Briefings in Functional Genomics Advance Access published online on March 27, 2008
Briefings in Functional Genomics, doi:10.1093/bfgp/eln008
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A review of algorithmic techniques for disulfide-bond determination
Corresponding author. Rahul Singh, Department of Computer Science, San Francisco State University, San Francisco, CA 94132, USA. Tel: + 415-338-2307; Fax: + 415-338-6826; E-mail: rsingh{at}cs.sfsu.edu
Disulfide bonds play an important role in understanding protein folding, evolution, and in studies related to determining structural and functional properties of specific proteins. At the state-of-the-art, a large number of computational techniques have been proposed for determining disulfide bonds. Operating across the gamut of input data, from pure sequence-based information to spectra from mass spectrometry, these techniques provide researchers with a variety of methodological choices and trade-offs. Techniques for disulfide-bond determination are also underpinned by a rich variety of algorithmic formulations. Analysis of these algorithms can provide valuable cues towards choosing a particular technique and understanding its results. Further, their study is critical in developing the next generation of techniques. This paper discusses the importance and applicability of disulfide-bond determination in understanding protein structure and function and provides a detailed review of computational approaches to this problem.
Keywords: disulfide bonds, proteomics, mass spectrometry, machine learning, review