title: Predicting protein folds with fold-specific PSSM libraries.
abstract: Accurately assigning folds for divergent protein sequences is a major obstacle to structural studies. Herein, we outline an effective method for fold recognition using sets of PSSMs, each of which is constructed for different protein folds. Our analyses demonstrate that FSL (Fold-specific Position Specific Scoring Matrix Libraries) can predict/relate structures given only their amino acid sequences of highly divergent proteins. This ability to detect distant relationships is dependent on low-identity sequence alignments obtained from FSL. Results from our experiments demonstrate that FSL perform well in recognizing folds from the "twilight-zone" SABmark dataset. Further, this method is capable of accurate fold prediction in newly determined structures. We suggest that by building complete PSSM libraries for all unique folds within the Protein Database (PDB), FSL can be used to rapidly and reliably annotate a large subset of protein folds at proteomic level. The related programs and fold-specific PSSMs for our FSL are publicly available at: http://ccp.psu.edu/download/FSLv1.0/.
authors.affiliation: Department of Computer Science and Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America.
authors.forename: Yoojin
authors.initials: Y
authors.lastname: Hong
authors.forename: Sree Vamsee
authors.initials: SV
authors.lastname: Chintapalli
authors.forename: Kyung Dae
authors.initials: KD
authors.lastname: Ko
authors.forename: Gaurav
authors.initials: G
authors.lastname: Bhardwaj
authors.forename: Zhenhai
authors.initials: Z
authors.lastname: Zhang
authors.forename: Damian
authors.initials: D
authors.lastname: van Rossum
authors.forename: Randen L
authors.initials: RL
authors.lastname: Patterson
mesh_terms: D008958:Models, Molecular; D017510:Protein Folding; D040901:Proteomics; D016415:Sequence Alignment