Current advances in disulfide connectivity predictions

The formation of disulfide bonds between cysteine residues stabilizes protein structures, and thus, plays critical roles in protein folding, function, and evolution. Essentially, knowing the disulfide connectivity pattern is helpful in predicting the three-dimensional structures of proteins due to its capability to restrain the flexibility of protein structures and to reduce the search in the conformational space. As a result, disulfide connectivity prediction from protein sequences has become more attractive and feasible with the rapid accumulation of complete genome sequences and the advances in bioinformatics and machine learning methods. In this review, we will describe the methods associated with disulfide bonding state and connectivity prediction in detail. In addition, the main issues and limitations will also be presented along with the methods discussed. Finally, the practical applications and some possible future directions of disulfide connectivity predictions will also be mentioned.