Biology – Quantitative Biology – Quantitative Methods
Scientific paper
2010-08-29
Biology
Quantitative Biology
Quantitative Methods
22 pages, 11 figures
Scientific paper
Accurately assigning folds for divergent protein sequences is a major obstacle to structural studies and underlies the inverse protein folding problem. Herein, we outline our theories for fold-recognition in the "twilight-zone" of sequence similarity (<25% identity). Our analyses demonstrate that structural sequence profiles built using Position-Specific Scoring Matrices (PSSMs) significantly outperform multiple popular homology-modeling algorithms for relating and predicting structures given only their amino acid sequences. Importantly, structural sequence profiles reconstitute SCOP fold classifications in control and test datasets. Results from our experiments suggest that structural sequence profiles can be used to rapidly annotate protein folds at proteomic scales. We propose that encoding the entire Protein DataBank (~1070 folds) into structural sequence profiles would extract interoperable information capable of improving most if not all methods of structural modeling.
Bhardwaj Gaurav
Hong Yoojin
Ko Kyung Dae
Patterson Randen L.
van Rossum Damian B.
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