Diabeticretinopathy is the leading cause of blindness in adults with diabetes and it isfrequently occurring complication of diabetes mellitus feared by many diabeticpatients across the world. There are several proteins which are believed to beinvolved in diabetic retinopathy. In this study we have evaluated such proteinswhich are likely to be part of diabetic retinopathy by utilizing multiplesequence alignment tool viz., ClustalOmega, and designed a phylogenetic tree ofmultiple protein sequences obtained from National Center for BiotechnologyInformation (NCBI).
Here data mining technique called sequence mining plays akey role in extracting protein sequences from the database. Sequence miningtechnique is specialized in analyzing sequential patterns which are relevantand distinct from one another and utilizing retrieved sequences similarity and distancebetween different protein sequences can be analyzed. Phylogram wasconstructed using Neighbor-Joining Algorithm in Sequence MiningTechniques approach. From the phylogenetic tree it was recognizedthat aldose reductase and nitric oxide synthase has close connection withdiabetic retinopathy. It is likely that vascular endothelial growth factor,pro-inflammatory cytokines, advanced glycation end products, and adhesionmolecules additionally assume a part in diabetic retinopathy by modulatingaldose reductase and nitric oxide synthase activities.
These outcomes inferthat techniques intended to standardize aldose reductase and nitric oxidesynthase activities could be of huge advantage and provide benefit incounteractive action and treatment of diabetic retinopathy. The finalobservations obtained using sequential mining techniques denotes that methodsdesigned to standardize placenta growth factor and vascular endothelial growthfactor synthase activities could be of significant advantage in the inhibitionand treatment of diabetic retinopathy in era of new therapeutic interventions.