one of the most widely used tools throughout the life sciences, as well as objects of research with in systematic, evolutionary biology. In every phylogenetic analysis reconstruction produces trees. These trees represent the evolutionary histories of many groups of organisms, bacteria due to horizontal gene transfer and plants due to process of hybridization. Through comparison with several species of healthy organism, one may determine where the defective mutation is located, and then determine how to treat the disease. This strategy may help us to identify the mutations that had occurred in evolutionary conserved residues. We feel this method can be useful for understanding evolutionary rate variation, and for understanding selection variation on different characters. The various tree topologies along with their significant homolog’s would enable a thorough understanding of the disease.