Disulfide bonding detection software tools | Protein structure data analysis
Disulfide bonds play an important role in protein folding and structure stability. Accurately predicting disulfide bonds from protein sequences is important for modeling the structural and functional characteristics of many proteins.
A framework for disulphide bridge predictions. DIpro provides graphical models and recursive neural networks to predict the bonding probability of each pair of cysteines, leveraging in addition secondary structure and relative solvent accessibility information. DIpro infers the disulphide bridge connectivity of each protein chain, which in turn yields a solution for both the bridge and residue classification problems, even in the case where the bonding state of individual cysteines is not known.
Provides prediction of disulfide bonding connectivity pattern without the prior knowledge of the bonding state of cysteines. The method used in this server improves the accuracy of disulfide connectivity pattern prediction (Qp) over the previous studies reported in the literature.