Prediction of Oligomeric Status of Quaternary Protein Structure by using Sequential Minimal Optimization for Support Vector Machine

Abstract

The prediction of quaternary structure and its function is important in pharmaceutical applications, drug design, medical or engineering applications. With the drastic rise in the number of protein sequences presented to the public database, acquiring an understanding of possible quaternary structural characteristics of their interested proteins in a timely way is essential for structural genomics research. There is a need for a method to identify quaternary attributes based on its amino acid sequence. In this study, discrimination of hetero-oligomer from non hetero-oligomer was demonstrated using amino acid composition implemented using a support vector machine with a minimum sequential optimization technique.