Manoharan Malini, Sankar Kannan, Offmann Bernard, Ramanathan Sowdhamini
Université de La Reunion, DSIMB, INSERM UMR-S 665, La Reunion, France. ; National Centre for Biological Sciences, Tata Institute for Fundamental Research, GKVK campus, Bangalore, INDIA. ; Manipal University, Madhav Nagar, Manipal, Karnataka, India.
Bioinform Biol Insights. 2013 Jul 22;7:231-51. doi: 10.4137/BBI.S11096. Print 2013.
Proteins may be related to each other very specifically as homologous subfamilies. Proteins can also be related to diverse proteins at the super family level. It has become highly important to characterize the existing sequence databases by their signatures to facilitate the function annotation of newly added sequences. The algorithm described here uses a scheme for the classification of odorant binding proteins on the basis of functional residues and Cys-pairing. The cysteine-based scoring scheme not only helps in unambiguously identifying families like odorant binding proteins (OBPs), but also aids in their classification at the subfamily level with reliable accuracy. The algorithm was also applied to yet another cysteine-rich family, where similar accuracy was observed that ensures the application of the protocol to other families.
蛋白质可能作为同源亚家族彼此非常特异性地相关。蛋白质在超家族水平上也可能与多种不同的蛋白质相关。通过其特征对现有序列数据库进行表征,以促进新添加序列的功能注释变得非常重要。这里描述的算法使用一种基于功能残基和半胱氨酸配对对气味结合蛋白进行分类的方案。基于半胱氨酸的评分方案不仅有助于明确识别气味结合蛋白(OBP)等家族,还能以可靠的准确性辅助它们在亚家族水平上的分类。该算法还应用于另一个富含半胱氨酸的家族,观察到了类似的准确性,这确保了该方案可应用于其他家族。