Proteomic Analysis in Diabetic Cardiomyopathy using Bioinformatics Approach

• Published in: Bioinformatics and biology insights Vol. 2
• Main Authors: Allam Appa Rao, Hanuman Thota, Ramamurthy Adapala, Suresh Babu Changalasetty, Ramachandra Sridhar Gumpeny, Annapurna Akula, Lalitha Saroja Thota, Siva Reddy Challa, M.R. Narasinga Rao, Undurti N. Das M.D., FAMS
• Format: Journal Article
• Language: English
• Published: SAGE Publishing 01.01.2008
• ISSN: 1177-9322
• DOI: 10.4137/BBI.S313

Diabetic cardiomyopathy is a distinct clinical entity that produces asymptomatic heart failure in diabetic patients without evidence of coronary artery disease and hypertension. Abnormalities in diabetic cardiomyopathy include: myocardial hypertrophy, impairment of contractile proteins, accumulation of extracellular matrix proteins, formation of advanced glycation end products, and decreased left ventricular compliance. These abnormalities lead to the most common clinical presentation of diabetic cardiomyopathy in the form of diastolic dysfunction. We evaluated the role of various proteins that are likely to be involved in diabetic cardiomyopathy by employing multiple sequence alignment using ClustalW tool and constructed a Phylogenetic tree using functional protein sequences extracted from NCBI. Phylogenetic tree was constructed using Neighbour—Joining Algorithm in bioinformatics approach. These results suggest a causal relationship between altered calcium homeostasis and diabetic cardiomyopathy that implies that efforts directed to normalize calcium homeostasis could form a novel therapeutic approach.