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Secondary Structure Prediction of proteins causing Diabetic Foot Ulcers using Artificial Neural Networks

KunjamNageswara Rao, P srinivasa Rao, AllamAppaRao, G.R Sridhar

The main aim is Secondary Structure Prediction of proteins causing Diabetic Foot Ulcers using Artificial Neural Networks.Protein structure prediction is one of the most important goals pursued by bioinformatics. The knowledge or prediction of secondary structure improves detection and alignment of remote homologs and helps for drug design. The purpose of this study is to identify the Secondary Structure of proteins causing foot problems in patients with diabetes, which is a major public health concern these days. The most feared factor among the diabetic patients is lower extremity amputation. The sequence of events leading to amputation is initiated by ulceration combined with sensation loss. To prevent complications and amputations it is necessary to detect the foot at risk of plantar ulceration at an early stage of sensation loss. To access the severity of foot ulcer, here Artificial Neural Networks is used to predict the secondary structure of proteins like P14780, P01137, P01912, P18462, P30499. By using this method the recognition of risk factors will be analyzed in efficient manner. Based on the severity of foot ulcer, preventive foot maintenance and regular foot examinations will take place in diabetes patients.to an early diagnosis and treatment against diabetic foot.