Journal of Proteomics & Bioinformatics
Open Access

Abstract

Functional Protein Analysis of Hypertriglyceridemia: A Bioinformatic Approach

V. Srinivasa Rao, Sussant Kumar Das and V. Janardhana Rao

Hypertriglyceridemia is defined as an abnormal concentration of triglycerides in blood and is a commonly encountered lipid abnormality frequently associated with other lipid and metabolic derangements. Prolonged hypertriglyceridemia may produce neuropathological and abnormal metabolic changes particularly in peripheral sensory nerves. In the present study, we evaluated the role of several proteins that are likely to be involved in hypertriglyceridemia by employing multiple sequence alignment using ClustalW tool and constructed a phylogenic tree using functional protein sequences extracted from NCBI. The phylogeny tree was constructed with Neighbor Joining Algorithm using bioinformatic principles and applications. The association of apolipoprotein C-II, proinsulin, fatty acid binding protein, sterol regulatory element binding transcription factor, angiotensin I converting enzyme, lipin 1, sterile co-A desaturase, cholesteryl ester transfer protein, and other apolipoproteins in hypertriglyceridemia suggests that a close interaction between these proteins may exist that may underlie the pathogenesis of hypertriglyceridemia. The results of the present bioinformatics study indicate a predominant involvement of apolipoprotein C-II, proinsulin in comparison to other proteins in the pathogenesis of hypertriglyceridemia.