Department of Computer Science
Fold recognition techniques take advantage of the limited number of overall structural organizations, and have become increasingly effective at identifying the fold of a given target sequence. However, in the absence of sufficient sequence identity, it remains difficult for fold recognition methods to always select the correct model. While a native-like model is often among a pool of highly ranked models, it is not necessarily the highest-ranked one, and the model rankings depend sensitively on the scoring function used. Structure elucidation methods can then be employed to decide among the models based on relatively rapid biochemical/biophysical experiments.
Xiong F, Friedman AM, Bailey-Kellogg C. Planning combinatorial disulfide cross-links for protein fold determination. BMC Bioinformatics. 2011 Nov 24;12 Suppl 12(Suppl 12):S5. doi: 10.1186/1471-2105-12-S12-S5. PMID: 22168447; PMCID: PMC3247086.
Dartmouth Digital Commons Citation
Xiong, Fei; Friedman, Alan M; and Bailey-Kellogg, Chris, "Planning Combinatorial Disulfide Cross-Links for Protein Fold Determination" (2011). Dartmouth Scholarship. 568.