Bioinformatics approaches for disulfide connectivity prediction.
Protein structure prediction with computational methods has gained much attention in the research 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 mini-review, the prediction of disulfide connectivity in proteins will be discussed in four aspects: (1) how the problem formulated and the computational techniques used in the literatures; (2) the effects of the features adopted to encode the information and the biological meanings implied; (3) the problems encountered and limitations of disulfide connectivity prediction; and (4) the practical usages of predicted disulfide bond information in molecular simulation and the prospects in the future.
Tsai
Chi-Hung
CH
Department of Chemical Engineering and Biotechnology and Graduate Institute of Biotechnology, National Taipei University of Technology, Taiwan.
Chan
Chen-Hsiung
CH
Chen
Bo-Juen
BJ
Kao
Cheng-Yan
CY
Liu
Hsuan-Liang
HL
Hsu
Jyh-Ping
JP
D000595:Amino Acid Sequence; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D003545:Cysteine / Q000737:chemistry; D004220:Disulfides / Q000737:chemistry*; D004355:Drug Stability; D006801:Humans; D006860:Hydrogen Bonding; D008958:Models, Molecular; D008968:Molecular Conformation; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism; D014568:Urokinase-Type Plasminogen Activator / Q000737:chemistry
D004220:Disulfides; D011506:Proteins; D014568:Urokinase-Type Plasminogen Activator; D003545:Cysteine