Computational approaches to predict protein structure have gained much attention in the fields of protein engineering and protein folding studies. Due to the vastness of conformational space, one of the major tasks is to restrain the flexibility of protein structure and reduce the search space. Many studies have revealed that, with the information of disulfide connectivity available, the search in conformational space can be dramatically reduced and lead to significant improvements in the prediction accuracy. As a result, predicting disulfide connectivity using bioinformatics approaches is of great interest nowadays. In this review, recent advances in disulfide connectivity predictions will be presented in detail. The predictions of disulfide bonding state and disulfide connectivity patterns will be covered. The effects of the features on the prediction accuracy will be compared and discussed. Finally, the practical uses and applications of the predicted disulfide bonding patterns will be illustrated. This review should serve as a reference for issues related to protein structure predictions.
Keywords: Protein engineering, protein folding, conformational space, disulfide connectivity, bioinformatics, molecular simulation