COFACTOR: an accurate comparative algorithm for structure-based protein function annotation
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TLDR
A new COFACTOR webserver for automated structure-based protein function annotation and was ranked as the best method for protein–ligand binding site predictions in the recent community-wide CASP9 experiment.Abstract:
We have developed a new COFACTOR webserver for automated structure-based protein function annotation. Starting from a structural model, given by either experimental determination or computational modeling, COFACTOR first identifies template proteins of similar folds and functional sites by threading the target structure through three representative template libraries that have known protein-ligand binding interactions, Enzyme Commission number or Gene Ontology terms. The biological function insights in these three aspects are then deduced from the functional templates, the confidence of which is evaluated by a scoring function that combines both global and local structural similarities. The algorithm has been extensively benchmarked by large-scale benchmarking tests and demonstrated significant advantages compared to traditional sequence-based methods. In the recent community-wide CASP9 experiment, COFACTOR was ranked as the best method for protein-ligand binding site predictions. The COFACTOR sever and the template libraries are freely available at http://zhanglab.ccmb.med.umich.edu/COFACTOR.read more
Citations
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I-TASSER server: new development for protein structure and function predictions
Jianyi Yang,Yang Zhang +1 more
TL;DR: Focuses have been made on the introduction of new methods for atomic-level structure refinement, local structure quality estimation and biological function annotations, which are designed to address the requirements from the user community and to increase the accuracy of modeling predictions.
Conflict of interest statement. None declared.
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Protein–ligand binding site recognition using complementary binding-specific substructure comparison and sequence profile alignment
TL;DR: Two new methods, one based on binding-specific substructure comparison (TM-Site) and another on sequence profile alignment (S-SITE), for complementary binding site predictions are developed, which demonstrate a new robust approach to protein-ligand binding site recognition, ready for genome-wide structure-based function annotations.
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BioLiP: a semi-manually curated database for biologically relevant ligand–protein interactions
TL;DR: To facilitate template-based ligand–protein docking, virtual ligand screening and protein function annotations, a hierarchical procedure for assessing the biological relevance of ligands present in the PDB structures is developed which involves a four-step biological feature filtering followed by careful manual verifications.
Journal ArticleDOI
COFACTOR: improved protein function prediction by combining structure, sequence and protein–protein interaction information
TL;DR: Large-scale benchmark tests show that the new hybrid COFACTOR approach significantly improves the function annotation accuracy of the former structure-based pipeline and other state-of-the-art functional annotation methods, particularly for targets that have no close homology templates.
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